http://scm.gsom.spbu.ru/index.php?title=Special:Contributions/Storch&feed=atom&limit=50&target=Storch&year=&month=Supply Chain Management Encyclopedia - User contributions [en]2024-03-28T23:05:49ZFrom Supply Chain Management EncyclopediaMediaWiki 1.16.5http://scm.gsom.spbu.ru/Supply_chain_managementSupply chain management2011-08-22T19:10:12Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_цепями_поставок Управление цепями поставок]'''<br />
<br />
Supply chain management (SCM) is a successful business practice, an effective strategy and a popular concept. According to many surveys, it is important for a growing number of companies all over the world. SCM concept is a mix of various concepts<ref> Гиюниперо Л. и др., 2011. Десять лет исследований в сфере управления цепями поставок: прошлое, настоящее и выводы для будущего. Российский журнал менеджмента 9 (2)</ref>. SCM combines the goals of logistics (minimizing of total costs in supply chain) and of operations management (efficient inventory and production management), of marketing (value creation and customer satisfaction) and of relationship marketing (cooperating with partners in a [[supply chain]]), as well as of other disciplines. Hence, it is obvious that explanation of approaches to management of a network of relationships and enjoying total costs minimization with a given level of customer satisfaction a multidisciplinary approach is required. <br />
The practice of managing supply chains (followed by a theory of SCM) appeared as an answer to new economic challenges in late 1970s – early 1980s, when macroeconomic environment of a world economy stagnation after the oil crisis required efforts on developing new managerial decisions and concepts<ref> Черенков В. И. (2004) Эволюция маркетинговой теории и трансформация доминирующей парадигмы маркетинга. Вестник Санкт-Петербургского Университета. Сер. Менеджмент 2: 3-32</ref>. One of the survival conditions for the companies at that time was a decrease in logistics costs. At the same time the managers found out pretty soon that the reason of dramatically increased logistics cost was not only transportation costs, but costs of safety stocks, obsolete inventories, cost of lost revenues because of out-of-stock situations, etc. The problems listed above are the problems of the [[bullwhip effect]] in [[supply chain]]. The bullwhip effect means that partners in supply chain do not have the information of real sales and have to creae safety stocks of goods and materials. The core competence paradigm<ref> Prahalad C.K. and Hamel, G (1990) The core competence of the corporation, Harvard Business Review, 68 (3): 79-91.</ref>, that was introduced and dominated in 1990s made this problem even worse, because companies started to concentrate on their own core competences and outsource the rest of the functions. It increased the number of actors in supply chain and made information flow more difficult. Obvious and logical decision was to organize the '''coordinated''' flow of materials and finished goods by exchanging reliable and relevant information<ref> Oliver K. and Webber M. (1982) Supply chain management: Logistics catches up with strategy. In: Christopher M. (ed.) Logistics, The Strategic Issues. Champan and Hall: London; 63–75.</ref>. This concept was named a supply chain management and later developed towards more complex coordination systems and integration of core business processes<ref> Croom S. R., Romano P. and Giannakis M. (2000) Supply chain management: an analytical framework for critical literature review. European Journal of Purchasing and Supply Management 7: 29–37</ref>. As a result supply chain differs from vertically-integrated corporation of the beginning of XX century by the fact, that supply chain consists of separate, formally independent (in reality tightly interdependent), concentrated on own core competences organizations, that have common goal to minimize costs in supply chain and maximize value for the ultimate customer. <br />
<br />
In literature different approaches of supply chain management might be found. Some of them contradict each other<ref> Burgess K., Singh P. and Koroglu, R. (2006) Supply Chain Management: A Structured Literature Review and Implications for Future Research. International Journal of Operations and Production Management, 26, (7), 703-729.</ref>. The definition basically depends on position of the author: logistics, operations management, marketing, etc. For instance, logistics and operation management specialists concentrate on optimization of business processes<ref> Lamming R., Johnsen T., Zheng J. and Harland C. (2000). An initial classification of supply networks. International Journal of Operations & Production Management, 20, (6), 675-691.</ref>, on the other hand, marketing specialists – on service level and value for the customer<ref> Jüttner U., Christopher M. and Baker S. (2007) Demand chain management — integrating marketing and supply chain management / U. Jüttner, // Industrial Marketing Management. – Vol. 36, № 5. p. 377-392</ref>,<ref>Кирюков С. И., Кротов К. В. (2007) Развитие концепции управления цепями поставок: маркетинговый подход. Вестник С.-Петербургского ун-та. Сер. Менеджмент (4): 97–111.</ref>. <br />
<br />
Attempts to make a unified, single definitions are still not very successful. For instance, Stock and Boyer tried to make a synthetic definition on the base of 173 given definitions: “The management of a network of relationships within a firm and between interdependent organizations and business units consisting of material suppliers, purchasing, production facilities, logistics, marketing, and related systems that facilitate the forward and reverse flow of materials, services, finances and information from the original producer to final customer with the benefits of adding value, maximizing profitability through efficiencies, and achieving customer satisfaction”<ref> Stock R., Boyer S., 2009 Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management 39 (8): 690-711</ref>. However, this synthetic definition has its own disadvantages: it is not focused and too “heavy”.<br />
<br />
Some other SCM definitions: <br />
* '''Council of Supply Chain Management Professionals (CSCMP):''' SCM is encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all Logistics Management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third party service providers, and customers. In essence, Supply Chain Management integrates supply and demand management within and across companies<ref>Council of Supply Chain Management Professionals (CSCMP) - www.cscmp.org</ref><br />
*'''Mentzer et al. (2001):''' SCM is the systematic, strategic coordination of the traditional business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole<ref>Mentzer J.T., DeWitt W., Keebler J.S., Min S., Nix N.W., Smith C.D. and Zacharia Z.G. (2001)<br />
Defining supply chain management, Journal of Business Logistics, Vol. 22 No. 2, pp. 1-25. </ref>.<br />
*'''Larson and Rogers (1998):''' SCM is the coordination of activities, within and between vertically linked firms, for the purpose of serving end customers at a profit<ref>Larson P. and Rogers D. (1998) Supply chain management: definition growth and approaches, Journal of Marketing Theory and Practice, Vol. 6 No. 3, pp. 1-5</ref>.<br />
<br />
==Supply Chain Management Frameworks== <br />
<br />
SCM frameworks or models are reference points for practitioners and researcher. Below there are two basic frameworks: SCOR and Metzer model that are most popular in specialized literature. <br />
<br />
====Supply Chain Operations Reference (SCOR)====<br />
[[File:Scm SCOR.jpg|thumb|The Supply Chain Operations Reference (SCOR) model ]] <br />
<br />
The Supply Chain Operations Reference (SCOR) model, developed by the Supply Chain Council<br />
(SCC) and AMR Research in 1996 is one of the most popular models. According to Supply Chain Council, this model provides a unique framework that links business processes, metrics, best practices<br />
and technology features into a unified structure to support communication among supply chain partners<br />
and to improve the effectiveness of supply chain management and related supply chain improvement<br />
activities<ref>( Supply Chain Council, 2009)</ref>. SCOR is used to identify, measure, reorganize and improve supply chain processes through a cyclical process that includes:<br />
*Capturing the configuration of a supply chain<br />
*Measuring the performance of the supply chain and comparing against internal and external<br />
industry goals<br />
*Re-aligning supply chain processes and best practices to fulfill unachieved or changing business<br />
objectives<br />
The SCOR model five processes: plan, source, make, deliver and return. Each process is<br />
implemented through four individual levels. The first level defines the scope and content of the model itself, as well as specifying basis for competition performance targets. At level two, companies implement their operations strategies dependent upon the configurations they choose for their supply chains. Level three defines inputs, outputs, and flows of each transactional element, and finally, level four defines the implementation of specific supply chain management practices<ref> Lockamy III, A. and McCormack, K. (2004). Linking SCOR planning practices to supply chain performance, an exploratory study. International Journal of Operations & Business Management, 24, (12), 1192-1218.</ref> The source, make, and deliver processes of the SCOR model create a continuous chain of activity<br />
throughout a company’s internal operations and, potentially, across the whole inter-organizational supply<br />
chain.<br />
<br />
====The Mentzer Model====<br />
[[File:SCM mentzer.png|thumb|The Mentzer model]]<br />
<br />
Mentzer and his colleagues defined supply chain management in this analysis as “the systematic, strategic coordination of the traditional business functions and tactics across these business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long term performance of the individual companies and the supply chain as a whole.” <br />
<br />
According to this definition, SCM includes multiple firms (supply chain actors) and multiple business activities. The definition is accompanied with the model (see figure). The supply chain looks like a pipeline that includes supply chain flows (services, products, information, materials, money, etc.), inter-functional coordination of business functions (marketing, sales, research and development, forecasting, production, logistics, etc.), which based on trust, commitment, risk and dependence. Mentzer model assumes, that at the end of supply chain there should be two important outcomes: greater customer satisfaction at less costs due to better organization of all flows. These two outcomes form competitive advantage on other supply chains (not individual companies).<br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T19:08:13Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. The principles of management usually are agreed with the retailer beforehand, and are '''based on the retailer’s sales information'''. The supplier assumes responsibility for monitoring '''sales and inventory'''. VMI helps to increase efficiency of the supply chain. The main difference from “general approach” is that in the latter the information about customer’s (retailer’s) sales and inventory level usually is not shared with the upstream companies and this makes inventory management complicated for both the customer and the supplier. The first attempt to introduce VMI was undertaken by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
The transfer of ownership in VMI system is similar to those in consignment arrangements where ownership of the goods is automatically transfered to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for the latter<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system the supplier can observe every item (associated with this supplier) in the customer’s warehouse. In summary, VMI system reduces out-of-stock situations and increase efficiency of the supply chain through the following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by the manufacturer or the distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain to the manufacturer / vendor who is in a better position to support the objectives of the entire integrated supply chain we may achieve a sustainable competitive advantage: <br />
* The manufacturer is responsible for maintaining the distributors inventory levels<br />
* Collaborative supply chain initiative<br />
* Optimizing supply chain performance<br />
* The manufacturer has access to the distributor's inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as <ref>Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
* influence of compensation: usually bonuses depend on efforts of the sales force, but under the VMI system sales force cannot influence its compensation,<br />
* loss of control over inventory level,<br />
* downsizing,<br />
* possible technical problems with VMI system,<br />
* a concern that reduced inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still some factors preventing its extensive implementation by companies. However, the potential benefits for both parties – the supplier and the customer – make the VMI approach an attractive, lucrative and attainable perspective.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T18:46:19Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. The principles of management usually are agreed with the retailer beforehand, and are '''based on the retailer’s sales information'''. The supplier assumes responsibility for monitoring '''sales and inventory'''. VMI helps to increase efficiency of the supply chain. The main difference from “general approach” is that in the latter the information about customer’s (retailer’s) sales and inventory level usually is not shared with the upstream companies and this makes inventory management complicated for both the customer and the supplier. The first attempt to introduce VMI was undertaken by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
The transfer of ownership in VMI system is similar to those in consignment arrangements where ownership of the goods is automatically transfered to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for the latter<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system the supplier can observe every item (associated with this supplier) in the customer’s warehouse. In summary, VMI system reduces out-of-stock situations and increase efficiency of the supply chain through the following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by the manufacturer or the distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain to the manufacturer / vendor who is in a better position to support the objectives of the entire integrated supply chain we may achieve a sustainable competitive advantage: <br />
* The manufacturer is responsible for maintaining the distributors inventory levels<br />
* Collaborative supply chain initiative<br />
* Optimizing supply chain performance<br />
* The manufacturer has access to the distributor's inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T18:12:31Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. The principles of management usually are agreed with the retailer beforehand, and are '''based on the retailer’s sales information'''. The supplier assumes responsibility for monitoring '''sales and inventory'''. VMI helps to increase efficiency of the supply chain. The main difference from “general approach” is that in the latter the information about customer’s (retailer’s) sales and inventory level usually is not shared with the upstream companies and this makes inventory management complicated for both the customer and the supplier. The first attempt to introduce VMI was undertaken by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
VMI planning system is not associated with inventory ownership but as information sharing requirements are similar to those in consignment arrangements ownership transfers to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for him<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system supplier can observe every item (associated with this supplier) on customer’s warehouse. In summary, VMI decreases stock-outs and inventory in a supply chain thanks to following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by manufacturer or distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain, the manufacturer / vendor is in a better position to support the objectives of the entire integrated supply chain resulting in sustainable competitive advantage: <br />
*Manufacturer is responsible for maintaining the distributors inventory levels<br />
*Collaborative supply chain initiative<br />
*Optimizing supply chain performance<br />
*Manufacturer has access to the distributors inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are following <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T18:09:57Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. The principles of management usually are agreed with the retailer beforehand, and are '''based on retailer’s sales information'''. Supplier assumes responsibility to monitoring '''sales and inventory'''. VMI helps to efficiency increase a supply chain performance. The main difference from “general approach” is that usually the information about customer’s (retailer’s) sales and inventory level is not shared with upstream companies and this makes inventory management complicated for both a customer and a supplier. <br />
The first practice of VMI was introduced by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
VMI planning system is not associated with inventory ownership but as information sharing requirements are similar to those in consignment arrangements ownership transfers to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for him<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system supplier can observe every item (associated with this supplier) on customer’s warehouse. In summary, VMI decreases stock-outs and inventory in a supply chain thanks to following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by manufacturer or distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain, the manufacturer / vendor is in a better position to support the objectives of the entire integrated supply chain resulting in sustainable competitive advantage: <br />
*Manufacturer is responsible for maintaining the distributors inventory levels<br />
*Collaborative supply chain initiative<br />
*Optimizing supply chain performance<br />
*Manufacturer has access to the distributors inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are following <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T18:09:32Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. The principles of management usually are agreed with the retailer beforehand, and are ‘’’based on retailer’s sales information’’’. Supplier assumes responsibility to monitoring ‘’’sales and inventory’’’. VMI helps to efficiency increase a supply chain performance. The main difference from “general approach” is that usually the information about customer’s (retailer’s) sales and inventory level is not shared with upstream companies and this makes inventory management complicated for both a customer and a supplier. <br />
The first practice of VMI was introduced by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
VMI planning system is not associated with inventory ownership but as information sharing requirements are similar to those in consignment arrangements ownership transfers to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for him<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system supplier can observe every item (associated with this supplier) on customer’s warehouse. In summary, VMI decreases stock-outs and inventory in a supply chain thanks to following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by manufacturer or distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain, the manufacturer / vendor is in a better position to support the objectives of the entire integrated supply chain resulting in sustainable competitive advantage: <br />
*Manufacturer is responsible for maintaining the distributors inventory levels<br />
*Collaborative supply chain initiative<br />
*Optimizing supply chain performance<br />
*Manufacturer has access to the distributors inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are following <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T18:05:49Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. Basis on which decision will be made is agreed with the retailer beforehand, and is ‘’’based on retailer’s sales information’’’. Supplier assumes responsibility to monitoring ‘’’sales and inventory’’’. VMI helps to efficiency increase a supply chain performance. The main difference from “general approach” is that usually the information about customer’s (retailer’s) sales and inventory level is not shared with upstream companies and this makes inventory management complicated for both a customer and a supplier. <br />
The first practice of VMI was introduced by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
VMI planning system is not associated with inventory ownership but as information sharing requirements are similar to those in consignment arrangements ownership transfers to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for him<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system supplier can observe every item (associated with this supplier) on customer’s warehouse. In summary, VMI decreases stock-outs and inventory in a supply chain thanks to following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by manufacturer or distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain, the manufacturer / vendor is in a better position to support the objectives of the entire integrated supply chain resulting in sustainable competitive advantage: <br />
*Manufacturer is responsible for maintaining the distributors inventory levels<br />
*Collaborative supply chain initiative<br />
*Optimizing supply chain performance<br />
*Manufacturer has access to the distributors inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are following <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T18:05:20Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управляемые_поставщиком_запасы Управляемые поставщиком запасы'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. Basis on which decision will be made is agreed with the retailer beforehand, and is ‘’’based on retailer’s sales information’’’. Supplier assumes responsibility to monitoring ‘’’sales and inventory’’’. VMI helps to efficiency increase a supply chain performance. The main difference from “general approach” is that usually the information about customer’s (retailer’s) sales and inventory level is not shared with upstream companies and this makes inventory management complicated for both a customer and a supplier. <br />
The first practice of VMI was introduced by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
VMI planning system is not associated with inventory ownership but as information sharing requirements are similar to those in consignment arrangements ownership transfers to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for him<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system supplier can observe every item (associated with this supplier) on customer’s warehouse. In summary, VMI decreases stock-outs and inventory in a supply chain thanks to following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by manufacturer or distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain, the manufacturer / vendor is in a better position to support the objectives of the entire integrated supply chain resulting in sustainable competitive advantage: <br />
*Manufacturer is responsible for maintaining the distributors inventory levels<br />
*Collaborative supply chain initiative<br />
*Optimizing supply chain performance<br />
*Manufacturer has access to the distributors inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are following <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Vendor_managed_inventoryVendor managed inventory2011-08-22T17:48:33Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_запасами_поставщиком Управление запасами поставщиком]'''<br />
<br />
Vendor managed inventory (VMI) is an approach of inventory management and order fulfillment whereby the '''supplier, not the customer''', is responsible for managing and replenishing inventory. Basis on which decision will be made is agreed with the retailer beforehand, and is ‘’’based on retailer’s sales information’’’. Supplier assumes responsibility to monitoring ‘’’sales and inventory’’’. VMI helps to efficiency increase a supply chain performance. The main difference from “general approach” is that usually the information about customer’s (retailer’s) sales and inventory level is not shared with upstream companies and this makes inventory management complicated for both a customer and a supplier. <br />
The first practice of VMI was introduced by Wall-Mart and Procter-and-Gamble when these companies tried to minimize inventory costs and simplify inventory management on Pampers diapers<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>. <br />
VMI planning system is not associated with inventory ownership but as information sharing requirements are similar to those in consignment arrangements ownership transfers to the stocking location. Under VMI, the distributor monitors customers’ sales and inventory in order to place replenishment orders for him<ref> Badrakhan B. (2010) Data-Driven Vendor-Managed Inventory, Electrical Wholesaling, Vol. 91, Iss. 6, 32-34</ref>. In VMI system supplier can observe every item (associated with this supplier) on customer’s warehouse. In summary, VMI decreases stock-outs and inventory in a supply chain thanks to following factors<ref> Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
*shortening the supply chain,<br />
*centralization of forecasting,<br />
*acceleration of communication process on stock-outs and inventory level (because of [[EDI]]),<br />
*absence or less frequent promotions (by manufacturer or distributor),<br />
*increase in loyalty to a supplier and improving of relationships in a supply chain.<br />
By pushing the decision making responsibility further up the supply chain, the manufacturer / vendor is in a better position to support the objectives of the entire integrated supply chain resulting in sustainable competitive advantage: <br />
*Manufacturer is responsible for maintaining the distributors inventory levels<br />
*Collaborative supply chain initiative<br />
*Optimizing supply chain performance<br />
*Manufacturer has access to the distributors inventory data and is responsible for generating purchase orders<br />
<br />
==Advantages and Problems of VMI==<br />
<br />
The benefits of VMI system approach are following <ref>Evanko P. (2010) Vendor Managed Inventory, HVACR Distribution Business, Vol. 75, Iss. 12, 32-35</ref>:<br />
<br />
*Improved client service. Getting timely information from POS data, suppliers are able to respond better to customer’s needs providing required quantities in a right location at a certain time. <br />
<br />
*Decreased demand uncertainty. Through permanent monitoring of market demand flows and customer’s inventories, a distributor is supposed to reduce the number of large unplanned customer orders and, finally, move them off at all. <br />
<br />
*Decreased inventory requirements. VMI planning system helps a distributor to decrease the inventory requirements as he knows exactly how much inventory the customer disposes, therefore, there is no need to have reserve inventories in order to manage uncertain orders.<br />
<br />
*Decreased costs. Despite the fact that VMI planning system requires additional expenses on its launching and implementation, all elements of a supply chain – manufacturers, distributors and customers – will reduce costs by re-engineering and merging their order fulfillments and distribution center replenishment activities.<br />
<br />
*Improved customer retention. Installing of VMI system is a specific-related investment into long term relationship between supplier and customer. As the launching of the system costs a lot, switching costs for a customer is a relatively high so he will prefer to deal for a long time with the same supplier.<br />
<br />
*Decreased reliance on forecasting. By using VMI, a supplier gets instant data about customer’s inventories so a supplier do not have to make forecasts the customer’s demand for a product which typically contain loads of errors. <br />
In spite of growing popularity and potential advantages of VMI planning system it is not the only solution. In fact, this solution is not available to every company because many suppliers will consider it only for their major customers. In addition, many vendors who are powerful in the industry would not consider VMI system at all as it is more advantageous for the customer than for the vendor and for some vendors whose profit-margin is already not high this increased customers power may result into pushing them out of business<ref>Saxena R. (2009) Vendor-Managed Inventory, Industrial Engineer, Vol. 41, Iss. 7, 20-20</ref>.<br />
<br />
It is also important that VMI is not a doubtless guarantee of increased efficiency which goes back to the outsourcing problem. Ideally, VMI should be as easy as a delegating of logistics operations to a specialized company ([[3PL]]). However, a company should not choose a 3PL without conducting the proper diligence. Similarly, a company should not hand off a part of its supply chain to a vendor (even a trusted vendor) without assessment if this vendor is certainly better choice for handling logistics. Unless company’s suppliers have access to the same types of discounts, experience and engineering tools, companies that go into VMI relationships can significantly lose some logistics ground and pay the price in conditions of lower efficiency, decreased reliability and higher transit costs. As a result, VMI often faces resistance. There are some organizational concerns about roles and skills, trust and power shift such as<ref> Lapide L. (2008) Use VMI to Improve Forecasting, Journal of Business Forecasting, Vol. 27, Iss. 3, 28-30</ref>:<br />
*influence of compensation – bonuses depend on employees’ sale activities, but sales force has less influence under VMI,<br />
*loss of control under inventory level,<br />
*downsizing,<br />
*possible technical problems with VMI system,<br />
*a concern that decreases inventory may lead to less shelf space and loss of market share.<br />
Thus, VMI can be a significant shift in supply chain organization, but there are still obstacles for its extensive implementation by companies. However, the potential benefits for both parties – a supplier and a customer – make VMI approach attractive, lucrative and attainable.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Supply_chainSupply chain2011-08-22T17:45:57Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Цепь_поставок Цепь поставок]'''<br />
<br />
[[File:Supply chain.png|thumb|The supply chain.]] <br />
<br />
Supply chain is a set of several independent companies that are involved in sourcing of materials, manufacturing, distributing and selling the product for ultimate customer. The term supply chain appeared along with the term “[[supply chain management]]”, however supply chains exist whenever they are managed or not. Unlike the definitions of supply chain management, the definitions of supply chain are rather homogeneous:<br />
*A supply chain is a set of firms that pass materials forward <ref>La Londe and Masters (1994) Emerging Logistics Strategies: Blueprints for the Next Century, International Journal of Physical Distribution & Logistics Management</ref>. <br />
*A supply chain is the alignment of firms that bring products or services to market <ref>Stock J., Lambert D. and Ellram L. (1998) Fundamentals of Logistics Management </ref><br />
*A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request <ref>Chopra S. and Meindl P. (2003) Supply Chain Management: Strategy, Planning, and Operations</ref><br />
*A supply chain is a set of three or more entities (organizations or individuals) directly involved in the upstream and downstream flows of products, materials and/or information from a source to a customer<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>.<br />
It is important to note that these definitions of supply chain include the final consumer as part of it. Other authors see supply chain as a network of organizations, which is more closely to the reality:<br />
*A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials into intermediate and finished products, and the distribution of these finished products to customers <ref>Ganeshan R. and Harrison T.P. (1993) An introduction to supply chain management. </ref><br />
* A supply chain is the network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate consumer<ref>Christopher M. (1992) Logistics and Supply Chain Management: Strategies for Reducing Costs and Improve Services. – London: Financial Times; Pitman. – 320 p.</ref>.<br />
It is also important to note that any one organization can be a part of numerous supply chains.<br />
==Types of channel relationships==<br />
The relationships between the actors (buyers and sellers) play a key role in supply chains. The supply chain type depends on what kind of relationships are between players. There are two classifications of relationship types (or strategies) below: one given by J. Mentzer et al. (2001)<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>. and the other given by N. Campbell (2002)<ref>Campbell N. (2002) An international approach to organizational buying behavior. In: Ford D. (ed.). Understanding Business Marketing and Purchasing. 3rd ed. Thomson Learning: London; 389-401</ref>. <br />
====Types of relationships by J. Mentzer====<br />
[[File:supply chain types.png|thumb|Types of channel relationships]]<br />
According to Mentzer and his colleagues, there are three degrees of supply chain complexity: a "direct supply chain" an "extended supply chain" and an "ultimate supply chain" (see the figure). <br />
*'''A direct supply chain''' consists of a company, a supplier, and a customer involved in the upstream and/or downstream flows of products, services, finances, and/or information. This might be either very big vertically integrated corporation that doesn’t have important second tier suppliers or small one without resources or need to monitor second tier suppliers. <br />
*'''An extended supply chain''' includes suppliers of the immediate supplier and customers of the immediate customer, all involved in the upstream and/or downstream flows of products, services, finances, and/or information. This is traditional supply chain. <br />
*'''An ultimate supply chain''' includes all the organizations involved in all the upstream and downstream flows of products, services, finances, and information from the ultimate supplier to the ultimate customer.<br />
<br />
====Types of relationships by N. Campbell====<br />
<br />
N. Campbell described three types of relationship strategies: <br />
*'''Competitive''' – independent relationships; the price is determined by competitive market forces,<br />
*'''Cooperative''' – interdependent relationships; may create new value,<br />
*'''Command''' – dependent; one party has a dominant position.<br />
[[File:Campbell.png|thumb|Types of relationships strategies]]<br />
Any of this strategies might be implemented by one of the sides: by buyer or by seller, depending on what bargaining power does it have, what are the plans of this player, etc. Some parameters are listed below: <br />
*Product<br />
**Frequency of purchase<br />
**Switching cost due to physical and human investments<br />
**Product complexity<br />
**Industry characteristics<br />
*Concentration<br />
**Number of alternative partners<br />
**Intensity of competition<br />
**Traditions and norms<br />
*Company characteristics<br />
**Relative size<br />
**Preferred infrastructure style<br />
**Relative brand awareness<br />
**Centralization of purchasing<br />
*Individual characteristics<br />
**Relative brand awareness<br />
**Preferred interaction style<br />
**Perceived importance of the purchase<br />
**Risk aversion<br />
<br />
<br />
<br />
{| border="1"<br />
!colspan="5"|Relatioship strategies and recommendations <br />
|-<br />
| Buyer's strategy || Seller'strategy || Combination title || Recommendation for buyer || Recommendation for seller<br />
|-<br />
| Competitive|| Competitive || Perfect market || Play the market, Standardize requirements || Take it or leave it, Try to obtain lower costs, Try to differentiate<br />
|-<br />
| Competitive || Command || Sellers’s market || Accept gracefully, Buy jointly, Exchange information with other buyers, Complain, agitate, Encourage competitors || Take it or leave it, Form a cartel, Legitimize, Standardize the product<br />
|-<br />
| Command || Competitive || Buyer’s market || Put out trends; Play the market || Competitive bidding; Try to obtain lower costs or differentiate r<br />
|-<br />
| Cooperative || Cooperative || Domesticated market || Adapt, cooperate, work together || Customize, specialize, differentiate, innovate<br />
|-<br />
| Cooperative || Command || Captive market || Learn from the supplier || Educate the buyer<br />
|-<br />
| Command || Cooperative || Subcontract market || Educate the supplier || Learn from the buyer<br />
|-<br />
|}<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Supply_chainSupply chain2011-08-22T17:44:37Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Цепь_поставок Цепь поставок]'''<br />
<br />
[[File:Supply chain.png|thumb|The supply chain.]] <br />
<br />
Supply chain is a set of several independent companies that are involved in sourcing of materials, manufacturing, distributing and selling the product for ultimate customer. The term supply chain appeared along with the term “[[supply chain management]]”, however supply chains exist whenever they are managed or not. Unlike the definitions of supply chain management, the definitions of supply chain are rather homogeneous:<br />
*A supply chain is a set of firms that pass materials forward <ref>La Londe and Masters (1994) Emerging Logistics Strategies: Blueprints for the Next Century, International Journal of Physical Distribution & Logistics Management</ref>. <br />
*A supply chain is the alignment of firms that bring products or services to market <ref>Stock J., Lambert D. and Ellram L. (1998) Fundamentals of Logistics Management </ref><br />
*A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request <ref>Chopra S. and Meindl P. (2003) Supply Chain Management: Strategy, Planning, and Operations</ref><br />
*A supply chain is a set of three or more entities (organizations or individuals) directly involved in the upstream and downstream flows of products, materials and/or information from a source to a customer<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>.<br />
It is important to note that these definitions of supply chain include the final consumer as part of it. Other authors see supply chain as a network of organizations, which is more closely to the reality:<br />
*A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials into intermediate and finished products, and the distribution of these finished products to customers <ref>Ganeshan R. and Harrison T.P. (1993) An introduction to supply chain management. </ref><br />
* A supply chain is the network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate consumer<ref>Christopher M. (1992) Logistics and Supply Chain Management: Strategies for Reducing Costs and Improve Services. – London: Financial Times; Pitman. – 320 p.</ref>.<br />
It is also important to note that any one organization can be a part of numerous supply chains.<br />
==Types of channel relationships==<br />
The relationships between the actors (buyers and sellers) play a key role in supply chains. The supply chain type depends on what kind of relationships are between players. There are two classifications of relationship types (or strategies) below: one given by J. Mentzer et al. (2001)<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>. and the other given by N. Campbell (2002)<ref>Campbell N. (2002) An international approach to organizational buying behavior. In: Ford D. (ed.). Understanding Business Marketing and Purchasing. 3rd ed. Thomson Learning: London; 389-401</ref>. <br />
====Types of relationships by J. Mentzer====<br />
[[File:supply chain types.png|thumb|Types of channel relationships]]<br />
According to Mentzer and his colleagues, there are three degrees of supply chain complexity: a "direct supply chain" an "extended supply chain" and an "ultimate supply chain" (see the figure). <br />
*'''A direct supply chain''' consists of a company, a supplier, and a customer involved in the upstream and/or downstream flows of products, services, finances, and/or information. This might be either very big vertically integrated corporation that doesn’t have important second tier suppliers or small one without resources or need to monitor second tier suppliers. <br />
*'''An extended supply chain''' includes suppliers of the immediate supplier and customers of the immediate customer, all involved in the upstream and/or downstream flows of products, services, finances, and/or information. This is traditional supply chain. <br />
*'''An ultimate supply chain''' includes all the organizations involved in all the upstream and downstream flows of products, services, finances, and information from the ultimate supplier to the ultimate customer.<br />
<br />
====Types of relationships by N. Campbell====<br />
<br />
N. Campbell described three types of relationship strategies: <br />
*'''Competitive''' – independent relationships; the price is determined by competitive market forces,<br />
*'''Cooperative''' – interdependent relationships; developing new value,<br />
*'''Command''' – dependent; one party has a dominant position.<br />
[[File:Campbell.png|thumb|Types of relationships strategies]]<br />
Any of this strategies might be implemented by one of the sides: by buyer or by seller, depending on what bargaining power does it have, what are the plans of this player, etc. Some parameters are listed below: <br />
*Product<br />
**Frequency of purchase<br />
**Switching cost due to physical and human investments<br />
**Product complexity<br />
**Industry characteristics<br />
*Concentration<br />
**Number of alternative partners<br />
**Intensity of competition<br />
**Traditions and norms<br />
*Company characteristics<br />
**Relative size<br />
**Preferred infrastructure style<br />
**Relative brand awareness<br />
**Centralization of purchasing<br />
*Individual characteristics<br />
**Relative brand awareness<br />
**Preferred interaction style<br />
**Perceived importance of the purchase<br />
**Risk aversion<br />
<br />
<br />
<br />
{| border="1"<br />
!colspan="5"|Relatioship strategies and recommendations <br />
|-<br />
| Buyer's strategy || Seller'strategy || Combination title || Recommendation for buyer || Recommendation for seller<br />
|-<br />
| Competitive|| Competitive || Perfect market || Play the market, Standardize requirements || Take it or leave it, Try to obtain lower costs, Try to differentiate<br />
|-<br />
| Competitive || Command || Sellers’s market || Accept gracefully, Buy jointly, Exchange information with other buyers, Complain, agitate, Encourage competitors || Take it or leave it, Form a cartel, Legitimize, Standardize the product<br />
|-<br />
| Command || Competitive || Buyer’s market || Put out trends; Play the market || Competitive bidding; Try to obtain lower costs or differentiate r<br />
|-<br />
| Cooperative || Cooperative || Domesticated market || Adapt, cooperate, work together || Customize, specialize, differentiate, innovate<br />
|-<br />
| Cooperative || Command || Captive market || Learn from the supplier || Educate the buyer<br />
|-<br />
| Command || Cooperative || Subcontract market || Educate the supplier || Learn from the buyer<br />
|-<br />
|}<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Supply_chainSupply chain2011-08-22T17:37:37Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Цепь_поставок Цепь поставок]'''<br />
<br />
[[File:Supply chain.png|thumb|The supply chain.]] <br />
<br />
Supply chain is a set of several independent companies that are involved in sourcing of materials, manufacturing, distributing and selling the product for ultimate customer. The term supply chain appeared along with the term “[[supply chain management]]”, however supply chains exist whenever they are managed or not. Unlike the definitions of supply chain management, the definitions of supply chain are rather homogeneous:<br />
*A supply chain is a set of firms that pass materials forward <ref>La Londe and Masters (1994) Emerging Logistics Strategies: Blueprints for the Next Century, International Journal of Physical Distribution & Logistics Management</ref>. <br />
*A supply chain is the alignment of firms that bring products or services to market <ref>Stock J., Lambert D. and Ellram L. (1998) Fundamentals of Logistics Management </ref><br />
*A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request <ref>Chopra S. and Meindl P. (2003) Supply Chain Management: Strategy, Planning, and Operations</ref><br />
*A supply chain is a set of three or more entities (organizations or individuals) directly involved in the upstream and downstream flows of products, materials and/or information from a source to a customer<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>.<br />
It is important to note that these definitions of supply chain include the final consumer as part of it. Other authors see supply chain as a network of organizations, which is more closely to the reality:<br />
*A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials into intermediate and finished products, and the distribution of these finished products to customers <ref>Ganeshan R. and Harrison T.P. (1993) An introduction to supply chain management. </ref><br />
* A supply chain is the network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate consumer<ref>Christopher M. (1992) Logistics and Supply Chain Management: Strategies for Reducing Costs and Improve Services. – London: Financial Times; Pitman. – 320 p.</ref>.<br />
It is also important to note that any one organization can be a part of numerous supply chains.<br />
==Types of channel relationships==<br />
The core role in supply chains play the relationships between the actors (buyers and sellers). Supply chain type depends on what kind of relationships are between players. Below there are two classifications of relationship types (or strategies): given by J. Mentzer et al. (2001)<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>. and by N. Campbell (2002)<ref>Campbell N. (2002) An international approach to organizational buying behavior. In: Ford D. (ed.). Understanding Business Marketing and Purchasing. 3rd ed. Thomson Learning: London; 389-401</ref>. <br />
====Types of relationships by J. Mentzer====<br />
[[File:supply chain types.png|thumb|Types of channel relationships]]<br />
According to J. Mentzer and his colleagues, there are three degrees of supply chain complexity: a "direct supply chain" an "extended supply chain" and an "ultimate supply chain" (see figure). <br />
*'''A direct supply chain''' consists of a company, a supplier, and a customer involved in the upstream and/or downstream flows of products, services, finances, and/or information. This might be either very big vertically integrated corporation that doesn’t have important second tier suppliers or small one without resources or need to monitor second tier suppliers. <br />
*'''An extended supply chain''' includes suppliers of the immediate supplier and customers of the immediate customer, all involved in the upstream and/or downstream flows of products, services, finances, and/or information. This is traditional supply chain. <br />
*'''An ultimate supply chain''' includes all the organizations involved in all the upstream and downstream flows of products, services, finances, and information from the ultimate supplier to the ultimate customer.<br />
<br />
====Types of relationships by N. Campbell====<br />
<br />
N. Campbell described three types of relationship strategies: <br />
*'''Competitive''' – independent relationships, price establishes by competitive market forces,<br />
*'''Cooperative''' – interdependent relationships, developing new value,<br />
*'''Command''' – dependent, one party has a dominant position of strength.<br />
[[File:Campbell.png|thumb|Types of relationships strategies]]<br />
Any of this strategies might be implemented by one of the sides: by buyer or by seller, depending on what bargaining power does it have, what are the plans of this player, etc. Some of parameters are listed here: <br />
*Product<br />
**Frequency of purchase<br />
**Switching cost due to physical and human investments<br />
**Product complexity<br />
**Industry characteristics<br />
*Concentration<br />
**Number of alternative partners<br />
**Intensity of competition<br />
**Traditions and norms<br />
*Company characteristics<br />
**Relative size<br />
**Preferred infrastructure style<br />
**Relative familiarity<br />
**Centralization of purchasing<br />
*Individual characteristics<br />
**Relative familiarity<br />
**Preferred interaction style<br />
**Perceived importance of the purchase<br />
**Risk aversion<br />
<br />
<br />
<br />
{| border="1"<br />
!colspan="5"|Relatioship strategies and recommendations <br />
|-<br />
| Buyer's strategy || Seller'strategy || Combination title || Recommendation for buyer || Recommendation for seller<br />
|-<br />
| Competitive|| Competitive || Perfect market || Play the market, Standardize requirements || Take it or leave it, Try to obtain lower costs, Try to differentiate<br />
|-<br />
| Competitive || Command || Sellers’s market || Accept gracefully, Buy jointly, Exchange information with other buyers, Complain, agitate, Encourage competitors || Take it or leave it, Form a cartel, Legitimize, Standardize the product<br />
|-<br />
| Command || Competitive || Buyer’s market || Put out trends; Play the market || Competitive bidding; Try to obtain lower costs or differentiate r<br />
|-<br />
| Cooperative || Cooperative || Domesticated market || Adapt, cooperate, work together || Customize, specialize, differentiate, innovate<br />
|-<br />
| Cooperative || Command || Captive market || Learn from the supplier || Educate the buyer<br />
|-<br />
| Command || Cooperative || Subcontract market || Educate the supplier || Learn from the buyer<br />
|-<br />
|}<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Supply_chainSupply chain2011-08-22T17:36:12Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Цепь_поставок Цепь поставок]'''<br />
<br />
[[File:Supply chain.png|thumb|The supply chain.]] <br />
<br />
Supply chain is a set of several independent companies that are involved in sourcing of materials, manufacturing, distributing and selling the product for ultimate customer. The term supply chain appeared along with the term “[[supply chain management]]”, however supply chains exist whenever they are managed or not. Unlike the definitions of supply chain management, the definitions of supply chain are rather homogeneous:<br />
*A supply chain is a set of firms that pass materials forward <ref>La Londe and Masters (1994) Emerging Logistics Strategies: Blueprints for the Next Century, International Journal of Physical Distribution & Logistics Management</ref>. <br />
*A supply chain is the alignment of firms that bring products or services to market <ref>Stock J., Lambert D. and Ellram L. (1998) Fundamentals of Logistics Management </ref><br />
*A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request <ref>Chopra S. and Meindl P. (2003) Supply Chain Management: Strategy, Planning, and Operations</ref><br />
*A supply chain is a set of three or more entities (organizations or individuals) directly involved in the upstream and downstream flows of products, materials and/or information from a source to a customer<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>.<br />
It is important to note that these definitions of supply chain include the final consumer as part of it. Other authors see supply chain as a network of organizations, which is more closely to the reality:<br />
*A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials into intermediate and finished products, and the distribution of these finished products to customers <ref>Ganeshan R. and Harrison T.P. (1993) An introduction to supply chain management. </ref><br />
* A supply chain is the network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate consumer<ref>Christopher M. (1992) Logistics and Supply Chain Management: Strategies for Reducing Costs and Improve Services. – London: Financial Times; Pitman. – 320 p.</ref>.<br />
It is also important to note that any one organization can be part of numerous supply chains.<br />
==Types of channel relationships==<br />
The core role in supply chains play the relationships between the actors (buyers and sellers). Supply chain type depends on what kind of relationships are between players. Below there are two classifications of relationship types (or strategies): given by J. Mentzer et al. (2001)<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>. and by N. Campbell (2002)<ref>Campbell N. (2002) An international approach to organizational buying behavior. In: Ford D. (ed.). Understanding Business Marketing and Purchasing. 3rd ed. Thomson Learning: London; 389-401</ref>. <br />
====Types of relationships by J. Mentzer====<br />
[[File:supply chain types.png|thumb|Types of channel relationships]]<br />
According to J. Mentzer and his colleagues, there are three degrees of supply chain complexity: a "direct supply chain" an "extended supply chain" and an "ultimate supply chain" (see figure). <br />
*'''A direct supply chain''' consists of a company, a supplier, and a customer involved in the upstream and/or downstream flows of products, services, finances, and/or information. This might be either very big vertically integrated corporation that doesn’t have important second tier suppliers or small one without resources or need to monitor second tier suppliers. <br />
*'''An extended supply chain''' includes suppliers of the immediate supplier and customers of the immediate customer, all involved in the upstream and/or downstream flows of products, services, finances, and/or information. This is traditional supply chain. <br />
*'''An ultimate supply chain''' includes all the organizations involved in all the upstream and downstream flows of products, services, finances, and information from the ultimate supplier to the ultimate customer.<br />
<br />
====Types of relationships by N. Campbell====<br />
<br />
N. Campbell described three types of relationship strategies: <br />
*'''Competitive''' – independent relationships, price establishes by competitive market forces,<br />
*'''Cooperative''' – interdependent relationships, developing new value,<br />
*'''Command''' – dependent, one party has a dominant position of strength.<br />
[[File:Campbell.png|thumb|Types of relationships strategies]]<br />
Any of this strategies might be implemented by one of the sides: by buyer or by seller, depending on what bargaining power does it have, what are the plans of this player, etc. Some of parameters are listed here: <br />
*Product<br />
**Frequency of purchase<br />
**Switching cost due to physical and human investments<br />
**Product complexity<br />
**Industry characteristics<br />
*Concentration<br />
**Number of alternative partners<br />
**Intensity of competition<br />
**Traditions and norms<br />
*Company characteristics<br />
**Relative size<br />
**Preferred infrastructure style<br />
**Relative familiarity<br />
**Centralization of purchasing<br />
*Individual characteristics<br />
**Relative familiarity<br />
**Preferred interaction style<br />
**Perceived importance of the purchase<br />
**Risk aversion<br />
<br />
<br />
<br />
{| border="1"<br />
!colspan="5"|Relatioship strategies and recommendations <br />
|-<br />
| Buyer's strategy || Seller'strategy || Combination title || Recommendation for buyer || Recommendation for seller<br />
|-<br />
| Competitive|| Competitive || Perfect market || Play the market, Standardize requirements || Take it or leave it, Try to obtain lower costs, Try to differentiate<br />
|-<br />
| Competitive || Command || Sellers’s market || Accept gracefully, Buy jointly, Exchange information with other buyers, Complain, agitate, Encourage competitors || Take it or leave it, Form a cartel, Legitimize, Standardize the product<br />
|-<br />
| Command || Competitive || Buyer’s market || Put out trends; Play the market || Competitive bidding; Try to obtain lower costs or differentiate r<br />
|-<br />
| Cooperative || Cooperative || Domesticated market || Adapt, cooperate, work together || Customize, specialize, differentiate, innovate<br />
|-<br />
| Cooperative || Command || Captive market || Learn from the supplier || Educate the buyer<br />
|-<br />
| Command || Cooperative || Subcontract market || Educate the supplier || Learn from the buyer<br />
|-<br />
|}<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Supply_chainSupply chain2011-08-22T17:35:29Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Цепь_поставок Цепь поставок]'''<br />
<br />
[[File:Supply chain.png|thumb|The supply chain.]] <br />
<br />
Supply chain is a set of several independent companies that are involved in sourcing of materials, manufacturing, distributing and selling the product for ultimate customer. The term supply chain appeared along with the term “[[supply chain management]]”, however supply chains exist whenever they are managed or not. Unlike the definitions if supply chain management, the definitions of supply chain are homogeneous enough:<br />
*A supply chain is a set of firms that pass materials forward <ref>La Londe and Masters (1994) Emerging Logistics Strategies: Blueprints for the Next Century, International Journal of Physical Distribution & Logistics Management</ref>. <br />
*A supply chain is the alignment of firms that bring products or services to market <ref>Stock J., Lambert D. and Ellram L. (1998) Fundamentals of Logistics Management </ref><br />
*A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request <ref>Chopra S. and Meindl P. (2003) Supply Chain Management: Strategy, Planning, and Operations</ref><br />
*A supply chain is a set of three or more entities (organizations or individuals) directly involved in the upstream and downstream flows of products, materials and/or information from a source to a customer<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>.<br />
It is important to note that these definitions of supply chain include the final consumer as part of it. Other authors see supply chain as a network of organizations, which is more closely to the reality:<br />
*A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials into intermediate and finished products, and the distribution of these finished products to customers <ref>Ganeshan R. and Harrison T.P. (1993) An introduction to supply chain management. </ref><br />
* A supply chain is the network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate consumer<ref>Christopher M. (1992) Logistics and Supply Chain Management: Strategies for Reducing Costs and Improve Services. – London: Financial Times; Pitman. – 320 p.</ref>.<br />
It is also important to note that any one organization can be part of numerous supply chains.<br />
==Types of channel relationships==<br />
The core role in supply chains play the relationships between the actors (buyers and sellers). Supply chain type depends on what kind of relationships are between players. Below there are two classifications of relationship types (or strategies): given by J. Mentzer et al. (2001)<ref>Mentzer J., DeWitt W., Keebler J., Soonhoong M., Nix N. Smith C., Zacharia Z. (2001) Defining supply chain management Journal of Business Logistics, Vol. 22 Issue 2, p1-25,</ref>. and by N. Campbell (2002)<ref>Campbell N. (2002) An international approach to organizational buying behavior. In: Ford D. (ed.). Understanding Business Marketing and Purchasing. 3rd ed. Thomson Learning: London; 389-401</ref>. <br />
====Types of relationships by J. Mentzer====<br />
[[File:supply chain types.png|thumb|Types of channel relationships]]<br />
According to J. Mentzer and his colleagues, there are three degrees of supply chain complexity: a "direct supply chain" an "extended supply chain" and an "ultimate supply chain" (see figure). <br />
*'''A direct supply chain''' consists of a company, a supplier, and a customer involved in the upstream and/or downstream flows of products, services, finances, and/or information. This might be either very big vertically integrated corporation that doesn’t have important second tier suppliers or small one without resources or need to monitor second tier suppliers. <br />
*'''An extended supply chain''' includes suppliers of the immediate supplier and customers of the immediate customer, all involved in the upstream and/or downstream flows of products, services, finances, and/or information. This is traditional supply chain. <br />
*'''An ultimate supply chain''' includes all the organizations involved in all the upstream and downstream flows of products, services, finances, and information from the ultimate supplier to the ultimate customer.<br />
<br />
====Types of relationships by N. Campbell====<br />
<br />
N. Campbell described three types of relationship strategies: <br />
*'''Competitive''' – independent relationships, price establishes by competitive market forces,<br />
*'''Cooperative''' – interdependent relationships, developing new value,<br />
*'''Command''' – dependent, one party has a dominant position of strength.<br />
[[File:Campbell.png|thumb|Types of relationships strategies]]<br />
Any of this strategies might be implemented by one of the sides: by buyer or by seller, depending on what bargaining power does it have, what are the plans of this player, etc. Some of parameters are listed here: <br />
*Product<br />
**Frequency of purchase<br />
**Switching cost due to physical and human investments<br />
**Product complexity<br />
**Industry characteristics<br />
*Concentration<br />
**Number of alternative partners<br />
**Intensity of competition<br />
**Traditions and norms<br />
*Company characteristics<br />
**Relative size<br />
**Preferred infrastructure style<br />
**Relative familiarity<br />
**Centralization of purchasing<br />
*Individual characteristics<br />
**Relative familiarity<br />
**Preferred interaction style<br />
**Perceived importance of the purchase<br />
**Risk aversion<br />
<br />
<br />
<br />
{| border="1"<br />
!colspan="5"|Relatioship strategies and recommendations <br />
|-<br />
| Buyer's strategy || Seller'strategy || Combination title || Recommendation for buyer || Recommendation for seller<br />
|-<br />
| Competitive|| Competitive || Perfect market || Play the market, Standardize requirements || Take it or leave it, Try to obtain lower costs, Try to differentiate<br />
|-<br />
| Competitive || Command || Sellers’s market || Accept gracefully, Buy jointly, Exchange information with other buyers, Complain, agitate, Encourage competitors || Take it or leave it, Form a cartel, Legitimize, Standardize the product<br />
|-<br />
| Command || Competitive || Buyer’s market || Put out trends; Play the market || Competitive bidding; Try to obtain lower costs or differentiate r<br />
|-<br />
| Cooperative || Cooperative || Domesticated market || Adapt, cooperate, work together || Customize, specialize, differentiate, innovate<br />
|-<br />
| Cooperative || Command || Captive market || Learn from the supplier || Educate the buyer<br />
|-<br />
| Command || Cooperative || Subcontract market || Educate the supplier || Learn from the buyer<br />
|-<br />
|}<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Geographic_postponementGeographic postponement2011-08-22T17:30:17Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Географическая_отсрочка_производства Географическая отсрочка производства]'''<br />
<br />
<br />
Geographic (or time, or logistics) [[postponement]] refers to a situation, where a fully stocked anticipatory inventory is maintained at one or a few strategic locations. When customer orders are received, the orders are delivered directly to the customer, for example, from strategic warehousing locations <ref> Bowersox, D.J., Closs, D.J., (1996) Logistical Management: The Integrated Supply Chain Process. McGraw-Hill, Singapore.</ref>. For more information, see [[Risk pooling]]. <br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Geographic_postponementGeographic postponement2011-08-22T17:20:53Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Географическая_отсрочка_производства Географическая отсрочка производства]'''<br />
<br />
<br />
Geographic (or space, or logistics) [[postponement]] refers to a situation, where a fully stocked anticipatory inventory is maintained at one or a few strategic locations. When customer orders are received, the orders are delivered directly to the customer, for example, from strategic warehousing locations <ref> Bowersox, D.J., Closs, D.J., (1996) Logistical Management: The Integrated Supply Chain Process. McGraw-Hill, Singapore.</ref>. For more information, see [[Risk pooling]]. <br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/EDIEDI2011-08-22T16:55:46Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Электронный_обмен_данными Электронный обмен данными]'''<br />
<br />
Electronic Data Interchange (EDI) is the electronic transfer of information between two trading partner’s systems using a set of transactions that have been adopted as a national or international standard for the particular business function. EDI is much more, than just e-mail. EDI provides a faster, more accurate, less costly method of communication. It reduces the amount of information that should be processed manually, thus it illuminates errors made because of the human factor (tiredness, inattentiveness, etc.). For instance, organizations might replace bills with appropriate EDI messages. Purchasing managers that usually do routine operations are substituted by EDI in automated relationships. EDI has become a requirement for doing business; it is particularly valuable in enhancing managerial information and control<ref> Emmelhainz, Margaret A (1990), Electronic Data Interchange: A Total Management Guide. New York Van Nostrand Reinhold.</ref>.<br />
<br />
A technical definition of EDI is: "the computer-to-computer interchange of strictly formatted messages that represent documents other than monetary instruments. EDI implies a sequence of messages between two parties, either of whom may serve as originator or recipient. The formatted data representing the documents may be transmitted from originator to recipient via telecommunications or physically transported on electronic storage media"<ref>National Institute of Standards and Technology (1996) </ref>. <br />
<br />
Businesses usually have various incentives to implement EDI applications; these incentives might be grouped into three categories<ref>Peffers, Ken, Brian L. Dos Santos, and Peter F. Thurner (1998). "Motivation, implementation, and impact of electronic data interchange among US and German firms." Information Services & Use 18.3.</ref>:<br />
* '''Cost reduction''' (reduced data entry, paper use and handling, reduced inventory carrying costs);<br />
* '''Inter-organizational process redesign''' (technological redesign of business processes, particularly processes that involve several organizations);<br />
* '''Strategic customer/supplier relationships''' (improves the buyer-supplier relationship: the parties become to better understand trading systems of each other).<br />
<br />
Besides, the initiative to implement EDI may internal (from within the company) or external (from other entity: usually customers or suppliers) Frequently, large customers have the bargaining power to demand that suppliers adopt EDI. Firms may have little choice about whether to implement EDI or not if a major customer decides to do business only with those who install EDI<ref>Peffers, Ken, Brian L. Dos Santos, and Peter F. Thurner (1998). "Motivation, implementation, and impact of electronic data interchange among US and German firms." Information Services & Use 18.3.</ref>.<br />
<br />
In logistics, EDI provides vast opportunities for a firm to develop differentiation of their service from that of its competitors, simply by building an integrated EDI network between its operation and that of carriers used to distribute its products; this network allows the companies to provide a superior service and to maintain control over raw materials. EDI helps to reduce the order cycle through automatic order placement, automatic invoicing and billing; besides, it is an essential part of just-in-time (JIT) delivery system. Via EDI it becomes possible to coordinate production schedules and to control inventory. The coordination of information flows between all affected departments allows for logistical trade-offs and enables the firm to act, rather than react, when critical situations arise<ref> Loar, Theodore T (1998), "Electronic Data Interchange: Integration of Shipper/Motor Carrier Systems." Transportation Journal 27.4</ref>. EDI might be used in creating new ways of doing business by means of new electronic markets creation. For example, incorporation of hotel rooms booking or car rent services into the airline reservation system<ref>Baker, Richard H. (1991), EDI: What Managers Need to Know About the Revolution in Business Communications. Blue Ridge Summit, PA: TAB Professional and Reference Books.</ref>.<br />
<br />
==References==<br />
<references/><br />
<br />
[[Category:Supply Chain Technology]]</div>Storchhttp://scm.gsom.spbu.ru/Customer_relationship_managementCustomer relationship management2011-08-22T16:22:58Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_взаимоотношениями_с_клиентами Управление взаимоотношениями с клиентами]'''<br />
<br />
Customer Relationship Management (CRM) is a management philosophy according to which a company's goals can be best achieved through identification and satisfaction of the customers’ stated and unstated needs and wants <ref>http://www.businessdictionary.com/definition/customer-relationship-management-CRM.html</ref>. <br />
While managing relationships it is important to remember about basic relationship types<ref>Webster and Frederick (1992)</ref>:<br />
*Transactions <br />
*Repeated transactions<br />
*Long-term relationships<br />
*Buyer-seller partnerships<br />
*Strategic alliances<br />
*Network organizations<br />
*Vertical integration <br />
Today the abbreviation CRM is also used for enterprise-level software solutions that help to collect and maintain valuable data about customers such as personal info, history of purchases and so on. These data help to understand preferences of the customer and predict future demand. This software makes communications with customers more comfortable. All these activities help to create customer loyalty. However CRM is not just a technological solution<ref>Nykamp M. (2001), The Customer Differential: The Complete Guide to Implementing CRM, AMACOM, 1601 Broadway, New York.</ref>. While the Internet and other advanced technologies enabled companies to obtain vast amounts of customer data, the very same technologies also gave more power to consumers, who now demand much higher levels of service, a greater choice in product features and lower prices. Businesses need to know what data should be collected first and foremost, what is the best application of this information, and how to provide personal “mass customization” to individual customers. <br />
CRM and [[Supply Chain Management]] (SCM) have different functions. On the one hand CRM help sales and marketing people to analyze customer behavior and brings value for the organization by using technological and human resources. On the other hand SCM offers to the organization several advantages in coordination of their raw material acquisition, production and logistic processes<ref>Bibiano L.H., Alberto C. (2007), “Comparative analysis of CRM and SCM systems implementation approaches,” Proceedings of Europe and Mediterranean Conference on Information Systems (EMCIS2007), Polytechnic University of Valencia</ref>. Therefore, these tools turn to work in opposite directions and are based on different sets of data. However, it is obvious that they are very interdependent, because when CRM helps to understand customers’ needs and predict demand, SCM must use this information in purchasing of raw materials in time and delivering final product to the customer as soon as possible.<br />
<br />
Customer Relationship Management is associated with various software and conceptual solutions: Efficient Consumer Response (ECR), [[Electronic data interchange]] (EDI), Quick response (QR), [[Collaborative planning forecasting and replenishment]] (CPFR), etc. <br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Customer_relationship_managementCustomer relationship management2011-08-22T16:22:26Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_взаимоотношениями_с_клиентами Управление взаимоотношениями с клиентами]'''<br />
<br />
Customer Relationship Management (CRM) is a management philosophy according to which a company's goals can be best achieved through identification and satisfaction of the customers’ stated and unstated needs and wants <ref>http://www.businessdictionary.com/definition/customer-relationship-management-CRM.html</ref>. <br />
While managing relationships it is important to remember about basic relationship types<ref>Webster and Frederick (1992)</ref>:<br />
*Transactions <br />
*Repeated transactions<br />
*Long-term relationships<br />
*Buyer-seller partnerships<br />
*Strategic alliances<br />
*Network organizations<br />
*Vertical integration <br />
Today the abbreviation CRM is also used for enterprise-level software solutions that help to collect and maintain valuable data about customers such as personal info, history of purchases and so on. These data help to understand preferences of the customer and predict future demand. This software makes communications with customers more comfortable. All these activities help to create customer loyalty. However CRM is not just a technological solution<ref>Nykamp M. (2001), The Customer Differential: The Complete Guide to Implementing CRM, AMACOM, 1601 Broadway, New York.</ref>. While the Internet and other advanced technologies enabled companies to obtain vast amounts of customer data, the very same technologies also gave more power to consumers, who now demand much higher levels of service, a greater choice in product features and lower prices. Businesses need to know what data should be collected first and foremost, what is the best application of this information, and how to provide personal “mass customization” to individual customers. <br />
CRM and [[Supply Chain Management]] (SCM) have different functions. On the one hand CRM help sales and marketing people to analyze customer behavior and brings value for the organization by using technological and human resources. On the other hand SCM offers to the organization several advantages in coordination of their raw material acquisition, production and logistic processes<ref>Bibiano L.H., Alberto C. (2007), “Comparative analysis of CRM and SCM systems implementation approaches,” Proceedings of Europe and Mediterranean Conference on Information Systems (EMCIS2007), Polytechnic University of Valencia</ref>. Therefore, these tools turn to work in opposite directions and are based on different sets of data. However, it is obvious that they are very interdependent, because when CRM helps to understand customers’ needs and predict demand, SCM must use this information in purchasing of raw materials in time and delivering final product to the customer as soon as possible.<br />
<br />
Customer Relationship Management is associated with various software and conceptual solutions: Efficient Consumer Response (ECR), [[EDI Electronic Data Interchange]] (EDI), Quick response (QR), [[Collaborative planning forecasting and replenishment]] (CPFR), etc. <br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Customer_relationship_managementCustomer relationship management2011-08-22T16:19:57Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_взаимоотношениями_с_клиентами Управление взаимоотношениями с клиентами]'''<br />
<br />
Customer Relationship Management (CRM) is a management philosophy according to which a company's goals can be best achieved through identification and satisfaction of the customers’ stated and unstated needs and wants <ref>http://www.businessdictionary.com/definition/customer-relationship-management-CRM.html</ref>. <br />
While managing relationships it is important to remember about basic relationship types<ref>Webster and Frederick (1992)</ref>:<br />
*Transactions <br />
*Repeated transactions<br />
*Long-term relationships<br />
*Buyer-seller partnerships<br />
*Strategic alliances<br />
*Network organizations<br />
*Vertical integration <br />
Today the abbreviation CRM is also used for enterprise-level software solutions that help to collect and maintain valuable data about customers such as personal info, history of purchases and so on. These data help to understand preferences of the customer and predict future demand. This software makes communications with customers more comfortable. All these activities help to create customer loyalty. However CRM is not just a technological solution<ref>Nykamp M. (2001), The Customer Differential: The Complete Guide to Implementing CRM, AMACOM, 1601 Broadway, New York.</ref>. While the Internet and other advanced technologies enabled companies to obtain vast amounts of customer data, the very same technologies also gave more power to consumers, who now demand much higher levels of service, a greater choice in product features and lower prices. Businesses need to know what data should be collected first and foremost, what is the best application of this information, and how to provide personal “mass customization” to individual customers. <br />
CRM and [[Supply Chain Management]] (SCM) have different functions. On the one hand CRM help sales and marketing people to analyze customer behavior and brings value for the organization by using technological and human resources. On the other hand SCM offers to the organization several advantages in coordination of their raw material acquisition, production and logistic processes<ref>Bibiano L.H., Alberto C. (2007), “Comparative analysis of CRM and SCM systems implementation approaches,” Proceedings of Europe and Mediterranean Conference on Information Systems (EMCIS2007), Polytechnic University of Valencia</ref>. Therefore, these tools turn to work in opposite directions and are based on different sets of data. However, it is obvious that they are very interdependent, because when CRM helps to understand customers’ needs and predict demand, SCM must use this information in purchasing of raw materials in time and delivering final product to the customer as soon as possible.<br />
<br />
Customer Relationship Management is associated with various software and conceptual solutions: Efficient Consumer Response (ECR), [[Electronic Data Interchange]] (EDI), Quick response (QR), [[Collaborative Forecasting, Planning and Replenishment]] (CPFR), etc. <br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Customer_relationship_managementCustomer relationship management2011-08-22T16:01:58Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_взаимоотношениями_с_клиентами Управление взаимоотношениями с клиентами]'''<br />
<br />
Customer Relationship Management (CRM) is a management philosophy according to which a company's goals can be best achieved through identification and satisfaction of the customers’ stated and unstated needs and wants <ref>http://www.businessdictionary.com/definition/customer-relationship-management-CRM.html</ref>. <br />
While managing relationships it is important to remember about basic relationship types<ref>Webster and Frederick (1992)</ref>:<br />
*Transactions <br />
*Repeated transactions<br />
*Long-term relationships<br />
*Buyer-seller partnerships<br />
*Strategic alliances<br />
*Network organizations<br />
*Vertical integration <br />
Today the abbreviation CRM is also used for enterprise-level software solutions that help to collect and maintain valuable data about customers such as personal info, history of purchases and so on. These data help to understand preferences of the customer and predict future demand. This software makes communications with customers more comfortable. All these activities help to create customer loyalty. However CRM is not just a technological solution<ref>Nykamp M. (2001), The Customer Differential: The Complete Guide to Implementing CRM, AMACOM, 1601 Broadway, New York.</ref>. While the Internet and other advances in technologies enabled companies to obtain vast amounts of customer data, the very same technologies also gave more power to consumers, who now demand much higher levels of service, a greater choice in product features and lower prices. Businesses need to know what data should be collected first and foremost and what is the best application of this information while at the same time providing personal “mass customization” to individual customers. <br />
CRM and [[Supply Chain Management]] (SCM) have different functions. On the one hand CRM help sales and marketing people to analyze customer behavior and its value for the organization by using technology and human resources. On the other hand SCM offers to organization several advantages to coordinate their raw material acquisition, production and logistic processes<ref>Bibiano L.H., Alberto C. (2007), “Comparative analysis of CRM and SCM systems implementation approaches,” Proceedings of Europe and Mediterranean Conference on Information Systems (EMCIS2007), Polytechnic University of Valencia</ref>. It means that these two tools tend to sit at opposite ends of the enterprise and deal with different sets of data. But also it is obvious that these different approaches are very interdependent, because when CRM helps to understand customers’ needs and predict demand, SCM must use this information make purchasing of raw materials in time and delivering final product to the customer as fast as possible.<br />
<br />
Customer Relationship Management is accompanied by various software and conceptual decisions: Efficient Consumer Response (ECR), Electronic Data Interchange (EDI), Quick response (QR), Collaborative Forecasting, Planning and Replenishment (CPFR), etc. <br />
<br />
<br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/File:Financial-logistics-rus.pngFile:Financial-logistics-rus.png2011-08-22T15:13:57Z<p>Storch: </p>
<hr />
<div></div>Storchhttp://scm.gsom.spbu.ru/Supply_chain_managementSupply chain management2011-08-22T00:47:20Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_цепями_поставок Управление цепями поставок]'''<br />
<br />
<br />
Supply chain management (SCM) is a successful business practice, an effective strategy and a popular concept. According to many surveys, it is important for a growing number of companies all over the world. SCM concept is a mix of various concepts<ref> Гиюниперо Л. и др., 2011. Десять лет исследований в сфере управления цепями поставок: прошлое, настоящее и выводы для будущего. Российский журнал менеджмента 9 (2)</ref>. SCM combines the goals of logistics (minimizing of total costs in supply chain) and of operations management (efficient inventory and production management), of marketing (value creation and customer satisfaction) and of relationship marketing (cooperating with partners in a [[supply chain]]), as well as of other disciplines. Hence, it is obvious that explanation of approaches to management of a network of relationships and enjoying total costs minimization with a given level of customer satisfaction a multidisciplinary approach is required. <br />
The practice of managing supply chains (followed by a theory of SCM) appeared as an answer to new economic challenges in late 1970s – early 1980s, when macroeconomic environment of a world economy stagnation after the oil crisis required efforts on developing new managerial decisions and concepts<ref> Черенков В. И. (2004) Эволюция маркетинговой теории и трансформация доминирующей парадигмы маркетинга. Вестник Санкт-Петербургского Университета. Сер. Менеджмент 2: 3-32</ref>. One of the survival conditions for the companies at that time was a decrease in logistics costs. At the same time the managers found out pretty soon that the reason of dramatically increased logistics cost was not only transportation costs, but costs of safety stocks, obsolete inventories, cost of lost revenues because of out-of-stock situations, etc. The problems listed above are the problems of the [[bullwhip effect]] in [[supply chain]]. The bullwhip effect means that partners in supply chain do not have the information of real sales and have to creae safety stocks of goods and materials. The core competence paradigm<ref> Prahalad C.K. and Hamel, G (1990) The core competence of the corporation, Harvard Business Review, 68 (3): 79-91.</ref>, that was introduced and dominated in 1990s made this problem even worse, because companies started to concentrate on their own core competences and outsource the rest of the functions. It increased the number of actors in supply chain and made information flow more difficult. Obvious and logical decision was to organize the '''coordinated''' flow of materials and finished goods by exchanging reliable and relevant information<ref> Oliver K. and Webber M. (1982) Supply chain management: Logistics catches up with strategy. In: Christopher M. (ed.) Logistics, The Strategic Issues. Champan and Hall: London; 63–75.</ref>. This concept was named a supply chain management and later developed towards more complex coordination systems and integration of core business processes<ref> Croom S. R., Romano P. and Giannakis M. (2000) Supply chain management: an analytical framework for critical literature review. European Journal of Purchasing and Supply Management 7: 29–37</ref>. As a result supply chain differs from vertically-integrated corporation of the beginning of XX century by the fact, that supply chain consists of separate, formally independent (in reality tightly interdependent), concentrated on own core competences organizations, that have common goal to minimize costs in supply chain and maximize value for the ultimate customer. <br />
<br />
In literature different approaches of supply chain management might be found. Some of them contradict each other<ref> Burgess K., Singh P. and Koroglu, R. (2006) Supply Chain Management: A Structured Literature Review and Implications for Future Research. International Journal of Operations and Production Management, 26, (7), 703-729.</ref>. The definition basically depends on position of the author: logistics, operations management, marketing, etc. For instance, logistics and operation management specialists concentrate on optimization of business processes<ref> Lamming R., Johnsen T., Zheng J. and Harland C. (2000). An initial classification of supply networks. International Journal of Operations & Production Management, 20, (6), 675-691.</ref>, on the other hand, marketing specialists – on service level and value for the customer<ref> Jüttner U., Christopher M. and Baker S. (2007) Demand chain management — integrating marketing and supply chain management / U. Jüttner, // Industrial Marketing Management. – Vol. 36, № 5. p. 377-392</ref>,<ref>Кирюков С. И., Кротов К. В. (2007) Развитие концепции управления цепями поставок: маркетинговый подход. Вестник С.-Петербургского ун-та. Сер. Менеджмент (4): 97–111.</ref>. <br />
<br />
Attempts to make a unified, single definitions are still not very successful. For instance, Stock and Boyer tried to make a synthetic definition on the base of 173 given definitions: “The management of a network of relationships within a firm and between interdependent organizations and business units consisting of material suppliers, purchasing, production facilities, logistics, marketing, and related systems that facilitate the forward and reverse flow of materials, services, finances and information from the original producer to final customer with the benefits of adding value, maximizing profitability through efficiencies, and achieving customer satisfaction”<ref> Stock R., Boyer S., 2009 Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management 39 (8): 690-711</ref>. However, this synthetic definition has its own disadvantages: it is not focused and too “heavy”.<br />
<br />
Some other SCM definitions: <br />
* '''Council of Supply Chain Management Professionals (CSCMP):''' SCM is encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all Logistics Management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third party service providers, and customers. In essence, Supply Chain Management integrates supply and demand management within and across companies<ref>Council of Supply Chain Management Professionals (CSCMP) - www.cscmp.org</ref><br />
*'''Mentzer et al. (2001):''' SCM is the systematic, strategic coordination of the traditional business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole<ref>Mentzer J.T., DeWitt W., Keebler J.S., Min S., Nix N.W., Smith C.D. and Zacharia Z.G. (2001)<br />
Defining supply chain management, Journal of Business Logistics, Vol. 22 No. 2, pp. 1-25. </ref>.<br />
*'''Larson and Rogers (1998):''' SCM is the coordination of activities, within and between vertically linked firms, for the purpose of serving end customers at a profit<ref>Larson P. and Rogers D. (1998) Supply chain management: definition growth and approaches, Journal of Marketing Theory and Practice, Vol. 6 No. 3, pp. 1-5</ref>.<br />
<br />
==Supply Chain Management Frameworks== <br />
<br />
SCM frameworks or models are reference points for practitioners and researcher. Below there are two basic frameworks: SCOR and Metzer model that are most popular in specialized literature. <br />
<br />
====Supply Chain Operations Reference (SCOR)====<br />
[[File:Scm SCOR.jpg|thumb|The Supply Chain Operations Reference (SCOR) model ]] <br />
<br />
The Supply Chain Operations Reference (SCOR) model, developed by the Supply Chain Council<br />
(SCC) and AMR Research in 1996 is one of the most popular models. According to Supply Chain Council, this model provides a unique framework that links business processes, metrics, best practices<br />
and technology features into a unified structure to support communication among supply chain partners<br />
and to improve the effectiveness of supply chain management and related supply chain improvement<br />
activities<ref>( Supply Chain Council, 2009)</ref>. SCOR is used to identify, measure, reorganize and improve supply chain processes through a cyclical process that includes:<br />
*Capturing the configuration of a supply chain<br />
*Measuring the performance of the supply chain and comparing against internal and external<br />
industry goals<br />
*Re-aligning supply chain processes and best practices to fulfill unachieved or changing business<br />
objectives<br />
The SCOR model five processes: plan, source, make, deliver and return. Each process is<br />
implemented through four individual levels. The first level defines the scope and content of the model itself, as well as specifying basis for competition performance targets. At level two, companies implement their operations strategies dependent upon the configurations they choose for their supply chains. Level three defines inputs, outputs, and flows of each transactional element, and finally, level four defines the implementation of specific supply chain management practices<ref> Lockamy III, A. and McCormack, K. (2004). Linking SCOR planning practices to supply chain performance, an exploratory study. International Journal of Operations & Business Management, 24, (12), 1192-1218.</ref> The source, make, and deliver processes of the SCOR model create a continuous chain of activity<br />
throughout a company’s internal operations and, potentially, across the whole inter-organizational supply<br />
chain.<br />
<br />
====The Mentzer Model====<br />
[[File:SCM mentzer.png|thumb|The Mentzer model]]<br />
<br />
Mentzer and his colleagues defined supply chain management in this analysis as “the systematic, strategic coordination of the traditional business functions and tactics across these business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long term performance of the individual companies and the supply chain as a whole.” <br />
<br />
According to this definition, SCM includes multiple firms (supply chain actors) and multiple business activities. The definition is accompanied with the model (see figure). The supply chain looks like a pipeline that includes supply chain flows (services, products, information, materials, money, etc.), inter-functional coordination of business functions (marketing, sales, research and development, forecasting, production, logistics, etc.), which based on trust, commitment, risk and dependence. Mentzer model assumes, that at the end of supply chain there should be two important outcomes: greater customer satisfaction at less costs due to better organization of all flows. These two outcomes form competitive advantage on other supply chains (not individual companies).<br />
<br />
==References==<br />
<references /><br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Supply_chain_managementSupply chain management2011-08-22T00:39:06Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Управление_цепями_поставок Управление цепями поставок]'''<br />
<br />
<br />
Supply chain management (SCM) is a successful business practice, an effective strategy and a popular concept. According to many surveys, it is important for a growing number of companies all over the world. SCM concept is a mix of various concepts<ref> Гиюниперо Л. и др., 2011. Десять лет исследований в сфере управления цепями поставок: прошлое, настоящее и выводы для будущего. Российский журнал менеджмента 9 (2)</ref>. SCM combines the goals of logistics (minimizing of total costs in supply chain) and of operations management (efficient inventory and production management), of marketing (value creation and customer satisfaction) and of relationship marketing (cooperating with partners in a [[supply chain]]), as well as of other disciplines. Hence, it is obvious that explanation of approaches to management of a network of relationships and enjoying total costs minimization with a given level of customer satisfaction a multidisciplinary approach is required. <br />
The practice of managing supply chains (followed by theory of SCM) appeared as an answer to new economic challenges in late 1970s – early 1980s, when the macroeconomic characteristics of stagnating after the oil crisis world economy required efforts on developing new managerial decisions and concepts<ref> Черенков В. И. (2004) Эволюция маркетинговой теории и трансформация доминирующей парадигмы маркетинга. Вестник Санкт-Петербургского Университета. Сер. Менеджмент 2: 3-32</ref>. One of the survival conditions for the companies at that time was a decrease of logistics costs. At the same time the managers found out pretty soon that the reason of dramatically increased logistics cost was not only transportation costs, but costs of safety stocks, obsolete inventories, cost of lost revenues because of absence of required goods or materials, etc. The problems listed above are the problems of the [[bullwhip effect]] in [[supply chain]]. The bullwhip effect problem is that partners in supply chain do not have the information of real sales and orders of goods and materials up and down the supply chain. The core competence paradigm<ref> Prahalad C.K. and Hamel, G (1990) The core competence of the corporation, Harvard Business Review, 68 (3): 79-91.</ref>, that was introduced and dominated in 1990s made this problem even worse, because companies started to concentrate on their own core competences and outsource the rest of the functions. It increased the number of actors in supply chain and made information flow more difficult. Obvious and logical decision was to organize the '''coordinated''' flow of materials and finished goods by exchanging reliable and relevant information<ref> Oliver K. and Webber M. (1982) Supply chain management: Logistics catches up with strategy. In: Christopher M. (ed.) Logistics, The Strategic Issues. Champan and Hall: London; 63–75.</ref>. This concept was named a supply chain management and later developed towards more complex coordination systems and integration of core business processes<ref> Croom S. R., Romano P. and Giannakis M. (2000) Supply chain management: an analytical framework for critical literature review. European Journal of Purchasing and Supply Management 7: 29–37</ref>. As a result supply chain differs from vertically-integrated corporation of the beginning of XX century by the fact, that supply chain consists of separate, formally independent (in reality tightly interdependent), concentrated on own core competences organizations, that have common goal to minimize costs in supply chain and maximize value for the ultimate customer. <br />
<br />
In literature different approaches of supply chain management might be found. Some of them contradict each other<ref> Burgess K., Singh P. and Koroglu, R. (2006) Supply Chain Management: A Structured Literature Review and Implications for Future Research. International Journal of Operations and Production Management, 26, (7), 703-729.</ref>. The definition basically depends on position of the author: logistics, operations management, marketing, etc. For instance, logistics and operation management specialists concentrate on optimization of business processes<ref> Lamming R., Johnsen T., Zheng J. and Harland C. (2000). An initial classification of supply networks. International Journal of Operations & Production Management, 20, (6), 675-691.</ref>, on the other hand, marketing specialists – on service level and value for the customer<ref> Jüttner U., Christopher M. and Baker S. (2007) Demand chain management — integrating marketing and supply chain management / U. Jüttner, // Industrial Marketing Management. – Vol. 36, № 5. p. 377-392</ref>,<ref>Кирюков С. И., Кротов К. В. (2007) Развитие концепции управления цепями поставок: маркетинговый подход. Вестник С.-Петербургского ун-та. Сер. Менеджмент (4): 97–111.</ref>. <br />
<br />
Attempts to make a unified, single definitions are still not very successful. For instance, Stock and Boyer tried to make a synthetic definition on the base of 173 given definitions: “The management of a network of relationships within a firm and between interdependent organizations and business units consisting of material suppliers, purchasing, production facilities, logistics, marketing, and related systems that facilitate the forward and reverse flow of materials, services, finances and information from the original producer to final customer with the benefits of adding value, maximizing profitability through efficiencies, and achieving customer satisfaction”<ref> Stock R., Boyer S., 2009 Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management 39 (8): 690-711</ref>. However, this synthetic definition has its own disadvantages: it is not focused and too “heavy”.<br />
<br />
Some other SCM definitions: <br />
* '''Council of Supply Chain Management Professionals (CSCMP):''' SCM is encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all Logistics Management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third party service providers, and customers. In essence, Supply Chain Management integrates supply and demand management within and across companies<ref>Council of Supply Chain Management Professionals (CSCMP) - www.cscmp.org</ref><br />
*'''Mentzer et al. (2001):''' SCM is the systematic, strategic coordination of the traditional business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole<ref>Mentzer J.T., DeWitt W., Keebler J.S., Min S., Nix N.W., Smith C.D. and Zacharia Z.G. (2001)<br />
Defining supply chain management, Journal of Business Logistics, Vol. 22 No. 2, pp. 1-25. </ref>.<br />
*'''Larson and Rogers (1998):''' SCM is the coordination of activities, within and between vertically linked firms, for the purpose of serving end customers at a profit<ref>Larson P. and Rogers D. (1998) Supply chain management: definition growth and approaches, Journal of Marketing Theory and Practice, Vol. 6 No. 3, pp. 1-5</ref>.<br />
<br />
==Supply Chain Management Frameworks== <br />
<br />
SCM frameworks or models are reference points for practitioners and researcher. Below there are two basic frameworks: SCOR and Metzer model that are most popular in specialized literature. <br />
<br />
====Supply Chain Operations Reference (SCOR)====<br />
[[File:Scm SCOR.jpg|thumb|The Supply Chain Operations Reference (SCOR) model ]] <br />
<br />
The Supply Chain Operations Reference (SCOR) model, developed by the Supply Chain Council<br />
(SCC) and AMR Research in 1996 is one of the most popular models. According to Supply Chain Council, this model provides a unique framework that links business processes, metrics, best practices<br />
and technology features into a unified structure to support communication among supply chain partners<br />
and to improve the effectiveness of supply chain management and related supply chain improvement<br />
activities<ref>( Supply Chain Council, 2009)</ref>. SCOR is used to identify, measure, reorganize and improve supply chain processes through a cyclical process that includes:<br />
*Capturing the configuration of a supply chain<br />
*Measuring the performance of the supply chain and comparing against internal and external<br />
industry goals<br />
*Re-aligning supply chain processes and best practices to fulfill unachieved or changing business<br />
objectives<br />
The SCOR model five processes: plan, source, make, deliver and return. Each process is<br />
implemented through four individual levels. The first level defines the scope and content of the model itself, as well as specifying basis for competition performance targets. At level two, companies implement their operations strategies dependent upon the configurations they choose for their supply chains. Level three defines inputs, outputs, and flows of each transactional element, and finally, level four defines the implementation of specific supply chain management practices<ref> Lockamy III, A. and McCormack, K. (2004). Linking SCOR planning practices to supply chain performance, an exploratory study. International Journal of Operations & Business Management, 24, (12), 1192-1218.</ref> The source, make, and deliver processes of the SCOR model create a continuous chain of activity<br />
throughout a company’s internal operations and, potentially, across the whole inter-organizational supply<br />
chain.<br />
<br />
====The Mentzer Model====<br />
[[File:SCM mentzer.png|thumb|The Mentzer model]]<br />
<br />
Mentzer and his colleagues defined supply chain management in this analysis as “the systematic, strategic coordination of the traditional business functions and tactics across these business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long term performance of the individual companies and the supply chain as a whole.” <br />
<br />
According to this definition, SCM includes multiple firms (supply chain actors) and multiple business activities. The definition is accompanied with the model (see figure). The supply chain looks like a pipeline that includes supply chain flows (services, products, information, materials, money, etc.), inter-functional coordination of business functions (marketing, sales, research and development, forecasting, production, logistics, etc.), which based on trust, commitment, risk and dependence. Mentzer model assumes, that at the end of supply chain there should be two important outcomes: greater customer satisfaction at less costs due to better organization of all flows. These two outcomes form competitive advantage on other supply chains (not individual companies).<br />
<br />
==References==<br />
<references /><br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-22T00:34:52Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
The main processes shown in the model have four stages that are performed in circle. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies significant events affecting supply and demand during the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is divided into Sales Forecasting aimed at predicting consumer demand in a point of sale, and Order Planning/Forecasting aimed at predicting future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and the seller collaborate on a joint product offer that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, a longer lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps to reduce forecasting uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” forecasting errors or a trading partner’s inability to provide a product available in a timely manner?<br />
**With CPFR, the product can be made-to-order instead of made-to-store on the basis of forecasting. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment in CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-22T00:33:24Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
The main processes shown in the model have four stages that are performed in circle. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is divided into Sales Forecasting aimed at predicting consumer demand in a point of sale, and Order Planning/Forecasting aimed at predicting future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and the seller collaborate on a joint product offer that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, a longer lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps to reduce forecasting uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” forecasting errors or a trading partner’s inability to provide a product available in a timely manner?<br />
**With CPFR, the product can be made-to-order instead of made-to-store on the basis of forecasting. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment in CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-22T00:32:46Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
The main processes shown in the model have four stages that are performed in circle. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is divided into Sales Forecasting aimed at predicting consumer demand in a point of sale, and Order Planning/Forecasting aimed at predicting future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and the seller collaborate on a joint product offer that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, a longer lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps reduce forecast uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” forecasting errors or a trading partner’s inability to provide a product available in a timely manner?<br />
**With CPFR, the product can be made-to-order instead of made-to-store on the basis of forecasting. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment in CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-22T00:20:01Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
The main processes shown in the model have four stages that are performed in circle. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is divided into Sales Forecasting aimed at predicting consumer demand in a point of sale, and Order Planning/Forecasting aimed at predicting future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and seller collaborate on a mutual product scheme that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, greater lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps reduce forecast uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” for forecasting errors or a trading partner’s inability to have the product available in a timely manner?<br />
**With CPFR, product can be produced to actual order instead of storing inventory based on forecast. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment from CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail, offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-22T00:09:33Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
The main processes shown in the model have four stages that are performed in circle. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is broken into Sales Forecasting, which projects consumer demand at the point of sale, and Order Planning/Forecasting, which determines future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and seller collaborate on a mutual product scheme that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, greater lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps reduce forecast uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” for forecasting errors or a trading partner’s inability to have the product available in a timely manner?<br />
**With CPFR, product can be produced to actual order instead of storing inventory based on forecast. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment from CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail, offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-22T00:09:23Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
<br />
The main processes shown in the model have four stages that are performed in circle. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is broken into Sales Forecasting, which projects consumer demand at the point of sale, and Order Planning/Forecasting, which determines future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and seller collaborate on a mutual product scheme that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, greater lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps reduce forecast uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” for forecasting errors or a trading partner’s inability to have the product available in a timely manner?<br />
**With CPFR, product can be produced to actual order instead of storing inventory based on forecast. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment from CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail, offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-21T23:54:06Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999):<br />
# Develop Front End Agreement<br />
# Create the Joint Business Plan<br />
# Create the Sales Forecast<br />
# Identify Exceptions for Sales Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Create Order Forecast<br />
# Identify Exceptions for Order Forecast<br />
# Resolve/Collaborate on Exception Items<br />
# Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
<br />
The main processes shown in the model go in a circular pattern and have four stages. This is displayed on the figure. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is broken into Sales Forecasting, which projects consumer demand at the point of sale, and Order Planning/Forecasting, which determines future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and seller collaborate on a mutual product scheme that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, greater lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps reduce forecast uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” for forecasting errors or a trading partner’s inability to have the product available in a timely manner?<br />
**With CPFR, product can be produced to actual order instead of storing inventory based on forecast. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment from CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail, offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Collaborative_planning_forecasting_and_replenishmentCollaborative planning forecasting and replenishment2011-08-21T23:49:12Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Совместное_планирование,_прогнозирование_и_пополнение_запасов Совместное планирование, прогнозирование и пополнение запасов ]'''<br />
<br />
Collaborative Planning, Forecasting and Replenishment (CPFR) is a concept and a business practice that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through '''joint visibility and replenishment''' of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. <br />
CPFR is a strategy for improving supply chain efficiency and effectiveness by making demand transparency drive the execution of the supply chain participants to maximize value for the end-customer. Fundamentally, the aim of CPFR is to convert the supply chain from a disjointed, ineffective and inefficient “push” system to a '''coordinated “pull” system based upon end customer demand'''. Trading partners move to selling '''through''' their customer firms (to their end-customers) rather than '''to''' their customer firms. <br />
CPFR aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners<ref> VICS (Voluntary Interindustry Commerce Standards), 1999, CPFR Technical Specification, http://www.vics.org/docs/guidelines/cpfr_roadmap_case_studies/13_5_CPFR_specifications.pdf</ref>.<br />
<br />
==CPFR Model==<br />
[[File:CPFR.png|thumb|The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes]]<br />
[[File:CPFR2.png|thumb|The CPFR reference model]]<br />
<br />
CPFR Model was originally presented by VICS in their VICS CPFR Guidelines in 1998 as a 9 step process (VICS 1999). The 9 steps are:<br />
1. Develop Front End Agreement<br />
2. Create the Joint Business Plan<br />
3. Create the Sales Forecast<br />
4. Identify Exceptions for Sales Forecast<br />
5. Resolve/Collaborate on Exception Items<br />
6. Create Order Forecast<br />
7. Identify Exceptions for Order Forecast<br />
8. Resolve/Collaborate on Exception Items<br />
9. Order Generation <br />
<br />
The CPFR reference model provides a general framework for the collaborative aspects of planning, forecasting and replenishment processes.<br />
<br />
<br />
The main processes shown in the model go in a circular pattern and have four stages. This is displayed on the figure. Each stage will be described in detail below <ref> CPFR Committee, 2011, http://www.vics.org/committees/cpfr/,</ref>:<br />
*'''Strategy & Planning''', Collaboration Arrangement is the process of setting the business goals for the relationship, defining the scope of collaboration and assigning roles, responsibilities, checkpoints and escalation procedures. The Joint Business Plan then identifies the significant events that affect supply and demand in the planning period, such as promotions, inventory policy changes, store openings/closings, and product introductions. <br />
*'''Demand & Supply Management''' is broken into Sales Forecasting, which projects consumer demand at the point of sale, and Order Planning/Forecasting, which determines future product ordering and delivery requirements based upon the sales forecast, inventory positions, transit lead times, and other factors. <br />
*'''Execution''' consists of Order Generation, which transitions forecasts to firm demand, and Order Fulfillment, the process of producing, shipping, delivering, and stocking products for consumer purchase. <br />
*'''Analysis tasks''' include Exception Management, the active monitoring of planning and operations for out-of-bounds conditions, and Performance Assessment, the calculation of key metrics to evaluate the achievement of business goals, uncover trends or develop alternative strategies<br />
<br />
==CPFR Benefits==<br />
CPFR benefits from demand point of view: <br />
*'''Enhanced Relationship'''<br />
**Implicitly, CPFR strengthens an existing relationship and substantially accelerates the growth of a new one. <br />
**Buyer and seller work hand-in-hand from inception through fruition on business plan, base, and promotional forecasts. <br />
**Continual CPFR meetings strengthen this relationship. <br />
*'''Greater Sales'''<br />
**The close collaboration needed for CPFR implementation drives the planning for an improved business plan between buyer and seller. <br />
**The strategic business advantage directly translates to increased category sales.<br />
*'''Category Management'''<br />
**Before beginning CPFR, both parties inspect shelf positioning and exposure for targeted SKUs to ensure adequate days of supply, and proper exposure to the consumer. <br />
**This scrutiny will result in improved shelf positioning and facings through sound category management.<br />
*'''Improved Product Offering'''<br />
**Before CPFR implementation, the buyer and seller collaborate on a mutual product scheme that includes SKU evaluation and additional product opportunities. <br />
CPFR benefits from supply point of view: <br />
*'''Improved Order Forecast Accuracy'''<br />
**CPFR enables a time-phased order forecast that provides additional information, greater lead time for production planning, and improved forecast accuracy vs. either stand-alone VMI/CRP or other industry tools.<br />
*'''Inventory Reductions'''<br />
**CPFR helps reduce forecast uncertainty and process inefficiencies. <br />
**How much inventory does your company hold to “cover up” for forecasting errors or a trading partner’s inability to have the product available in a timely manner?<br />
**With CPFR, product can be produced to actual order instead of storing inventory based on forecast. <br />
*'''Improved Technology ROI'''<br />
**Through the CPFR process, technology investments for internal integration can be enabled with higher quality forecast information.<br />
**Your company will benefit by driving internal processes with common, high-quality data. <br />
*'''Improved Overall ROI'''<br />
**As other processes improve, the return on investment from CPFR can be substantial.<br />
*'''Increased Customer Satisfaction'''<br />
**With fewer out-of-stocks resulting from better planning information, higher store service levels will prevail, offering greater consumer satisfaction.<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/3PL3PL2011-08-21T14:03:44Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Логистические_провайдеры Логистические провайдеры]'''<br />
<br />
Third-party logistics (3PL) is a model of outsourced logistics and related processes. A '''3PL provider''' is an organization that delivers integrated logistics services for the customer: transportation, warehousing, handling, securing, customs clearance, etc. 3PLs typically specialize in integrated operation, warehousing and transportation services that can be scaled and customized to customer’s needs based on market conditions and the demands and delivery service requirements for their products and materials. <br />
<br />
Advantages: <br />
*Focus on core strength <br />
*Provides technological flexibility <br />
*Provides other flexibilities <br />
Disadvantages: <br />
*Loss of control <br />
According to (Hertz and Alfredsson, 2003) <ref>Hertz S. and Alfredsson M. (2003) Strategic development of third party logistics providers. Industrial Marketing Management 32: pp. 139–149</ref>, the following 4 categories of 3PL organizations are distinguished:<br />
*'''Standard 3PL provider:''' this is the most basic form of a 3PL provider. It would perform activities such as, pick and pack, warehousing, and distribution (business) – the most basic functions of logistics. For a majority of these firms, the 3PL function is not their main activity.<br />
*'''Service developer:''' this type of 3PL provider will offer their customers advanced value-added services such as: tracking and tracing, cross-docking, specific packaging, or providing a unique security system. A solid IT foundation and a focus on economies of scale and scope will enable this type of 3PL provider to perform these types of tasks.<br />
*'''The customer adapter:''' this type of 3PL provider comes in at the request of the customer and essentially takes over complete control of the company's logistics activities. The 3PL provider improves the logistics dramatically, but do not develop a new service. The customer base for this type of 3PL provider is typically quite small.<br />
*'''The customer developer:''' this is the highest level that a 3PL provider can attain with respect to its processes and activities. This occurs when a 3PL provider integrates itself with the customer and takes over the latter's entire logistics function. These providers will have few customers, but will perform extensive and detailed tasks for them.<br />
<br />
<br />
==References==<br />
<references/><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Bullwhip_effectBullwhip effect2011-08-21T13:58:27Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Эффект_хлыста Эффект хлыста]'''<br />
<br />
[[File:Bullwhip effect.png|thumb|Illustration of the bullwhip effect: the ultimate customer places an order (whip) and order fluctuations build up upstream the [[supply chain]].]]<br />
<br />
The bullwhip effect (also known as demand amplification, whip-saw, whiplash effect, or Forrester effect) refers to the phenomenon of demand variability amplification as moving up in the supply chain: from the point of actual (final) demand to the point of origin <ref>Lee H.L., Padmanabhan V. and Whang S. (1997) Information distortion in a supply chain: The bullwhip effect, Management Science; Apr 1997; 43, 4; pg. 546</ref>. It means that variability at the "end" of supply chain (closer to consumption, e. g. retailer) is much less, than at the other "end", where it begins (far from consumer, e. g. producer or supplier). Moving up in the supply chain from consumer to supplier increases demand variability. The more actors exist in a particular supply chain and the greater is [[lead time]], the greater demand variability would be. <br />
<br />
The first record of this phenomena belongs, probably, to J. Forrester <ref>Forrester J.W., (1961) Industrial dynamics. New York: MIT Press and John Wiley & Sons.</ref> (that is why it is possible to find in the literature references to "Forrester effect", although J. Forrester had never named it neither Forrester, nor bullwhip effect). The term "Forrester effect" used to denote what is now called demand signal processing, as Forrester was the first to demonstrate this phenomenon through dynamo simulation. In 1997, the phenomenon of bullwhip effect was popularized by Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref>. <br />
<br />
The bullwhip effect has quite negative impact on supply chain efficiency. It leads to excessive safety stock, higher production costs and overheads, potential final product quality distortions, poor customer service, lost sales, higher logistics costs, and so on. <br />
<br />
==Causes and Consequences of the Bullwhip Effect==<br />
Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref> identified four major causes of the bullwhip effect: <br />
<br />
*'''Demand forecast updating.''' Demand forecasting and production planning are often based on the history of direct customers` orders of the company. These customers, however, rarely make exactly the same orders in a short period of time as they receive from their own direct customers due to various reasons, including sales expectations, risk aversion, personal factors, industry characteristics, etc. As soon as a manager observes a change in downstream orders, he or she readjusts its own plans, however this order might not (and often not) reflect the real demand. As a result, each member of the supply chain makes slightly different order from the order it receives itself and, finally, the supplier may receives an order that is totally different from the real market dynamics. This situation is very common, because if the lead time is more than 0 (and it is 0 only in electronic commerce), it is a wise rule to keep safety stocks. The higher lead time the larger safety stock should be. On the one hand, the safety stocks are the cause of inefficiency in the supply chain, because they require extra operational costs, and on the other hand, they increase the bullwhip effect. <br />
<br />
*'''Order batching.''' Orders usually are accumulated in batches: in time (daily, weekly, monthly, etc.) or in volume (palette, container, etc). Batching also increase the bullwhip effect. There are various reasons for batching: from order processing costs (how much does the company spend on managing the orders) to transportation issues. Sometimes this effect is referred as the Burbidge effect<ref>Burbidge J.L. (1991) Period Batch Control (PBC) with GT – the Way Forward from MRP, PBCIS Annual Conference, Birmingham, UK</ref>. Burbidge outlined particular problems that my be caused by this effect unless duly watched. <br />
<br />
*'''Price fluctuation.''' Manufacturers or retailers often launch various promotion programs (discounts, flexible prices, etc.). As a result, customers observe different prices and may artificially boost or cut their buying to get benefits from temporary advantages. This leads to additional order fluctuations. For more information see [[EDLP EDLP]] <br />
<br />
*'''Rationing and shortage gaming.''' If the producer is not able to fulfill the excessive demand in a short period of time, and the retailer (wholesaler or distributor) knows about this, they will act to increase their orders to get at least something. For example, if the retailer really needs 100 pieces of a product and he knows that the producer will fulfill only about 50% of the order, he will order 200. However, "200 pieces" is very often a real practice of suppliers who make their strategic decisions basing on this information, however in the next period there might be only 100 (real) pieces ordered by retailers. Behavioral psychology often resorts to the term "bounded rationality" implying a sub-optimal but borderline rational decision making by actors<ref>Sterman J.D. (1989) Modeling managerial behavior: misperceptions of feedback in a dynamic decision making experiments. Management Science, 35 (3), p321–339</ref>. Rationing and gaming are sometimes referred to as the Houlihan effect after John Houlihan<ref>Houlihan J. B. (1988) International supply chains: a new approach. Management Decisions. Vol. 26. p13-19.</ref>. This effect suggests that missed deliveries lead to higher safety stock levels and thus inflated orders. As more orders are made, the chain becomes more vulnerable to unreliable sources as reliable ones lack capacity to increase production instantly. All this leads to the bullwhip effect going up the supply chain with increasing magnitude. Houlihan described this process as a "flywheel effect". Olsmats et al. (1988) demonstrated this phenomenon in action in the automotive sector. Price variation describes offering goods and services to consumers at lower prices through various promotions in order to boost immediate demand<ref> Olsmats C. M., Edghill J. S. and Towill D. R. (1988) Industrial dynamics model building of a close-coupled production-distribution system. Engineering Costs & Production Economics, Vol. 13 Issue 4, p295-310, 16p</ref>.<br />
<br />
Some of researchers try to find origins of the bullwhip effect in the psychology of decision makers. Using modeling of bullwhip effect with the Beer Game, they prove that the manager uses one of two basic strategies: ‘safe harbor’ or ‘panic’, both having negative impact on the supply chain efficiency. However, as soon as there is a chance for negotiation, the results of simulation become much better <ref>Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online Production Planning & Control, Vol. 17, No. 6, 547–557</ref>. <br />
<br />
Particularly negative impacts of the bullwhip effect for the supply chain are:<br />
*'''Inefficient inventory management.''' The varying demand leads to variation in inventory levels at each tier of the supply chain. As supplier receives order, which is higher than the order on previous period, the company has to increase inventory level. On the other hand, if the order level is lower, it is not always possible to decrease inventory level in short period of time. The higher variability in demand (in orders), the higher safety stocks should be. Safety stock have trend to increase, as moving away from point of consumption. <br />
*'''Backlogged orders and poor service to product outlets.''' The safety stock that is required to ensure a sufficient service level increases with the variation in the demand, however, it is not always enough to fulfill excessive demand (orders). Hence, sometimes companies might face absence of goods on the shelves of the retailer. <br />
*'''Unpredictable production schedules.''' A variation in demand causes variation in capacity usage. During “high” period producer usually has to increase the number of shifts. During “low” period – to make extra safety stocks or leave workers without any work (both cases lead to financial losses).<br />
*'''High prices for raw materials because of immediate need.''' In case of emergent need of producing the order, producer often face a situation of absence of raw materials (of some of raw materials). Ordering even small part of raw materials from supplier on emergence will cost to producer enormously high price (at least for unscheduled transportation) . <br />
*'''Lost revenues.''' All these leads to financial losses: extra safety stocks (means more capital employed) or missed orders (missed sales). <br />
<br />
<br />
Analyses of recent papers shows that researchers do not argue about the causes and consequences of bullwhip effect, but try to find remedies for negative impact on the supply chain performance.<br />
<br />
==Example of the Bullwhip Effect==<br />
Usually consumption of most FMCG goods is stable. For instance, consumption of diapers by babies – is constant; consumption of bread, salt, ketchup and other food – constant, etc. Retailers very often see smooth demand with minor fluctuations as shown on the figure below. <br />
<br />
<lines size=500x200 title="Customer Sales" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,12<br />
2,11<br />
3,12<br />
4,13<br />
5,12<br />
6,13<br />
7,11<br />
8,13<br />
9,10<br />
10,13<br />
11,12<br />
12,13<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,10<br />
19,13<br />
20,13<br />
</lines><br />
<br />
----<br />
<br />
However, while making its own orders the retailer takes into account his own stock levels (from previous periods), sales expectations (including expectations of his own advertising and promotion), discounts from the manufacturer or the distributor, the price of transportation, order processing and other minor factors. Therefore, orders do not look that smooth any more. <br />
<br />
<lines size=500x200 title="Retailer's Orders to Wholesaler" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,11<br />
3,12<br />
4,14<br />
5,12<br />
6,14<br />
7,11<br />
8,14<br />
9,10<br />
10,14<br />
11,12<br />
12,14<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,9<br />
19,13<br />
20,14<br />
</lines><br />
<br />
----<br />
<br />
Orders from the wholesaler to the distributor are even more volatile due to the same reasons. <br />
<br />
<lines size=500x200 title="Wholesaler's Orders to Distributor" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,17<br />
3,10<br />
4,9<br />
5,17<br />
6,19<br />
7,12<br />
8,10<br />
9,16<br />
10,15<br />
11,17<br />
12,16<br />
13,9<br />
14,11<br />
15,10<br />
16,14<br />
17,9<br />
18,10<br />
19,17<br />
20,11<br />
</lines><br />
<br />
----<br />
<br />
At the end of the supply chain, orders to the manufacturer are even more variable. The manufacturer now has to solve problems of extra labor force or extra safety stock to fulfill all the orders. Extra costs and order failures are very common in this situation. <br />
<br />
<lines size=500x200 title="Distributor's Orders to Manufacturer" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,2<br />
2,19<br />
3,22<br />
4,12<br />
5,16<br />
6,7<br />
7,17<br />
8,20<br />
9,10<br />
10,14<br />
11,3<br />
12,20<br />
13,12<br />
14,8<br />
15,10<br />
16,21<br />
17,14<br />
18,6<br />
19,13<br />
20,19<br />
</lines><br />
----<br />
The bullwhip effect has been studied well and diagnosed as a significant problem in general <ref>Buzzell R. D., J. A. Quelch and W. J. Salmon (1990) The costly bargain of trade promotion. Harvard Business Review, 68, p141–148</ref>,<ref>Richard M. (1997) Quantifying the bullwhip effect in supply chains. Journal of Operations Management, Vol. 15 Issue 2, p89-100</ref>, as well as in particular companies or industries: <br />
<br />
*Hi-tech industry<ref>Kelly, K. 1995. Burned by busy signals: Why Motorola ramped up production way past demand. Business Week 6 36</ref><br />
*Grocery industry<ref>Holmstrom, J. 1997. Product range management: a case study of supply chain operations in the European grocery industry. Supply Chain Management 2(3) 107–115</ref><br />
*Manufacturing sector<ref> Dooley K., Yan T., Mohan S., Gopalakrishnan M. (2010) Inventory management and the bullwhip effect during the 2007–2009 recession: evidence from the manufacturing sector. Journal of Supply Chain Management, Vol. 46 Issue 1, p12-18 </ref><br />
* and other.<br />
<br />
==Analysis of the Bullwhip Effect==<br />
The bullwhip effect was analyzed by various researchers with different methods: <br />
*Simulation approach <ref> Wangphanich P., Kara S. and Kayis B. (2010) Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems-a simulation approach, International Journal of Production Research; Aug2010, Vol. 48 Issue 15, p4501-4517</ref><br />
*Evolutionary least-mean-square algorithm <ref>Tseng L-T., Tseng L-F., Chen H-C. (2011) Exploration of the bullwhip effect based on the evolutionary least-mean-square algorithm, International Journal of Electronic Business Management, Vol. 9 Issue 2, p160-168 </ref><br />
* Beer game simulation with different demand scenarios <ref> Matteo C., Chiara R., Tommaso R. and Fernanda S. (2010) Bullwhip effect and inventory oscillations analysis using the beer game model, International Journal of Production Research, Vol. 48 Issue 13, p3943-3956</ref><br />
*Multi-echelon supply chain system <ref> Xiao-Yuan, H. (2007) An H∞ control method of the bullwhip effect for a class of supply chain system. International Journal of Production Research, Vol. 45 Issue 1, p207-226</ref><br />
*Analytical approach<br />
<br />
==Bullwhip Effect Simulation (Beer Game)==<br />
[[File:beergame.png|thumb|Beergame illustration. Source: Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557]]<br />
<br />
Bullwhip Effect Simulation Game (Beer Game, also known as beer distribution game) was developed by the Systems Dynamics Group at the Massachusetts Institute of Technology in the 1960s. It demonstrates the bullwhip effect by simulating a supply chain with four tiers: the retailer, the wholesaler, the distributor or the factory. It might be played in class or on-line and is a very effective mean of illustrating systems thinking. By enabling managers to experience the negative impact of the bullwhip effect on supply chain performance, the beer game makes them aware of the application of countermeasures in their companies<rev> Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557</ref>.<br />
Each player takes the role (individually or in group of 2-3 players) one of the roles. An ultimate customer places orders at the retailer (buys beer). His demand is defined, but unknown to the participants. The ultimate demand is four units (bottles, packs of beer) during the first six periods (including “test” or “zero” period) and eight units during the following periods of the simulation. The game usually lasts for 50-70 period. It is enough to diagnose bullwhip effect. Each period represents one week. During this period participants have to make important decisions and activities in strict order:<br />
* Each player (team) receives order from their customer. For retailer it is pre-defined order (demand). For the rest of players it is orders from previous players (eg order from wholesaler for distributor). <br />
* Each player (team) makes a decision of how much to order. This decision is based on the received orders, on backlogged orders (all orders should be accomplished), on the previous orders, on the inventory left in stock and other factors. <br />
*Each player (team) has to minimize its costs. A product on stock (safety stock) costs $0.50 per product per period. Backlogged orders costs $1.00 per product per period (penalty for out-of-stock situations). Thus participants have to take into account a trade-off between minimizing the costs of capital employed in stocks on the one hand and avoiding of out-of-stock situations, on the other hand.<br />
Information flow (the information of how much to order) moves along supply chain with a delay of one week. It represents common situation in real companies. Good flow has a delay of two weeks due to transportation. Producer gets its orders from production after two weeks as well (to make it easier it is possible to say that one week is for production and one week is for quality control and packaging). <br />
Some important rules to remember: <br />
* Do not try to look for your demand before it is time to. <br />
* Do not change the sequence of steps. <br />
* Do not mix the orders and finished products. <br />
* It is possible to make an empty order. <br />
* If you missed the round, don’t try to catch-up. Make sure that all other members did it correctly.<br />
<br />
==Remedies for the Bullwhip Effect==<br />
Lee et al. (1997) proposed a framework for supply chain initiatives to deal with the bullwhip effect: information sharing, channel alignment, operational efficiency. It was criticized for general approach and since then a lot of papers on this topic, trying to find more general or more specific solutions: <br />
* Ordering policy<ref>Disney S.M. and Towill D.R., (2003) On the bullwhip and inventory variance produced by an<br />
ordering policy. Omega, 31 (3), 157–167</ref>,<ref>Kelle P. and Milne A. (1999) The effect of (s,S) ordering policy on the supply chain. International Journal of Production Economics, 59 (1–3), 113–122 </ref><br />
* Lot sizing rules <ref> Pujawan I.N. (2004) The effect of lot sizing rules on order variability. European Journal of<br />
Operations Research, 159 (3), 617–635</ref><br />
* Forecasting improvements<ref>Zhang X. (2005) Delayed demand information and the dampened bullwhip effect. Operations Research<br />
Letters, 33 (3), 289–294</ref>,<ref>Zhao X. and Xie J. (2002) Forecasting errors and the value of information sharing in a supply chain. International Journal of Production Research, 40 (2), 311–335</ref>,<ref>Croson R. and Donohue K. (2005) Upstream versus downstream information and its impact on the bullwhip effect. System Dynamics Review, 21 (3), 249–260</ref>,<ref>Ingalls R.G., Foote B.L. and Krishnamoorthy A. (2005) Reducing the bullwhip effect in supply<br />
chains with control-based forecasting. International Journal of Simulation & Process Modelling, 1–2 (1), 90–110</ref><br />
* Decreasing demand variability <ref>Lin C. and Lin Y. (2006) Issues in the reduction of demand variance in the supply chain.<br />
International Journal of Production Research, 44 (9), 1821–1843</ref><br />
* A multi-agent approach <ref> Qing Cao and Leggio K. (2008) Alleviating the bullwhip effect in supply chain management using the multi-agent approach: an empirical study. International Journal of Computer Applications in Technology, Vol. 31 Issue 3/4, p225-237</ref><br />
Information sharing is one of the most important tools for minimizing the bullwhip effect. Most of contemporary tools and approaches, including [[VMI]], [[CPFR]], etc. and technical innovations, such as [[RFID]] use this principle. The importance of information in supply chains: <br />
*Helps reduce variability in supply chains <br />
*Help suppliers make better forecast <br />
*Enables the coordination system of manufacturing and distribution systems and strategies <br />
*Enables retailers to serve their customers better <br />
*Enables retailers to react and adapt to supply chain problems more rapidly <br />
*Enables lead time reductions<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Bullwhip_effectBullwhip effect2011-08-21T02:08:02Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Эффект_хлыста Эффект хлыста]'''<br />
<br />
[[File:Bullwhip effect.png|thumb|Illustration of the bullwhip effect: the ultimate customer places an order (whip) and order fluctuations build up upstream the [[supply chain]].]]<br />
<br />
The bullwhip effect (also known as demand amplification, whip-saw, whiplash effect, or Forrester effect) refers to the phenomenon of demand variability amplification as moving up in the supply chain: from the point of actual (final) demand to the point of origin <ref>Lee H.L., Padmanabhan V. and Whang S. (1997) Information distortion in a supply chain: The bullwhip effect, Management Science; Apr 1997; 43, 4; pg. 546</ref>. It means that variability at the "end" of supply chain (closer to consumption, e. g. retailer) is much less, than at the other "end", where it begins (far from consumer, e. g. producer or supplier). Moving up in the supply chain from consumer to supplier increases demand variability. The more actors exist in a particular supply chain and the greater is [[lead time]], the greater demand variability would be. <br />
<br />
The first record of this phenomena belongs, probably, to J. Forrester <ref>Forrester J.W., (1961) Industrial dynamics. New York: MIT Press and John Wiley & Sons.</ref> (that is why it is possible to find in the literature references to "Forrester effect", although J. Forrester had never named it neither Forrester, nor bullwhip effect). The term "Forrester effect" used to denote what is now called demand signal processing, as Forrester was the first to demonstrate this phenomenon through dynamo simulation. In 1997, the phenomenon of bullwhip effect was popularized by Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref>. <br />
<br />
The bullwhip effect has quite negative impact on supply chain efficiency. It leads to excessive safety stock, higher production costs and overheads, potential final product quality distortions, poor customer service, lost sales, higher logistics costs, and so on. <br />
<br />
==Causes and Consequences of the Bullwhip Effect==<br />
Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref> identified four major causes of the bullwhip effect: <br />
<br />
*'''Demand forecast updating.''' Demand forecasting and production planning are often based on the history of direct customers` orders of the company. These customers, however, rarely make exactly the same orders in a short period of time as they receive from their own direct customers due to various reasons, including sales expectations, risk aversion, personal factors, industry characteristics, etc. As soon as a manager observes a change in downstream orders, he or she readjusts its own plans, however this order might not (and often not) reflect the real demand. As a result, each member of the supply chain makes slightly different order from the order it receives itself and, finally, the supplier may receives an order that is totally different from the real market dynamics. This situation is very common, because if the lead time is more than 0 (and it is 0 only in electronic commerce), it is a wise rule to keep safety stocks. The higher lead time the larger safety stock should be. On the one hand, the safety stocks are the cause of inefficiency in the supply chain, because they require extra operational costs, and on the other hand, they increase the bullwhip effect. <br />
<br />
*'''Order batching.''' Orders usually are accumulated in batches: in time (daily, weekly, monthly, etc.) or in volume (palette, container, etc). Batching also increase the bullwhip effect. There are various reasons for batching: from order processing costs (how much does the company spend on managing the orders) to transportation issues. Sometimes this effect is referred as the Burbidge effect<ref>Burbidge J.L. (1991) Period Batch Control (PBC) with GT – the Way Forward from MRP, PBCIS Annual Conference, Birmingham, UK</ref>. Burbidge outlined particular problems that my be caused by this effect unless duly watched. <br />
<br />
*'''Price fluctuation.''' Manufacturer or retailer often make different promotion programs (special discounts, price terms, rebates, etc.). These programs cause price fluctuations. As a result, customers see different price and react differently. For more information see [[http://scm.gsom.spbu.ru/EDLP EDLP]] <br />
<br />
*'''Rationing and shortage gaming.''' If producer is not able to fulfill the excessive demand in short period of time, and retailer (wholesaler or distributor) know about it, they will act to increase the orders to get at least something. For example, if retailer really needs 100 pieces of product and it knows that producer will fulfill only about 50% of the order, it will order 200. However, very often, 200 pieces is “the real picture” for the supplier and it make its strategic decisions basing on this information, however in the next period there might be only 100 (real) pieces in order from retailer. Behavioral psychology often resorts to the term bounded rationality implying sub-optimal but borderline rational decision making by actors<ref>Sterman J.D. (1989) Modeling managerial behavior: misperceptions of feedback in a dynamic<br />
decision making experiments. Management Science, 35 (3), p321–339</ref>. Rationing and gaming are sometimes referred to as the Houlihan effect after Houlihan<ref>Houlihan J. B. (1988) International supply chains : a new approach. Management Decisions. Vol. 26. p13-19.</ref>. This effect suggests that missed deliveries lead to higher safety stock levels and thus inflated orders. As more orders are made, the chain becomes more vulnerable to unreliable sources as reliable ones lack capacity to increase production instantly. All of this leads to bullwhip effect going up the supply chain with increasing magnitude. Houlihan described this process as the flywheel effect. Olsmats et al. (1988) demonstrated this phenomenon in action in the automotive sector. Price variation describes offering goods and services to consumers at lower prices through various promotions in order to boost immediate demand assuming elasticity<ref> Olsmats C. M., Edghill J. S. and Towill D. R. (1988) Industrial dynamics model building of a close-coupled production-distribution system. Engineering Costs & Production Economics, Vol. 13 Issue 4, p295-310, 16p</ref>.<br />
<br />
Some of researchers try to find origins of the bullwhip effect problems in psychology of manager, who takes a decision. Using modeling of bullwhip effect with a beer game, they prove that manager use one of two basic strategies: ‘safe harbor’ or ‘panic’, both of them have negative impact on the supply chain efficiency. However, as soon as there is a chance for negotiation, the results of simulation become much better <ref>Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online Production Planning & Control, Vol. 17, No. 6, 547–557</ref>. <br />
<br />
Particularly negative impacts of the bullwhip effect for the supply chain are:<br />
*'''Inefficient inventory management.''' The varying demand leads to variation in inventory levels at each tier of the supply chain. As supplier receives order, which is higher than the order on previous period, the company has to increase inventory level. On the other hand, if the order level is lower, it is not always possible to decrease inventory level in short period of time. The higher variability in demand (in orders), the higher safety stocks should be. Safety stock have trend to increase, as moving away from point of consumption. <br />
*'''Backlogged orders and poor service to product outlets.''' The safety stock that is required to ensure a sufficient service level increases with the variation in the demand, however, it is not always enough to fulfill excessive demand (orders). Hence, sometimes companies might face absence of goods on the shelves of the retailer. <br />
*'''Unpredictable production schedules.''' A variation in demand causes variation in capacity usage. During “high” period producer usually has to increase the number of shifts. During “low” period – to make extra safety stocks or leave workers without any work (both cases lead to financial losses).<br />
*'''High prices for raw materials because of immediate need.''' In case of emergent need of producing the order, producer often face a situation of absence of raw materials (of some of raw materials). Ordering even small part of raw materials from supplier on emergence will cost to producer enormously high price (at least for unscheduled transportation) . <br />
*'''Lost revenues.''' All these leads to financial losses: extra safety stocks (means more capital employed) or missed orders (missed sales). <br />
<br />
<br />
Analyses of recent papers shows that researchers do not argue about the causes and consequences of bullwhip effect, but try to find remedies for negative impact on the supply chain performance.<br />
<br />
==Example of the Bullwhip Effect==<br />
Usually consumption of most FMCG goods is stable. For instance, consumption of diapers by babies – is constant; consumption of bread, salt, ketchup and other food – constant, etc. Retailers very often see smooth demand with minor fluctuations as seen on the figure below. <br />
<br />
<lines size=500x200 title="Customer Sales" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,12<br />
2,11<br />
3,12<br />
4,13<br />
5,12<br />
6,13<br />
7,11<br />
8,13<br />
9,10<br />
10,13<br />
11,12<br />
12,13<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,10<br />
19,13<br />
20,13<br />
</lines><br />
<br />
----<br />
<br />
Making its own orders, however, retailer take in account own stock levels (from previous periods), sales expectations (including expectations on own advertising and promotion), discounts from manufacturer or distributor, the price of transportation, order processing and other minor factors. Orders are not that smooth any more. <br />
<br />
<lines size=500x200 title="Retailer's Orders to Wholesaler" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,11<br />
3,12<br />
4,14<br />
5,12<br />
6,14<br />
7,11<br />
8,14<br />
9,10<br />
10,14<br />
11,12<br />
12,14<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,9<br />
19,13<br />
20,14<br />
</lines><br />
<br />
----<br />
<br />
Orders from wholesaler to distributor are even more volatile due to the same reasons. <br />
<br />
<lines size=500x200 title="Wholesaler's Orders to Distributor" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,17<br />
3,10<br />
4,9<br />
5,17<br />
6,19<br />
7,12<br />
8,10<br />
9,16<br />
10,15<br />
11,17<br />
12,16<br />
13,9<br />
14,11<br />
15,10<br />
16,14<br />
17,9<br />
18,10<br />
19,17<br />
20,11<br />
</lines><br />
<br />
----<br />
<br />
At the end of supply chain, orders to manufacturer are even more variable. Manufacturer now has to solve problems of extra shifts or extra safety stock to fulfill all the orders. Extra costs and order failures are very common in this situation. <br />
<br />
<lines size=500x200 title="Distributor's Orders to Manufacturer" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,2<br />
2,19<br />
3,22<br />
4,12<br />
5,16<br />
6,7<br />
7,17<br />
8,20<br />
9,10<br />
10,14<br />
11,3<br />
12,20<br />
13,12<br />
14,8<br />
15,10<br />
16,21<br />
17,14<br />
18,6<br />
19,13<br />
20,19<br />
</lines><br />
----<br />
The bullwhip effect has been studied well and diagnosed as a significant problem in general <ref>Buzzell R. D., J. A. Quelch and W. J. Salmon (1990) The costly bargain of trade promotion. Harvard Business Review, 68, p141–148</ref>,<ref>Richard M. (1997) Quantifying the bullwhip effect in supply chains. Journal of Operations Management, Vol. 15 Issue 2, p89-100</ref>, as well as in particular companies or industries: <br />
<br />
*Hi-tech industry<ref>Kelly, K. 1995. Burned by busy signals: Why Motorola ramped up production way past demand. Business Week 6 36</ref><br />
*Grocery industry<ref>Holmstrom, J. 1997. Product range management: a case study of supply chain operations in the European grocery industry. Supply Chain Management 2(3) 107–115</ref><br />
*Manufacturing sector<ref> Dooley K., Yan T., Mohan S., Gopalakrishnan M. (2010) Inventory management and the bullwhip effect during the 2007–2009 recession: evidence from the manufacturing sector. Journal of Supply Chain Management, Vol. 46 Issue 1, p12-18 </ref><br />
* and other.<br />
<br />
==Analysis of the Bullwhip Effect==<br />
The bullwhip effect was analyzed by various researchers with different methods: <br />
*Simulation approach <ref> Wangphanich P., Kara S. and Kayis B. (2010) Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems-a simulation approach, International Journal of Production Research; Aug2010, Vol. 48 Issue 15, p4501-4517</ref><br />
*Evolutionary least-mean-square algorithm <ref>Tseng L-T., Tseng L-F., Chen H-C. (2011) Exploration of the bullwhip effect based on the evolutionary least-mean-square algorithm, International Journal of Electronic Business Management, Vol. 9 Issue 2, p160-168 </ref><br />
* Beer game simulation with different demand scenarios <ref> Matteo C., Chiara R., Tommaso R. and Fernanda S. (2010) Bullwhip effect and inventory oscillations analysis using the beer game model, International Journal of Production Research, Vol. 48 Issue 13, p3943-3956</ref><br />
*Multi-echelon supply chain system <ref> Xiao-Yuan, H. (2007) An H∞ control method of the bullwhip effect for a class of supply chain system. International Journal of Production Research, Vol. 45 Issue 1, p207-226</ref><br />
*Analytical approach<br />
<br />
==Bullwhip Effect Simulation (Beer Game)==<br />
[[File:beergame.png|thumb|Beergame illustration. Source: Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557]]<br />
<br />
Bullwhip Effect Simulation Game (Beer Game, also known as beer distribution game), which was developed by the Systems Dynamics Group at the Massachusetts Institute of Technology in the 1960s. It demonstrates the bullwhip effect by simulating a supply chain with four tiers: the retailer, the wholesaler, the distributor or the factory. It might be played in class or on-line and is very effective mean of illustrating systems thinking. By enabling managers to experience the negative impact of the bullwhip effect on supply chain performance, the beer game makes them aware of the application of countermeasures in their companies<rev> Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557</ref>.<br />
Each player takes the role (individually or in group of 2-3 players) one of the roles. An ultimate customer places orders at the retailer (buys beer). His demand is defined, but unknown to the participants. The ultimate demand is four units (bottles, packs of beer) during the first six periods (including “test” or “zero” period) and eight units during the following periods of the simulation. The game usually lasts for 50-70 period. It is enough to diagnose bullwhip effect. Each period represents one week. During this period participants have to make important decisions and activities in strict order:<br />
* Each player (team) receives order from their customer. For retailer it is pre-defined order (demand). For the rest of players it is orders from previous players (eg order from wholesaler for distributor). <br />
* Each player (team) makes a decision of how much to order. This decision is based on received order, on backlogged orders (all orders should be accomplished), on previous orders, on inventory left in stock and other factors. <br />
*Each player (team) has to minimize its costs. A product on stock (safety stock) costs $0.50 per product per period. Backlogged orders costs $1.00 per product per period (penalty for out-of-stock situations). Thus participants have to take into account a trade-off between minimizing the costs of capital employed in stocks on the one hand and avoiding of out-of-stock situations, on the other hand.<br />
Information flow (the information of how much to order) moves along supply chain with a delay of one week. It represents common situation in real companies. Good flow has a delay of two weeks due to transportation. Producer gets its orders from production after two weeks as well (to make it easier it is possible to say that one week is for production and one week is for quality control and packaging). <br />
Some important rules to remember: <br />
* Do not try to look for your demand before there is time to. <br />
* Do not change the sequence of steps. <br />
* Do not mix the orders and finished products. <br />
* It is possible to make 0 order. <br />
* If you missed the round, don’t try to catch-up. Make sure that all other members did it correctly.<br />
<br />
==Remedies for the Bullwhip Effect==<br />
Lee et al. (1997) proposed a framework for supply chain initiatives to deal with the bullwhip effect: information sharing, channel alignment, operational efficiency. It was criticized for general approach and since then a lot of papers on this topic, trying to find more general or more specific solutions: <br />
* Ordering policy<ref>Disney S.M. and Towill D.R., (2003) On the bullwhip and inventory variance produced by an<br />
ordering policy. Omega, 31 (3), 157–167</ref>,<ref>Kelle P. and Milne A. (1999) The effect of (s,S) ordering policy on the supply chain. International Journal of Production Economics, 59 (1–3), 113–122 </ref><br />
* Lot sizing rules <ref> Pujawan I.N. (2004) The effect of lot sizing rules on order variability. European Journal of<br />
Operations Research, 159 (3), 617–635</ref><br />
* Forecasting improvements<ref>Zhang X. (2005) Delayed demand information and dampened bullwhip effect. Operations Research<br />
Letters, 33 (3), 289–294</ref>,<ref>Zhao X. and Xie J. (2002) Forecasting errors and the value of information sharing in a supply chain. International Journal of Production Research, 40 (2), 311–335</ref>,<ref>Croson R. and Donohue K. (2005) Upstream versus downstream information and its impact on the bullwhip effect. System Dynamics Review, 21 (3), 249–260</ref>,<ref>Ingalls R.G., Foote B.L. and Krishnamoorthy A. (2005) Reducing the bullwhip effect in supply<br />
chains with control-based forecasting. International Journal of Simulation & Process Modelling, 1–2 (1), 90–110</ref><br />
* Decreasing demand variability <ref>Lin C. and Lin Y. (2006) Issues in the reduction of demand variance in the supply chain.<br />
International Journal of Production Research, 44 (9), 1821–1843</ref><br />
* Multi-agent approach <ref> Qing Cao and Leggio K. (2008) Alleviating the bullwhip effect in supply chain management using the multi-agent approach: an empirical study. International Journal of Computer Applications in Technology, Vol. 31 Issue 3/4, p225-237</ref><br />
Information sharing is one of the most important tools for minimizing bullwhip effect. Most of contemporary tools and approaches, including [[VMI]], [[CPFR]], etc. and technical innovations, such as [[RFID]] use this principle. The importance of information in supply chains: <br />
*Helps reduce variability in supply chains <br />
*Help suppliers make better forecast <br />
*Enables the coordination system of manufacturing and distribution systems and strategies <br />
*Enables retailers to better serve their customers<br />
*Enables retailers to react and adapt to supply chain problems more rapidly <br />
*Enables lead time reductions<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Bullwhip_effectBullwhip effect2011-08-21T00:59:48Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Эффект_хлыста Эффект хлыста]'''<br />
<br />
[[File:Bullwhip effect.png|thumb|Illustration of the bullwhip effect: the ultimate customer places an order (whip) and order fluctuations build up upstream the [[supply chain]].]]<br />
<br />
The bullwhip effect (also known as demand amplification, whip-saw, whiplash effect, or Forrester effect) refers to the phenomenon of demand variability amplification as moving up in the supply chain: from the point of actual (final) demand to the point of origin <ref>Lee H.L., Padmanabhan V. and Whang S. (1997) Information distortion in a supply chain: The bullwhip effect, Management Science; Apr 1997; 43, 4; pg. 546</ref>. It means that variability at the "end" of supply chain (closer to consumption, e. g. retailer) is much less, than at the other "end", where it begins (far from consumer, e. g. producer or supplier). Moving up in the supply chain from consumer to supplier increases demand variability. The more actors exist in a particular supply chain and the greater is [[lead time]], the greater demand variability would be. <br />
<br />
The first record of this phenomena belongs, probably, to J. Forrester <ref>Forrester J.W., (1961) Industrial dynamics. New York: MIT Press and John Wiley & Sons.</ref> (that is why it is possible to find in the literature references to "Forrester effect", although J. Forrester had never named it neither Forrester, nor bullwhip effect). The term "Forrester effect" used to denote what is now called demand signal processing, as Forrester was the first to demonstrate this phenomenon through dynamo simulation. In 1997, the phenomenon of bullwhip effect was popularized by Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref>. <br />
<br />
The bullwhip effect has quite negative impact on supply chain efficiency. It leads to excessive safety stock, higher production costs and overheads, potential final product quality distortions, poor customer service, lost sales, higher logistics costs, and so on. <br />
<br />
==Causes and Consequences of the Bullwhip Effect==<br />
Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref> identified four major causes of the bullwhip effect: <br />
<br />
*'''Demand forecast updating.''' Demand forecasting and production planning are often based on the history of direct customers` orders of the company. These customers, however, rarely make exactly the same orders in a short period of time as they receive from their own direct customers due to various reasons, including sales expectations, risk aversion, personal factors, industry characteristics, etc. As soon as a manager observes a change in downstream orders, he or she readjusts its own plans, however this order might not (and often not) reflect the real demand. As a result, each member of the supply chain makes slightly different order from the order it receives itself and, finally, the supplier may receives an order that is totally different from the real market dynamics. This situation is very common, because if the lead time is more than 0 (and it is 0 only in electronic commerce), it is a wise rule to keep safety stocks. The higher lead time, the larger safety stock should be. On the one hand, the safety stocks are the cause of inefficiency in the supply chain, because they require extra operational costs, and on the other hand, they increase the bullwhip effect. <br />
<br />
*'''Order batching.''' Orders usually are accumulated in batches: in time (daily, weekly, monthly, etc.) or in volume (pallete, container, etc). Batches also increase the bullwhip effect. The reason for batches is different: from order processing costs (how much does the company spend on managing the orders) to transportation issues. Sometimes this effect is referred as Burbidge effect<ref>Burbidge J.L. (1991) Period Batch Control (PBC) with GT – the Way Forward from MRP, PBCIS Annual Conference, Birmingham, UK</ref>. Burbidge points out particular problems that this effect might cause shopkeepers unless duly watched. <br />
<br />
*'''Price fluctuation.''' Manufacturer or retailer often make different promotion programs (special discounts, price terms, rebates, etc.). These programs cause price fluctuations. As a result, customers see different price and react differently. For more information see [[http://scm.gsom.spbu.ru/EDLP EDLP]] <br />
<br />
*'''Rationing and shortage gaming.''' If producer is not able to fulfill the excessive demand in short period of time, and retailer (wholesaler or distributor) know about it, they will act to increase the orders to get at least something. For example, if retailer really needs 100 pieces of product and it knows that producer will fulfill only about 50% of the order, it will order 200. However, very often, 200 pieces is “the real picture” for the supplier and it make its strategic decisions basing on this information, however in the next period there might be only 100 (real) pieces in order from retailer. Behavioral psychology often resorts to the term bounded rationality implying sub-optimal but borderline rational decision making by actors<ref>Sterman J.D. (1989) Modeling managerial behavior: misperceptions of feedback in a dynamic<br />
decision making experiments. Management Science, 35 (3), p321–339</ref>. Rationing and gaming are sometimes referred to as the Houlihan effect after Houlihan<ref>Houlihan J. B. (1988) International supply chains : a new approach. Management Decisions. Vol. 26. p13-19.</ref>. This effect suggests that missed deliveries lead to higher safety stock levels and thus inflated orders. As more orders are made, the chain becomes more vulnerable to unreliable sources as reliable ones lack capacity to increase production instantly. All of this leads to bullwhip effect going up the supply chain with increasing magnitude. Houlihan described this process as the flywheel effect. Olsmats et al. (1988) demonstrated this phenomenon in action in the automotive sector. Price variation describes offering goods and services to consumers at lower prices through various promotions in order to boost immediate demand assuming elasticity<ref> Olsmats C. M., Edghill J. S. and Towill D. R. (1988) Industrial dynamics model building of a close-coupled production-distribution system. Engineering Costs & Production Economics, Vol. 13 Issue 4, p295-310, 16p</ref>.<br />
<br />
Some of researchers try to find origins of the bullwhip effect problems in psychology of manager, who takes a decision. Using modeling of bullwhip effect with a beer game, they prove that manager use one of two basic strategies: ‘safe harbor’ or ‘panic’, both of them have negative impact on the supply chain efficiency. However, as soon as there is a chance for negotiation, the results of simulation become much better <ref>Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online Production Planning & Control, Vol. 17, No. 6, 547–557</ref>. <br />
<br />
Particularly negative impacts of the bullwhip effect for the supply chain are:<br />
*'''Inefficient inventory management.''' The varying demand leads to variation in inventory levels at each tier of the supply chain. As supplier receives order, which is higher than the order on previous period, the company has to increase inventory level. On the other hand, if the order level is lower, it is not always possible to decrease inventory level in short period of time. The higher variability in demand (in orders), the higher safety stocks should be. Safety stock have trend to increase, as moving away from point of consumption. <br />
*'''Backlogged orders and poor service to product outlets.''' The safety stock that is required to ensure a sufficient service level increases with the variation in the demand, however, it is not always enough to fulfill excessive demand (orders). Hence, sometimes companies might face absence of goods on the shelves of the retailer. <br />
*'''Unpredictable production schedules.''' A variation in demand causes variation in capacity usage. During “high” period producer usually has to increase the number of shifts. During “low” period – to make extra safety stocks or leave workers without any work (both cases lead to financial losses).<br />
*'''High prices for raw materials because of immediate need.''' In case of emergent need of producing the order, producer often face a situation of absence of raw materials (of some of raw materials). Ordering even small part of raw materials from supplier on emergence will cost to producer enormously high price (at least for unscheduled transportation) . <br />
*'''Lost revenues.''' All these leads to financial losses: extra safety stocks (means more capital employed) or missed orders (missed sales). <br />
<br />
<br />
Analyses of recent papers shows that researchers do not argue about the causes and consequences of bullwhip effect, but try to find remedies for negative impact on the supply chain performance.<br />
<br />
==Example of the Bullwhip Effect==<br />
Usually consumption of most FMCG goods is stable. For instance, consumption of diapers by babies – is constant; consumption of bread, salt, ketchup and other food – constant, etc. Retailers very often see smooth demand with minor fluctuations as seen on the figure below. <br />
<br />
<lines size=500x200 title="Customer Sales" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,12<br />
2,11<br />
3,12<br />
4,13<br />
5,12<br />
6,13<br />
7,11<br />
8,13<br />
9,10<br />
10,13<br />
11,12<br />
12,13<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,10<br />
19,13<br />
20,13<br />
</lines><br />
<br />
----<br />
<br />
Making its own orders, however, retailer take in account own stock levels (from previous periods), sales expectations (including expectations on own advertising and promotion), discounts from manufacturer or distributor, the price of transportation, order processing and other minor factors. Orders are not that smooth any more. <br />
<br />
<lines size=500x200 title="Retailer's Orders to Wholesaler" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,11<br />
3,12<br />
4,14<br />
5,12<br />
6,14<br />
7,11<br />
8,14<br />
9,10<br />
10,14<br />
11,12<br />
12,14<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,9<br />
19,13<br />
20,14<br />
</lines><br />
<br />
----<br />
<br />
Orders from wholesaler to distributor are even more volatile due to the same reasons. <br />
<br />
<lines size=500x200 title="Wholesaler's Orders to Distributor" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,17<br />
3,10<br />
4,9<br />
5,17<br />
6,19<br />
7,12<br />
8,10<br />
9,16<br />
10,15<br />
11,17<br />
12,16<br />
13,9<br />
14,11<br />
15,10<br />
16,14<br />
17,9<br />
18,10<br />
19,17<br />
20,11<br />
</lines><br />
<br />
----<br />
<br />
At the end of supply chain, orders to manufacturer are even more variable. Manufacturer now has to solve problems of extra shifts or extra safety stock to fulfill all the orders. Extra costs and order failures are very common in this situation. <br />
<br />
<lines size=500x200 title="Distributor's Orders to Manufacturer" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,2<br />
2,19<br />
3,22<br />
4,12<br />
5,16<br />
6,7<br />
7,17<br />
8,20<br />
9,10<br />
10,14<br />
11,3<br />
12,20<br />
13,12<br />
14,8<br />
15,10<br />
16,21<br />
17,14<br />
18,6<br />
19,13<br />
20,19<br />
</lines><br />
----<br />
The bullwhip effect has been studied well and diagnosed as a significant problem in general <ref>Buzzell R. D., J. A. Quelch and W. J. Salmon (1990) The costly bargain of trade promotion. Harvard Business Review, 68, p141–148</ref>,<ref>Richard M. (1997) Quantifying the bullwhip effect in supply chains. Journal of Operations Management, Vol. 15 Issue 2, p89-100</ref>, as well as in particular companies or industries: <br />
<br />
*Hi-tech industry<ref>Kelly, K. 1995. Burned by busy signals: Why Motorola ramped up production way past demand. Business Week 6 36</ref><br />
*Grocery industry<ref>Holmstrom, J. 1997. Product range management: a case study of supply chain operations in the European grocery industry. Supply Chain Management 2(3) 107–115</ref><br />
*Manufacturing sector<ref> Dooley K., Yan T., Mohan S., Gopalakrishnan M. (2010) Inventory management and the bullwhip effect during the 2007–2009 recession: evidence from the manufacturing sector. Journal of Supply Chain Management, Vol. 46 Issue 1, p12-18 </ref><br />
* and other.<br />
<br />
==Analysis of the Bullwhip Effect==<br />
The bullwhip effect was analyzed by various researchers with different methods: <br />
*Simulation approach <ref> Wangphanich P., Kara S. and Kayis B. (2010) Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems-a simulation approach, International Journal of Production Research; Aug2010, Vol. 48 Issue 15, p4501-4517</ref><br />
*Evolutionary least-mean-square algorithm <ref>Tseng L-T., Tseng L-F., Chen H-C. (2011) Exploration of the bullwhip effect based on the evolutionary least-mean-square algorithm, International Journal of Electronic Business Management, Vol. 9 Issue 2, p160-168 </ref><br />
* Beer game simulation with different demand scenarios <ref> Matteo C., Chiara R., Tommaso R. and Fernanda S. (2010) Bullwhip effect and inventory oscillations analysis using the beer game model, International Journal of Production Research, Vol. 48 Issue 13, p3943-3956</ref><br />
*Multi-echelon supply chain system <ref> Xiao-Yuan, H. (2007) An H∞ control method of the bullwhip effect for a class of supply chain system. International Journal of Production Research, Vol. 45 Issue 1, p207-226</ref><br />
*Analytical approach<br />
<br />
==Bullwhip Effect Simulation (Beer Game)==<br />
[[File:beergame.png|thumb|Beergame illustration. Source: Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557]]<br />
<br />
Bullwhip Effect Simulation Game (Beer Game, also known as beer distribution game), which was developed by the Systems Dynamics Group at the Massachusetts Institute of Technology in the 1960s. It demonstrates the bullwhip effect by simulating a supply chain with four tiers: the retailer, the wholesaler, the distributor or the factory. It might be played in class or on-line and is very effective mean of illustrating systems thinking. By enabling managers to experience the negative impact of the bullwhip effect on supply chain performance, the beer game makes them aware of the application of countermeasures in their companies<rev> Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557</ref>.<br />
Each player takes the role (individually or in group of 2-3 players) one of the roles. An ultimate customer places orders at the retailer (buys beer). His demand is defined, but unknown to the participants. The ultimate demand is four units (bottles, packs of beer) during the first six periods (including “test” or “zero” period) and eight units during the following periods of the simulation. The game usually lasts for 50-70 period. It is enough to diagnose bullwhip effect. Each period represents one week. During this period participants have to make important decisions and activities in strict order:<br />
* Each player (team) receives order from their customer. For retailer it is pre-defined order (demand). For the rest of players it is orders from previous players (eg order from wholesaler for distributor). <br />
* Each player (team) makes a decision of how much to order. This decision is based on received order, on backlogged orders (all orders should be accomplished), on previous orders, on inventory left in stock and other factors. <br />
*Each player (team) has to minimize its costs. A product on stock (safety stock) costs $0.50 per product per period. Backlogged orders costs $1.00 per product per period (penalty for out-of-stock situations). Thus participants have to take into account a trade-off between minimizing the costs of capital employed in stocks on the one hand and avoiding of out-of-stock situations, on the other hand.<br />
Information flow (the information of how much to order) moves along supply chain with a delay of one week. It represents common situation in real companies. Good flow has a delay of two weeks due to transportation. Producer gets its orders from production after two weeks as well (to make it easier it is possible to say that one week is for production and one week is for quality control and packaging). <br />
Some important rules to remember: <br />
* Do not try to look for your demand before there is time to. <br />
* Do not change the sequence of steps. <br />
* Do not mix the orders and finished products. <br />
* It is possible to make 0 order. <br />
* If you missed the round, don’t try to catch-up. Make sure that all other members did it correctly.<br />
<br />
==Remedies for the Bullwhip Effect==<br />
Lee et al. (1997) proposed a framework for supply chain initiatives to deal with the bullwhip effect: information sharing, channel alignment, operational efficiency. It was criticized for general approach and since then a lot of papers on this topic, trying to find more general or more specific solutions: <br />
* Ordering policy<ref>Disney S.M. and Towill D.R., (2003) On the bullwhip and inventory variance produced by an<br />
ordering policy. Omega, 31 (3), 157–167</ref>,<ref>Kelle P. and Milne A. (1999) The effect of (s,S) ordering policy on the supply chain. International Journal of Production Economics, 59 (1–3), 113–122 </ref><br />
* Lot sizing rules <ref> Pujawan I.N. (2004) The effect of lot sizing rules on order variability. European Journal of<br />
Operations Research, 159 (3), 617–635</ref><br />
* Forecasting improvements<ref>Zhang X. (2005) Delayed demand information and dampened bullwhip effect. Operations Research<br />
Letters, 33 (3), 289–294</ref>,<ref>Zhao X. and Xie J. (2002) Forecasting errors and the value of information sharing in a supply chain. International Journal of Production Research, 40 (2), 311–335</ref>,<ref>Croson R. and Donohue K. (2005) Upstream versus downstream information and its impact on the bullwhip effect. System Dynamics Review, 21 (3), 249–260</ref>,<ref>Ingalls R.G., Foote B.L. and Krishnamoorthy A. (2005) Reducing the bullwhip effect in supply<br />
chains with control-based forecasting. International Journal of Simulation & Process Modelling, 1–2 (1), 90–110</ref><br />
* Decreasing demand variability <ref>Lin C. and Lin Y. (2006) Issues in the reduction of demand variance in the supply chain.<br />
International Journal of Production Research, 44 (9), 1821–1843</ref><br />
* Multi-agent approach <ref> Qing Cao and Leggio K. (2008) Alleviating the bullwhip effect in supply chain management using the multi-agent approach: an empirical study. International Journal of Computer Applications in Technology, Vol. 31 Issue 3/4, p225-237</ref><br />
Information sharing is one of the most important tools for minimizing bullwhip effect. Most of contemporary tools and approaches, including [[VMI]], [[CPFR]], etc. and technical innovations, such as [[RFID]] use this principle. The importance of information in supply chains: <br />
*Helps reduce variability in supply chains <br />
*Help suppliers make better forecast <br />
*Enables the coordination system of manufacturing and distribution systems and strategies <br />
*Enables retailers to better serve their customers<br />
*Enables retailers to react and adapt to supply chain problems more rapidly <br />
*Enables lead time reductions<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Bullwhip_effectBullwhip effect2011-08-21T00:28:32Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Эффект_хлыста Эффект хлыста]'''<br />
<br />
[[File:Bullwhip effect.png|thumb|Illustration of the bullwhip effect: the ultimate customer places an order (whip) and order fluctuations build up upstream the [[supply chain]].]]<br />
<br />
<br />
Bullwhip effect (also known as demand amplification, whip-saw, whiplash effect, or Forrester effect) refers to the phenomenon of demand variability amplification as moving up in the supply chain: from the point of actual (final) demand to the point of origin <ref>Lee H.L., Padmanabhan V. and Whang S. (1997) Information distortion in a supply chain: The bullwhip effect, Management Science; Apr 1997; 43, 4; pg. 546</ref>. It means that variability at the "end" of supply chain (closer to consumption, e. g. retailer) is much less, than at the other "end", where it begins (far from consumer, e. g. producer or supplier). Moving up in the supply chain from consumer to supplier increases demand variability. The more actors exist in a particular supply chain and the greater is [[lead time]], the greater demand variability would be. <br />
<br />
The first record of this phenomena belongs, probably, to J. Forrester <ref>Forrester J.W., (1961) Industrial dynamics. New York: MIT Press and John Wiley & Sons.</ref> (that is why it is possible to find in the literature references to "Forrester effect", although J. Forrester had never named it neither Forrester, nor bullwhip effect). The term "Forrester effect" used to denote what is now called demand signal processing, as Forrester was the first to demonstrate this phenomenon through dynamo simulation. In 1997, the phenomenon of bullwhip effect was popularized by Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref>. <br />
<br />
Bullwhip effect has quite negative impact on supply chain efficiency. It leads to excessive safety stock, higher production costs and overheads, potential final product quality distortions, poor customer service, lost sales, higher logistics costs, and so on. <br />
<br />
==Causes and Consequences of the Bullwhip Effect==<br />
Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref> identified four major causes of the bullwhip effect: <br />
<br />
*'''Demand forecast updating.''' Forecasting and production plans are often based on the order history from company's immediate customer. This immediate customer, however, rarely make exactly the same orders in short period of time as it received from its own immediate customer due to various reasons, including sales expectations, risk aversion, personal factors, production specifics, etc. As soon as manager see the change in downstream orders, he or she readjusts its own plans, however this order might not (and often not) reflect real demand situation. As a result, each member of supply chain makes a little bit different order from what it received and, finally, the supplier receives the order which is totally different from real market dynamics. This situation is very common, because if lead time is more, than 0 (and it is 0 only in electronic goods sales), it is not uncommon to have safety stocks. The higher lead times, the bigger safety stocks. These safety stocks on one hand are the cause of inefficiency In supply chain, because they require extra operation budget, and on the other hand, they increase the bullwhip effect itself. <br />
<br />
*'''Order batching.''' Orders usually accumulated in batches: periodic (daily, weekly, monthly, etc.) or push. Batches also increase the bullwhip effect. The reason for batches is different: from order processing costs (how much does the company spend on managing the orders) to transportation issues. Sometimes this effect is referred as Burbidge effect<ref>Burbidge J.L. (1991) Period Batch Control (PBC) with GT – the Way Forward from MRP, PBCIS Annual Conference, Birmingham, UK</ref>. Burbidge points out particular problems that this effect might cause shopkeepers unless duly watched. <br />
<br />
*'''Price fluctuation.''' Manufacturer or retailer often make different promotion programs (special discounts, price terms, rebates, etc.). These programs cause price fluctuations. As a result, customers see different price and react differently. For more information see [[http://scm.gsom.spbu.ru/EDLP EDLP]] <br />
<br />
*'''Rationing and shortage gaming.''' If producer is not able to fulfill the excessive demand in short period of time, and retailer (wholesaler or distributor) know about it, they will act to increase the orders to get at least something. For example, if retailer really needs 100 pieces of product and it knows that producer will fulfill only about 50% of the order, it will order 200. However, very often, 200 pieces is “the real picture” for the supplier and it make its strategic decisions basing on this information, however in the next period there might be only 100 (real) pieces in order from retailer. Behavioral psychology often resorts to the term bounded rationality implying sub-optimal but borderline rational decision making by actors<ref>Sterman J.D. (1989) Modeling managerial behavior: misperceptions of feedback in a dynamic<br />
decision making experiments. Management Science, 35 (3), p321–339</ref>. Rationing and gaming are sometimes referred to as the Houlihan effect after Houlihan<ref>Houlihan J. B. (1988) International supply chains : a new approach. Management Decisions. Vol. 26. p13-19.</ref>. This effect suggests that missed deliveries lead to higher safety stock levels and thus inflated orders. As more orders are made, the chain becomes more vulnerable to unreliable sources as reliable ones lack capacity to increase production instantly. All of this leads to bullwhip effect going up the supply chain with increasing magnitude. Houlihan described this process as the flywheel effect. Olsmats et al. (1988) demonstrated this phenomenon in action in the automotive sector. Price variation describes offering goods and services to consumers at lower prices through various promotions in order to boost immediate demand assuming elasticity<ref> Olsmats C. M., Edghill J. S. and Towill D. R. (1988) Industrial dynamics model building of a close-coupled production-distribution system. Engineering Costs & Production Economics, Vol. 13 Issue 4, p295-310, 16p</ref>.<br />
<br />
Some of researchers try to find origins of the bullwhip effect problems in psychology of manager, who takes a decision. Using modeling of bullwhip effect with a beer game, they prove that manager use one of two basic strategies: ‘safe harbor’ or ‘panic’, both of them have negative impact on the supply chain efficiency. However, as soon as there is a chance for negotiation, the results of simulation become much better <ref>Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online Production Planning & Control, Vol. 17, No. 6, 547–557</ref>. <br />
<br />
Particularly negative impacts of the bullwhip effect for the supply chain are:<br />
*'''Inefficient inventory management.''' The varying demand leads to variation in inventory levels at each tier of the supply chain. As supplier receives order, which is higher than the order on previous period, the company has to increase inventory level. On the other hand, if the order level is lower, it is not always possible to decrease inventory level in short period of time. The higher variability in demand (in orders), the higher safety stocks should be. Safety stock have trend to increase, as moving away from point of consumption. <br />
*'''Backlogged orders and poor service to product outlets.''' The safety stock that is required to ensure a sufficient service level increases with the variation in the demand, however, it is not always enough to fulfill excessive demand (orders). Hence, sometimes companies might face absence of goods on the shelves of the retailer. <br />
*'''Unpredictable production schedules.''' A variation in demand causes variation in capacity usage. During “high” period producer usually has to increase the number of shifts. During “low” period – to make extra safety stocks or leave workers without any work (both cases lead to financial losses).<br />
*'''High prices for raw materials because of immediate need.''' In case of emergent need of producing the order, producer often face a situation of absence of raw materials (of some of raw materials). Ordering even small part of raw materials from supplier on emergence will cost to producer enormously high price (at least for unscheduled transportation) . <br />
*'''Lost revenues.''' All these leads to financial losses: extra safety stocks (means more capital employed) or missed orders (missed sales). <br />
<br />
<br />
Analyses of recent papers shows that researchers do not argue about the causes and consequences of bullwhip effect, but try to find remedies for negative impact on the supply chain performance.<br />
<br />
==Example of the Bullwhip Effect==<br />
Usually consumption of most FMCG goods is stable. For instance, consumption of diapers by babies – is constant; consumption of bread, salt, ketchup and other food – constant, etc. Retailers very often see smooth demand with minor fluctuations as seen on the figure below. <br />
<br />
<lines size=500x200 title="Customer Sales" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,12<br />
2,11<br />
3,12<br />
4,13<br />
5,12<br />
6,13<br />
7,11<br />
8,13<br />
9,10<br />
10,13<br />
11,12<br />
12,13<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,10<br />
19,13<br />
20,13<br />
</lines><br />
<br />
----<br />
<br />
Making its own orders, however, retailer take in account own stock levels (from previous periods), sales expectations (including expectations on own advertising and promotion), discounts from manufacturer or distributor, the price of transportation, order processing and other minor factors. Orders are not that smooth any more. <br />
<br />
<lines size=500x200 title="Retailer's Orders to Wholesaler" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,11<br />
3,12<br />
4,14<br />
5,12<br />
6,14<br />
7,11<br />
8,14<br />
9,10<br />
10,14<br />
11,12<br />
12,14<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,9<br />
19,13<br />
20,14<br />
</lines><br />
<br />
----<br />
<br />
Orders from wholesaler to distributor are even more volatile due to the same reasons. <br />
<br />
<lines size=500x200 title="Wholesaler's Orders to Distributor" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,17<br />
3,10<br />
4,9<br />
5,17<br />
6,19<br />
7,12<br />
8,10<br />
9,16<br />
10,15<br />
11,17<br />
12,16<br />
13,9<br />
14,11<br />
15,10<br />
16,14<br />
17,9<br />
18,10<br />
19,17<br />
20,11<br />
</lines><br />
<br />
----<br />
<br />
At the end of supply chain, orders to manufacturer are even more variable. Manufacturer now has to solve problems of extra shifts or extra safety stock to fulfill all the orders. Extra costs and order failures are very common in this situation. <br />
<br />
<lines size=500x200 title="Distributor's Orders to Manufacturer" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,2<br />
2,19<br />
3,22<br />
4,12<br />
5,16<br />
6,7<br />
7,17<br />
8,20<br />
9,10<br />
10,14<br />
11,3<br />
12,20<br />
13,12<br />
14,8<br />
15,10<br />
16,21<br />
17,14<br />
18,6<br />
19,13<br />
20,19<br />
</lines><br />
----<br />
The bullwhip effect has been studied well and diagnosed as a significant problem in general <ref>Buzzell R. D., J. A. Quelch and W. J. Salmon (1990) The costly bargain of trade promotion. Harvard Business Review, 68, p141–148</ref>,<ref>Richard M. (1997) Quantifying the bullwhip effect in supply chains. Journal of Operations Management, Vol. 15 Issue 2, p89-100</ref>, as well as in particular companies or industries: <br />
<br />
*Hi-tech industry<ref>Kelly, K. 1995. Burned by busy signals: Why Motorola ramped up production way past demand. Business Week 6 36</ref><br />
*Grocery industry<ref>Holmstrom, J. 1997. Product range management: a case study of supply chain operations in the European grocery industry. Supply Chain Management 2(3) 107–115</ref><br />
*Manufacturing sector<ref> Dooley K., Yan T., Mohan S., Gopalakrishnan M. (2010) Inventory management and the bullwhip effect during the 2007–2009 recession: evidence from the manufacturing sector. Journal of Supply Chain Management, Vol. 46 Issue 1, p12-18 </ref><br />
* and other.<br />
<br />
==Analysis of the Bullwhip Effect==<br />
The bullwhip effect was analyzed by various researchers with different methods: <br />
*Simulation approach <ref> Wangphanich P., Kara S. and Kayis B. (2010) Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems-a simulation approach, International Journal of Production Research; Aug2010, Vol. 48 Issue 15, p4501-4517</ref><br />
*Evolutionary least-mean-square algorithm <ref>Tseng L-T., Tseng L-F., Chen H-C. (2011) Exploration of the bullwhip effect based on the evolutionary least-mean-square algorithm, International Journal of Electronic Business Management, Vol. 9 Issue 2, p160-168 </ref><br />
* Beer game simulation with different demand scenarios <ref> Matteo C., Chiara R., Tommaso R. and Fernanda S. (2010) Bullwhip effect and inventory oscillations analysis using the beer game model, International Journal of Production Research, Vol. 48 Issue 13, p3943-3956</ref><br />
*Multi-echelon supply chain system <ref> Xiao-Yuan, H. (2007) An H∞ control method of the bullwhip effect for a class of supply chain system. International Journal of Production Research, Vol. 45 Issue 1, p207-226</ref><br />
*Analytical approach<br />
<br />
==Bullwhip Effect Simulation (Beer Game)==<br />
[[File:beergame.png|thumb|Beergame illustration. Source: Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557]]<br />
<br />
Bullwhip Effect Simulation Game (Beer Game, also known as beer distribution game), which was developed by the Systems Dynamics Group at the Massachusetts Institute of Technology in the 1960s. It demonstrates the bullwhip effect by simulating a supply chain with four tiers: the retailer, the wholesaler, the distributor or the factory. It might be played in class or on-line and is very effective mean of illustrating systems thinking. By enabling managers to experience the negative impact of the bullwhip effect on supply chain performance, the beer game makes them aware of the application of countermeasures in their companies<rev> Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557</ref>.<br />
Each player takes the role (individually or in group of 2-3 players) one of the roles. An ultimate customer places orders at the retailer (buys beer). His demand is defined, but unknown to the participants. The ultimate demand is four units (bottles, packs of beer) during the first six periods (including “test” or “zero” period) and eight units during the following periods of the simulation. The game usually lasts for 50-70 period. It is enough to diagnose bullwhip effect. Each period represents one week. During this period participants have to make important decisions and activities in strict order:<br />
* Each player (team) receives order from their customer. For retailer it is pre-defined order (demand). For the rest of players it is orders from previous players (eg order from wholesaler for distributor). <br />
* Each player (team) makes a decision of how much to order. This decision is based on received order, on backlogged orders (all orders should be accomplished), on previous orders, on inventory left in stock and other factors. <br />
*Each player (team) has to minimize its costs. A product on stock (safety stock) costs $0.50 per product per period. Backlogged orders costs $1.00 per product per period (penalty for out-of-stock situations). Thus participants have to take into account a trade-off between minimizing the costs of capital employed in stocks on the one hand and avoiding of out-of-stock situations, on the other hand.<br />
Information flow (the information of how much to order) moves along supply chain with a delay of one week. It represents common situation in real companies. Good flow has a delay of two weeks due to transportation. Producer gets its orders from production after two weeks as well (to make it easier it is possible to say that one week is for production and one week is for quality control and packaging). <br />
Some important rules to remember: <br />
* Do not try to look for your demand before there is time to. <br />
* Do not change the sequence of steps. <br />
* Do not mix the orders and finished products. <br />
* It is possible to make 0 order. <br />
* If you missed the round, don’t try to catch-up. Make sure that all other members did it correctly.<br />
<br />
==Remedies for the Bullwhip Effect==<br />
Lee et al. (1997) proposed a framework for supply chain initiatives to deal with the bullwhip effect: information sharing, channel alignment, operational efficiency. It was criticized for general approach and since then a lot of papers on this topic, trying to find more general or more specific solutions: <br />
* Ordering policy<ref>Disney S.M. and Towill D.R., (2003) On the bullwhip and inventory variance produced by an<br />
ordering policy. Omega, 31 (3), 157–167</ref>,<ref>Kelle P. and Milne A. (1999) The effect of (s,S) ordering policy on the supply chain. International Journal of Production Economics, 59 (1–3), 113–122 </ref><br />
* Lot sizing rules <ref> Pujawan I.N. (2004) The effect of lot sizing rules on order variability. European Journal of<br />
Operations Research, 159 (3), 617–635</ref><br />
* Forecasting improvements<ref>Zhang X. (2005) Delayed demand information and dampened bullwhip effect. Operations Research<br />
Letters, 33 (3), 289–294</ref>,<ref>Zhao X. and Xie J. (2002) Forecasting errors and the value of information sharing in a supply chain. International Journal of Production Research, 40 (2), 311–335</ref>,<ref>Croson R. and Donohue K. (2005) Upstream versus downstream information and its impact on the bullwhip effect. System Dynamics Review, 21 (3), 249–260</ref>,<ref>Ingalls R.G., Foote B.L. and Krishnamoorthy A. (2005) Reducing the bullwhip effect in supply<br />
chains with control-based forecasting. International Journal of Simulation & Process Modelling, 1–2 (1), 90–110</ref><br />
* Decreasing demand variability <ref>Lin C. and Lin Y. (2006) Issues in the reduction of demand variance in the supply chain.<br />
International Journal of Production Research, 44 (9), 1821–1843</ref><br />
* Multi-agent approach <ref> Qing Cao and Leggio K. (2008) Alleviating the bullwhip effect in supply chain management using the multi-agent approach: an empirical study. International Journal of Computer Applications in Technology, Vol. 31 Issue 3/4, p225-237</ref><br />
Information sharing is one of the most important tools for minimizing bullwhip effect. Most of contemporary tools and approaches, including [[VMI]], [[CPFR]], etc. and technical innovations, such as [[RFID]] use this principle. The importance of information in supply chains: <br />
*Helps reduce variability in supply chains <br />
*Help suppliers make better forecast <br />
*Enables the coordination system of manufacturing and distribution systems and strategies <br />
*Enables retailers to better serve their customers<br />
*Enables retailers to react and adapt to supply chain problems more rapidly <br />
*Enables lead time reductions<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Bullwhip_effectBullwhip effect2011-08-21T00:21:14Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Эффект_хлыста Эффект хлыста]'''<br />
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[[File:Bullwhip effect.png|thumb|Illustration of the bullwhip effect: the ultimate customer places an order (whip) and order fluctuations build up upstream the [[supply chain]].]]<br />
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<br />
Bullwhip effect (also known as demand amplification, whip-saw, whiplash effect, or Forrester effect) refers to the phenomenon of demand variability amplification as moving up in the supply chain: from the point of actual (final) demand to the point of origin <ref>Lee H.L., Padmanabhan V. and Whang S. (1997) Information distortion in a supply chain: The bullwhip effect, Management Science; Apr 1997; 43, 4; pg. 546</ref>. It means that variability at the "end" of supply chain (closer to consumption, e. g. retailer) is much less, than at the other "end", where it begins (far from consumer, e. g. producer or supplier). Moving up in the supply chain from consumer to supplier increases demand variability. The more actors are in a particular supply chain and the greater is [[lead time]], the greater demand variability would be. <br />
<br />
The first record on this phenomena belongs, probably, to J. Forrester <ref>Forrester J.W., (1961) Industrial dynamics. New York: MIT Press and John Wiley & Sons.</ref> (that is why in some literature it is possible to find refers to Forrester effect, however J. Forrester never named it neither Forrester, nor bullwhip effect). The term Forrester effect used to denote what is now called demand signal processing, as Forrester was the first to demonstrate this factor through dynamo simulation. In 1997, the phenomena of bullwhip effect was popularized by Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref>. <br />
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Bullwhip effect has a very negative impact on supply chain efficiency. It leads to excessive stock inventories, increased production costs and overheads, potential quality distortions, worse customer support, foregone sales, increased logistics costs and so on. <br />
<br />
==Causes and Consequences of the Bullwhip Effect==<br />
Lee et al.<ref>Lee H.L., Padmanabhan V. and Whang S. (1997) The bullwhip effect in supply chains. Sloan Management Review 38(3) p93–102</ref> identified four major causes of the bullwhip effect: <br />
<br />
*'''Demand forecast updating.''' Forecasting and production plans are often based on the order history from company's immediate customer. This immediate customer, however, rarely make exactly the same orders in short period of time as it received from its own immediate customer due to various reasons, including sales expectations, risk aversion, personal factors, production specifics, etc. As soon as manager see the change in downstream orders, he or she readjusts its own plans, however this order might not (and often not) reflect real demand situation. As a result, each member of supply chain makes a little bit different order from what it received and, finally, the supplier receives the order which is totally different from real market dynamics. This situation is very common, because if lead time is more, than 0 (and it is 0 only in electronic goods sales), it is not uncommon to have safety stocks. The higher lead times, the bigger safety stocks. These safety stocks on one hand are the cause of inefficiency In supply chain, because they require extra operation budget, and on the other hand, they increase the bullwhip effect itself. <br />
<br />
*'''Order batching.''' Orders usually accumulated in batches: periodic (daily, weekly, monthly, etc.) or push. Batches also increase the bullwhip effect. The reason for batches is different: from order processing costs (how much does the company spend on managing the orders) to transportation issues. Sometimes this effect is referred as Burbidge effect<ref>Burbidge J.L. (1991) Period Batch Control (PBC) with GT – the Way Forward from MRP, PBCIS Annual Conference, Birmingham, UK</ref>. Burbidge points out particular problems that this effect might cause shopkeepers unless duly watched. <br />
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*'''Price fluctuation.''' Manufacturer or retailer often make different promotion programs (special discounts, price terms, rebates, etc.). These programs cause price fluctuations. As a result, customers see different price and react differently. For more information see [[http://scm.gsom.spbu.ru/EDLP EDLP]] <br />
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*'''Rationing and shortage gaming.''' If producer is not able to fulfill the excessive demand in short period of time, and retailer (wholesaler or distributor) know about it, they will act to increase the orders to get at least something. For example, if retailer really needs 100 pieces of product and it knows that producer will fulfill only about 50% of the order, it will order 200. However, very often, 200 pieces is “the real picture” for the supplier and it make its strategic decisions basing on this information, however in the next period there might be only 100 (real) pieces in order from retailer. Behavioral psychology often resorts to the term bounded rationality implying sub-optimal but borderline rational decision making by actors<ref>Sterman J.D. (1989) Modeling managerial behavior: misperceptions of feedback in a dynamic<br />
decision making experiments. Management Science, 35 (3), p321–339</ref>. Rationing and gaming are sometimes referred to as the Houlihan effect after Houlihan<ref>Houlihan J. B. (1988) International supply chains : a new approach. Management Decisions. Vol. 26. p13-19.</ref>. This effect suggests that missed deliveries lead to higher safety stock levels and thus inflated orders. As more orders are made, the chain becomes more vulnerable to unreliable sources as reliable ones lack capacity to increase production instantly. All of this leads to bullwhip effect going up the supply chain with increasing magnitude. Houlihan described this process as the flywheel effect. Olsmats et al. (1988) demonstrated this phenomenon in action in the automotive sector. Price variation describes offering goods and services to consumers at lower prices through various promotions in order to boost immediate demand assuming elasticity<ref> Olsmats C. M., Edghill J. S. and Towill D. R. (1988) Industrial dynamics model building of a close-coupled production-distribution system. Engineering Costs & Production Economics, Vol. 13 Issue 4, p295-310, 16p</ref>.<br />
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Some of researchers try to find origins of the bullwhip effect problems in psychology of manager, who takes a decision. Using modeling of bullwhip effect with a beer game, they prove that manager use one of two basic strategies: ‘safe harbor’ or ‘panic’, both of them have negative impact on the supply chain efficiency. However, as soon as there is a chance for negotiation, the results of simulation become much better <ref>Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online Production Planning & Control, Vol. 17, No. 6, 547–557</ref>. <br />
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Particularly negative impacts of the bullwhip effect for the supply chain are:<br />
*'''Inefficient inventory management.''' The varying demand leads to variation in inventory levels at each tier of the supply chain. As supplier receives order, which is higher than the order on previous period, the company has to increase inventory level. On the other hand, if the order level is lower, it is not always possible to decrease inventory level in short period of time. The higher variability in demand (in orders), the higher safety stocks should be. Safety stock have trend to increase, as moving away from point of consumption. <br />
*'''Backlogged orders and poor service to product outlets.''' The safety stock that is required to ensure a sufficient service level increases with the variation in the demand, however, it is not always enough to fulfill excessive demand (orders). Hence, sometimes companies might face absence of goods on the shelves of the retailer. <br />
*'''Unpredictable production schedules.''' A variation in demand causes variation in capacity usage. During “high” period producer usually has to increase the number of shifts. During “low” period – to make extra safety stocks or leave workers without any work (both cases lead to financial losses).<br />
*'''High prices for raw materials because of immediate need.''' In case of emergent need of producing the order, producer often face a situation of absence of raw materials (of some of raw materials). Ordering even small part of raw materials from supplier on emergence will cost to producer enormously high price (at least for unscheduled transportation) . <br />
*'''Lost revenues.''' All these leads to financial losses: extra safety stocks (means more capital employed) or missed orders (missed sales). <br />
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Analyses of recent papers shows that researchers do not argue about the causes and consequences of bullwhip effect, but try to find remedies for negative impact on the supply chain performance.<br />
<br />
==Example of the Bullwhip Effect==<br />
Usually consumption of most FMCG goods is stable. For instance, consumption of diapers by babies – is constant; consumption of bread, salt, ketchup and other food – constant, etc. Retailers very often see smooth demand with minor fluctuations as seen on the figure below. <br />
<br />
<lines size=500x200 title="Customer Sales" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,12<br />
2,11<br />
3,12<br />
4,13<br />
5,12<br />
6,13<br />
7,11<br />
8,13<br />
9,10<br />
10,13<br />
11,12<br />
12,13<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,10<br />
19,13<br />
20,13<br />
</lines><br />
<br />
----<br />
<br />
Making its own orders, however, retailer take in account own stock levels (from previous periods), sales expectations (including expectations on own advertising and promotion), discounts from manufacturer or distributor, the price of transportation, order processing and other minor factors. Orders are not that smooth any more. <br />
<br />
<lines size=500x200 title="Retailer's Orders to Wholesaler" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,11<br />
3,12<br />
4,14<br />
5,12<br />
6,14<br />
7,11<br />
8,14<br />
9,10<br />
10,14<br />
11,12<br />
12,14<br />
13,12<br />
14,11<br />
15,10<br />
16,13<br />
17,12<br />
18,9<br />
19,13<br />
20,14<br />
</lines><br />
<br />
----<br />
<br />
Orders from wholesaler to distributor are even more volatile due to the same reasons. <br />
<br />
<lines size=500x200 title="Wholesaler's Orders to Distributor" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,13<br />
2,17<br />
3,10<br />
4,9<br />
5,17<br />
6,19<br />
7,12<br />
8,10<br />
9,16<br />
10,15<br />
11,17<br />
12,16<br />
13,9<br />
14,11<br />
15,10<br />
16,14<br />
17,9<br />
18,10<br />
19,17<br />
20,11<br />
</lines><br />
<br />
----<br />
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At the end of supply chain, orders to manufacturer are even more variable. Manufacturer now has to solve problems of extra shifts or extra safety stock to fulfill all the orders. Extra costs and order failures are very common in this situation. <br />
<br />
<lines size=500x200 title="Distributor's Orders to Manufacturer" ymin=0 ymax=25 colors=2D00B8 xlabel ylabel=5 grid=xy legend><br />
, Order Quantity<br />
1,2<br />
2,19<br />
3,22<br />
4,12<br />
5,16<br />
6,7<br />
7,17<br />
8,20<br />
9,10<br />
10,14<br />
11,3<br />
12,20<br />
13,12<br />
14,8<br />
15,10<br />
16,21<br />
17,14<br />
18,6<br />
19,13<br />
20,19<br />
</lines><br />
----<br />
The bullwhip effect has been studied well and diagnosed as a significant problem in general <ref>Buzzell R. D., J. A. Quelch and W. J. Salmon (1990) The costly bargain of trade promotion. Harvard Business Review, 68, p141–148</ref>,<ref>Richard M. (1997) Quantifying the bullwhip effect in supply chains. Journal of Operations Management, Vol. 15 Issue 2, p89-100</ref>, as well as in particular companies or industries: <br />
<br />
*Hi-tech industry<ref>Kelly, K. 1995. Burned by busy signals: Why Motorola ramped up production way past demand. Business Week 6 36</ref><br />
*Grocery industry<ref>Holmstrom, J. 1997. Product range management: a case study of supply chain operations in the European grocery industry. Supply Chain Management 2(3) 107–115</ref><br />
*Manufacturing sector<ref> Dooley K., Yan T., Mohan S., Gopalakrishnan M. (2010) Inventory management and the bullwhip effect during the 2007–2009 recession: evidence from the manufacturing sector. Journal of Supply Chain Management, Vol. 46 Issue 1, p12-18 </ref><br />
* and other.<br />
<br />
==Analysis of the Bullwhip Effect==<br />
The bullwhip effect was analyzed by various researchers with different methods: <br />
*Simulation approach <ref> Wangphanich P., Kara S. and Kayis B. (2010) Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems-a simulation approach, International Journal of Production Research; Aug2010, Vol. 48 Issue 15, p4501-4517</ref><br />
*Evolutionary least-mean-square algorithm <ref>Tseng L-T., Tseng L-F., Chen H-C. (2011) Exploration of the bullwhip effect based on the evolutionary least-mean-square algorithm, International Journal of Electronic Business Management, Vol. 9 Issue 2, p160-168 </ref><br />
* Beer game simulation with different demand scenarios <ref> Matteo C., Chiara R., Tommaso R. and Fernanda S. (2010) Bullwhip effect and inventory oscillations analysis using the beer game model, International Journal of Production Research, Vol. 48 Issue 13, p3943-3956</ref><br />
*Multi-echelon supply chain system <ref> Xiao-Yuan, H. (2007) An H∞ control method of the bullwhip effect for a class of supply chain system. International Journal of Production Research, Vol. 45 Issue 1, p207-226</ref><br />
*Analytical approach<br />
<br />
==Bullwhip Effect Simulation (Beer Game)==<br />
[[File:beergame.png|thumb|Beergame illustration. Source: Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557]]<br />
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Bullwhip Effect Simulation Game (Beer Game, also known as beer distribution game), which was developed by the Systems Dynamics Group at the Massachusetts Institute of Technology in the 1960s. It demonstrates the bullwhip effect by simulating a supply chain with four tiers: the retailer, the wholesaler, the distributor or the factory. It might be played in class or on-line and is very effective mean of illustrating systems thinking. By enabling managers to experience the negative impact of the bullwhip effect on supply chain performance, the beer game makes them aware of the application of countermeasures in their companies<rev> Nienhaus J., Ziegenbein A. and Schoensleben P. (2006) How human behavior amplifies the bullwhip effect. A study based on the beer distribution game online, Production Planning & Control, Vol. 17, No. 6, p.547–557</ref>.<br />
Each player takes the role (individually or in group of 2-3 players) one of the roles. An ultimate customer places orders at the retailer (buys beer). His demand is defined, but unknown to the participants. The ultimate demand is four units (bottles, packs of beer) during the first six periods (including “test” or “zero” period) and eight units during the following periods of the simulation. The game usually lasts for 50-70 period. It is enough to diagnose bullwhip effect. Each period represents one week. During this period participants have to make important decisions and activities in strict order:<br />
* Each player (team) receives order from their customer. For retailer it is pre-defined order (demand). For the rest of players it is orders from previous players (eg order from wholesaler for distributor). <br />
* Each player (team) makes a decision of how much to order. This decision is based on received order, on backlogged orders (all orders should be accomplished), on previous orders, on inventory left in stock and other factors. <br />
*Each player (team) has to minimize its costs. A product on stock (safety stock) costs $0.50 per product per period. Backlogged orders costs $1.00 per product per period (penalty for out-of-stock situations). Thus participants have to take into account a trade-off between minimizing the costs of capital employed in stocks on the one hand and avoiding of out-of-stock situations, on the other hand.<br />
Information flow (the information of how much to order) moves along supply chain with a delay of one week. It represents common situation in real companies. Good flow has a delay of two weeks due to transportation. Producer gets its orders from production after two weeks as well (to make it easier it is possible to say that one week is for production and one week is for quality control and packaging). <br />
Some important rules to remember: <br />
* Do not try to look for your demand before there is time to. <br />
* Do not change the sequence of steps. <br />
* Do not mix the orders and finished products. <br />
* It is possible to make 0 order. <br />
* If you missed the round, don’t try to catch-up. Make sure that all other members did it correctly.<br />
<br />
==Remedies for the Bullwhip Effect==<br />
Lee et al. (1997) proposed a framework for supply chain initiatives to deal with the bullwhip effect: information sharing, channel alignment, operational efficiency. It was criticized for general approach and since then a lot of papers on this topic, trying to find more general or more specific solutions: <br />
* Ordering policy<ref>Disney S.M. and Towill D.R., (2003) On the bullwhip and inventory variance produced by an<br />
ordering policy. Omega, 31 (3), 157–167</ref>,<ref>Kelle P. and Milne A. (1999) The effect of (s,S) ordering policy on the supply chain. International Journal of Production Economics, 59 (1–3), 113–122 </ref><br />
* Lot sizing rules <ref> Pujawan I.N. (2004) The effect of lot sizing rules on order variability. European Journal of<br />
Operations Research, 159 (3), 617–635</ref><br />
* Forecasting improvements<ref>Zhang X. (2005) Delayed demand information and dampened bullwhip effect. Operations Research<br />
Letters, 33 (3), 289–294</ref>,<ref>Zhao X. and Xie J. (2002) Forecasting errors and the value of information sharing in a supply chain. International Journal of Production Research, 40 (2), 311–335</ref>,<ref>Croson R. and Donohue K. (2005) Upstream versus downstream information and its impact on the bullwhip effect. System Dynamics Review, 21 (3), 249–260</ref>,<ref>Ingalls R.G., Foote B.L. and Krishnamoorthy A. (2005) Reducing the bullwhip effect in supply<br />
chains with control-based forecasting. International Journal of Simulation & Process Modelling, 1–2 (1), 90–110</ref><br />
* Decreasing demand variability <ref>Lin C. and Lin Y. (2006) Issues in the reduction of demand variance in the supply chain.<br />
International Journal of Production Research, 44 (9), 1821–1843</ref><br />
* Multi-agent approach <ref> Qing Cao and Leggio K. (2008) Alleviating the bullwhip effect in supply chain management using the multi-agent approach: an empirical study. International Journal of Computer Applications in Technology, Vol. 31 Issue 3/4, p225-237</ref><br />
Information sharing is one of the most important tools for minimizing bullwhip effect. Most of contemporary tools and approaches, including [[VMI]], [[CPFR]], etc. and technical innovations, such as [[RFID]] use this principle. The importance of information in supply chains: <br />
*Helps reduce variability in supply chains <br />
*Help suppliers make better forecast <br />
*Enables the coordination system of manufacturing and distribution systems and strategies <br />
*Enables retailers to better serve their customers<br />
*Enables retailers to react and adapt to supply chain problems more rapidly <br />
*Enables lead time reductions<br />
<br />
==References==<br />
<references /><br />
<br />
KK<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Load-planning_problemLoad-planning problem2011-08-20T23:05:13Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Задача_о_загрузке_самолета Задача о загрузке самолета]'''<br />
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Description of the problem and its solution are based on the method of dynamic programming and Bellman's optimality principle.<br />
<br />
==Dynamic programming method==<br />
<br />
Dynamic programming is widely used in optimal control and planning problems as well as various technical problems. <br />
<br />
Suppose that the process of control of a system <math>\, X </math> goes <math> \, n </math> steps. Given a state space <math>\, P </math> and control space <math>\, Q </math> with elements <math>\, p </math> and <math>\, q </math> respectively. It is assumed that the initial state <math>\, p_0 </math> is known. Consider a function <math> \, T </math>:<br />
<br />
<math>\, P\times Q\to P</math>, i.e. <math>\, T(p,q)=p',\, \, \, (p,q)\in P\times Q,\, \, p'\in P</math>.<br />
<br />
Function <math> \, T </math> is often referred to as a function of dynamics of the controlled process.<br />
<br />
Multi-step guided process is realized as follows (see Fig. 1.)<br />
<br />
'''Step 1'''. The system is in the state <math> \, p_ {0} \ in P </math>. In this state the following control is used <math> \, q_ {1} \ in Q </math>. Mapping <math> \, T </math> sets the system into a new state <math> \, T (p_ {0}, q_ {1}) = p_ {1} </math>.<br />
<br />
'''Step 2'''. The system is in the state <math> \, p_ {1} \ in P </math>. In this state the following control is used <math> \, q_ {2} \ in Q </math> so <math> \, T (p_ {1}, q_ {2}) = p_ {2} </math>.<br />
<br />
'''Step ''k''''. The system is in the state <math>\,p_{k-1} \in P</math>. In this state the following control is used <math>\,q_{k} \in Q </math>, then <math>\,T(p_{k-1} ,q_{k} )=p_{k} </math>.<br />
<br />
'''Step''n'''''. The system <math>\,X </math> is in the state <math>\, p_{n-1} \in P </math>. When the control <math>\,q_{n} \in Q </math> is chosen we have <math>\,T(p_{n-1} ,q_{n} )=p_{n} </math>. The process ends.<br />
<br />
[[File:zPic51.jpg]]<br />
<br />
'''Fig. 1. The implementation of the multi-step control process.'''<br />
<br />
We denote <math>\, q = (q_ {1} ,..., q_ {k} ,..., q_ {n}), \, \, \, \, q_ {k} \ in Q, \, \, \, \, k = \overline {1, n} </math> - multistep control process. Then this initial state <math> \, p_ {0} </math> and control <math> \, q </math> corresponds to a trajectory <math> \, p = (p_ {0} ,..., p_ {k-1}, p_ {k}, p_ {k +1} ,..., p_ {n}) </math>, where <math> \, p_ {k} = T (p_ {k-1} , q_ {k}) </math>, <math> \, k = \overline {1, n} </math>.<br />
<br />
Assume that on control <math> \, q </math> and trajectory <math> \, p </math> is given an additive function:<br />
<br />
<math>\, \bar{K}(p,q)=f_{1} (p_{0} ,q_{1} )+...+f_{i} (p_{i-1} ,q_{i} )+...+f_{n} (p_{n-1} ,q_{n} )+f_{n+1} (p_{n} )= \sum _{i=1}^{n}f_{i} (p_{i-1} ,q_{i} ) +f_{n+1} (p_{n} ) </math>.<br />
<br />
Denote<br />
<br />
<math>\, K(p_{0} ,q)=\sum _{i=1}^{n}f_{i} (p_{i-1} ,q_{i} ) +f_{n+1} (p_{n} )</math>.<br />
<br />
value of the function <math> \, \ bar {K} (p, q) </math> on the trajectory of the process from the initial state <math> \, p_ {0} </math> in <math> \, q </math>.<br />
<br />
Now we can formulate the ''discrete optimal control'' problem. Find the optimal control <math> \, q ^ {*} </math>, which is the solution of the following problem:<br />
<br />
<math>\, \mathop{\max }\limits_{q} K(p_{0} ,q)=\max \left[\sum _{i=1}^{n}f_{i} (p_{i-1} ,q_{i} ) +f_{n+1} (p_{n} )\right]</math>.<br />
<br />
under dynamic constraints:<br />
<br />
<math>\, \left\{\begin{array}{l} {p_{i} =T(p_{i-1} ,q_{i} ),\, \, \, q_{i} \in Q,\, \, \, i=\overline{1,n}} \\ {p_{0} =p^{0}} \end{array}\right. </math> <br />
<br />
where <math>\, p_{0} </math> - given initial state of the process.<br />
<br />
Note that when the control <math> \, q_ {i} </math> is being choosing in step <math> \, i </math> we know the state of the process <math> \, p_ {i-1} </math> in the previous step, and the knowledge of <math> \, (p_ {i-1}, q_ {i}) </math> defines the future state of the process and the value of the functional. It is therefore natural to consider functions <math> \, q_ {i} = q_ {i} (p_ {i-1}) </math>, <math> \, i = \overline {1, n} </math> and set of functions<br />
<br />
(1) <math>\, q(\cdot )=(q_{1} (\cdot ),...,q_{k} (\cdot ),...,q_{n} (\cdot )) </math><br />
<br />
where <math>\,q_{k} (\cdot ): q_{k} =q_{k} (p_{k-1} ) </math>. Such set of functions <math>\,q(\cdot ) </math> is called a strategy.<br />
<br />
== Bellman's optimality principle.==<br />
<br />
''Optimal strategy''<br />
<br />
<math>\, q^{*} (\cdot )=(q_{1}^{*} (\cdot ),...,q_{k}^{*} (\cdot ),...,q_{n}^{*} (\cdot )) </math><br />
<br />
has the property that whatever the initial state <math> \, p </math> and the initial control is chosen <math> \, q_ {1} </math>, it remains the best strategy in the process with <math> \, n-1 </math> steps, which starts at the state <math> \, p_ {1} = T (p, q) </math>.<br />
<br />
From Bellman's optimality principle can be derived recurrence ''functional'' Bellman equation, which is the basis of computational procedures for dynamic programming.<br />
<br />
Denote <math> \, F_n (p) </math> - the maximum functional value in <math> \, n </math> - steps problem from the initial state <math> \, p </math>. Function <math> \, F_n (p) </math> is often called the ''Bellman’s function''. From the principle of optimality we have the following equation.<br />
<br />
'''The Bellman equation.'''<br />
<br />
(2) <math>\, F_{n} (p)=\mathop{\max }\limits_{q_{1} \in Q} [f_{1} (p,q_{1} )+F_{n-1} (T(p,q_{1} )) </math><br />
<br />
with the boundary condition<br />
<br />
<math>\, F_{0} (p)=f_{n+1} (p). </math><br />
<br />
'''The general scheme of dynamic programming'''<br />
<br />
Consider the idea of dynamic programming in the following example. Find:<br />
<br />
(3) <math>\, \mathop{\max }\limits_{x_{1} ...x_{n} } \sum _{j=1}^{n}f_{j} (x_{j} )</math>, <br />
<br />
<math>\, x_{j} \ge 0</math>, <math>\,x_{j} </math> - integer, <math>\,j=\overline{1,n}</math>.<br />
<br />
Because the variables <math> \, x_ {j} </math>, <math> \, j = \overline {1, n} </math> are independent, then<br />
<br />
<math>\, \mathop{\max }\limits_{x_{1} ,...,x_{n} } \sum _{j=1}^{n}f_{j} (x_{j} ) =\mathop{\max }\limits_{x_{n} } \left[f_{n} (x_{n} )+\mathop{\max }\limits_{x_{1} ,...,x_{n-1} } \sum _{j=1}^{n-1}f_{j} (x_{j} ) \right]</math>, <br />
<br />
(4) <math>\, \sum _{j=1}^{n-1}a_{j} x_{j} \le b-a_{n} x_{n} </math><br />
<br />
Denote <math> \, \mathop {\ max} \ limits_ {x_ {1} ,..., x_ {n-1}} \ sum _ {j = 1} ^ {n} f_ {j} (x_ {j}) </math> in the condition (4) through <math> \, F_ {n-1} (b-a_ {n} x_ {n}) </math>, then<br />
<br />
(6) <math>\, \mathop{\max }\limits_{x_{1} ,...,x_{n} } \sum _{j=1}^{n}f_{j} (x_{j} ) =\mathop{\max }\limits_{x_{n} } \left[f_{n} (x_{n} )+F_{n-1} (b-a_{n} x_{n} )\right] </math> <br />
<br />
Denote <math>\, \mathop{\max }\limits_{x_{1} ,...,x_{k} } \sum _{j=1}^{k}f_{j} (x_{j} ) =F_{k} (\xi ) </math> under condition<br />
<math>\, \sum _{j=1}^{k}a_{j} x_{j} \le \xi </math>.<br />
<br />
<math>\, x_{j} \ge 0 </math>, <math>\,x_{j} </math> - integer, <math>\,j=\overline{1,n}</math>.<br />
<br />
After transformations we obtain the following fundamental recurrence relation of dynamic programming<br />
<br />
(7) <math>\, F_{k} (\xi )=\mathop{\max }\limits_{x_{k} } \left[f_{k} (x_{k} )+F_{n-1} (\xi -a_{n} x_{n} )\right],\, \, \, k=\overline{1,n} </math><br />
<br />
subject to <math>\,0\le x_{k} \le \frac{\xi }{a_{k} } </math> .<br />
<br />
Use (7) to define calculation process:<br />
<br />
'''Construction of Bellman’s function'''.<br />
<br />
'''Step 1'''. Compute<br />
<br />
(8) <math>\,F_{1} (\xi )=\mathop{\max }\limits_{x_{1} } f_{1} (x_{1} ),\, \, \, x_{1} \le \xi </math>, <br />
<br />
where <math>\,\xi =\overline{0,b}</math> - a parameter of the process. Fill the table 1 by values <math>\,F_{1} (\xi ) </math> , <math>\,x_{1}^{0} (\xi )</math>, for <math>\,\xi =\overline{0,b}</math> <math>\,x_{1}^{0} (\xi )</math> - optimal solution of the problem (8).<br />
<br />
'''Step 2'''. Compute<br />
<br />
(9) <math>\, F_{2}(\xi )=\mathop{\max }\limits_{0\le x_{2} \le \frac{\xi }{a_{2}}} \left[f_{2}(x_{2})+F_{1}(\xi-a_{2} x_{2})\right] </math> <br />
<br />
Values <math> \, F_ {1} (\ xi-a_ {2} x_ {2}) </math> for different values of the argument <math> \, \ xi-a_ {2} x_ {2} </math > select from Table. 1. Fill in the table 2 with the following results: <math> \, F_ {2} (\ xi) </math>, <math> \, x_ {2} ^ {0} (\ xi) </math>, where <math> \, x_ {2} ^ {0} (\ xi) </math> - the optimal solution of problem (9).<br />
<br />
''' Step ''k'''''. <math>\,(1\le k\le n-1)</math>. Compute<br />
<br />
(10) <math>\, F_{k}(\xi )=\mathop{\max }\limits_{0\le x_{k} \le \frac{\xi}{a_{k}}} \left[f_{k}(x_{k})+F_{k-1}(\xi-a_{k}x_{k})\right] </math> <br />
<br />
Fill in the table of values <math> \, F_ {k} (\ xi) </math>, <math> \, x_ {k} ^ {0} (\ xi) </math>, <math> \, \ xi = \overline {0, b} </math>, where <math> \, x_ {k} ^ {0} (\ xi) </math> - the optimal solution of problem (10).<br />
<br />
'''Optimal solution computation'''.<br />
<br />
Assuming <math> \, \ xi = b </math> and <math> \, k = n </math> find <math> \, F_ {n} (b) </math> and <math> \, x_ {n} ^ {0} = x_ {n} ^ {0} (\ xi) </math>.<br />
<br />
<br />
Calculate in (10) the optimal value <math> \, x_ {n} ^ {0} = x_ {n} ^ {0} (\ xi) </math> and assume <math> \, \ xi_ {1}, {0} = b-a_ {n} x_ {n} ^ {0} </math>. Then, using the value of <math>\, \ xi _ {1} ^ {0} </math> of the table step <math> \, n-1 </math>, determine the optimal values of other variables <math> \, x_ {n-1} ^ {0} (\ xi _ {1} ^ {0}) </math>. Then determine the values <math> \, x_ {n-2} ^ {0} (\ xi_ {1} ^ {0}), \ dots, x_ {1} ^ {0} (\ xi _ {1} ^ {0}) </math>.<br />
<br />
{| border="1"<br />
| align="center" | <math>\,\xi </math>|| align="center" | <math>\,F_{1}(\xi)</math> || align="center" | <math>x_{1}^{0} (\xi )</math><br />
|-<br />
| align="center" |<math>\, 0 </math> || align="center" | <math>\, F_{1}(0)</math> || align="center" | <math>\, x_{1}^{0}(0)</math><br />
|-<br />
| align="center" |<math>\, 1 </math> || align="center" | <math>\, F_{1}(1)</math> || align="center" | <math>\, x_{1}^{0}(1)</math><br />
|-<br />
| align="center" | <math>\, \ldots </math>|| align="center" | <math>\, \ldots </math> || align="center" | <math>\, \ldots </math><br />
|-<br />
| align="center" | <math>\, b-1 </math> || align="center" | <math>\, F_{1} (b-1) </math> || align="center" | <math>\, x_{1}^{0} (b-1)</math><br />
|-<br />
| align="center" | <math>\, b </math> || align="center" | <math>\, F_{1} (b)</math> || align="center" | <math>\,x_{1}^{0}(b)</math><br />
|}<br />
<br />
''Table 1. Table for the first iteration''<br />
{| border="1"<br />
| align="center" | <math>\,\xi</math>|| align="center" | <math>\,F_{2}(\xi )</math> || align="center" | <math>\, x_{2}^{0}(\xi)</math><br />
|-<br />
| align="center" |<math>\, 0 </math> || align="center" | <math>\, F_{2}(0)</math> || align="center" | <math>\, x_{2}^{0}(0)</math><br />
|-<br />
| align="center" |<math>\, 1 </math> || align="center" | <math>\, F_{2}(1)</math> || align="center" | <math>\, x_{2}^{0}(1)</math><br />
|-<br />
| align="center" | <math>\, \ldots </math>|| align="center" | <math>\, \ldots </math> || align="center" | <math>\, \ldots </math><br />
|-<br />
| align="center" | <math>\, b-1 </math> || align="center" | <math>\, F_{2} (b-1) </math> || align="center" | <math>\, x_{2}^{0} (b-1)</math><br />
|-<br />
| align="center" | <math>\, b </math> || align="center" | <math>\, F_{2} (b)</math> || align="center" | <math>\,x_{2}^{0}(b)</math><br />
|}<br />
<br />
''Table 2. Table for the second iteration''<br />
<br />
To apply dynamic programming method the following conditions are to be satisfied:<br />
<br />
* The decision-making process should allow an interpretation as a multi-step process;<br />
<br />
* For each step it should be defined a set of state parameters <math> \, \ xi </math>, which do not depend on the number of steps;<br />
<br />
* Optimal solution in step <math> \, k </math> depends only on the current state and does not depend on the prehistory of the process.<br />
<br />
==Aircraft Loading Problem==<br />
<br />
An aircraft is loaded by objects <math> \, N </math> of various types. Each object type <math> \, i </math> has weight <math> \, F_ {i} </math> and insurance cost <math> \, v_ {i} </math>, (<math> \ , i = \overline {1, N} </math>). Maximum load capacity of the aircraft is <math> \, W </math>. It is required to determine the maximum value of the goods whose weight must not exceed maximum permissible carrying capacity of aircraft. For definiteness, assume that <math> \, W = 5 </math> and there are three types of objects, details of which are listed in the table below:<br />
{| border="1"<br />
| align="center" | <math>\, \, \, \, i \, \, \, </math>|| align="center" | <math>\, \, \, \, F_{i}\, \, \, </math> || align="center" | <math>\, \, \, \, v_{i} \, \, \, </math><br />
|-<br />
| align="center" |<math>\, 1 </math> || align="center" | <math>\, 2 </math> || align="center" | <math>\, 65 </math><br />
|-<br />
| align="center" |<math>\, 2 </math> || align="center" | <math>\, 3 </math> || align="center" | <math>\, 80 </math><br />
|-<br />
| align="center" | <math>\, 3 </math>|| align="center" | <math>\, 1 </math> || align="center" | <math>\, 30 </math><br />
|}<br />
<br />
Consider the problem in general formulation. Denote the number of items such as <math> \, i </math> by <math> \, k_ {i} </math>. Then the problem of loading the aircraft can be written as:<br />
<br />
<math>\, \max z=\max (v_{1} k_{1} +v_{2} k_{2} +...+v_{N} k_{N} ) </math><br />
<br />
<math>\, \left\{\begin{array}{l} {F_{1} k_{1} +F_{2} k_{2} +...+F_{n} k_{n} \le W,} \\ {k\ge 0,\, \, i=\overline{1,N,}} \end{array}\right. </math> <br />
<br />
where <math>\, k </math> are integer.<br />
<br />
If it were possible to discard the requirement of integrality, it was a linear programming problem and it could be solved with the simplex method.<br />
<br />
Consider three main elements of a dynamic model.<br />
<br />
'''1.''' Step <math> \, j </math> is associated with type <math> \, j, j = 1,2 ,..., </math><br />
<br />
'''2.''' State <math> \, y_j </math> on stage <math> \, j </math> is the total weight of items, loaded on the previous stages <math> \, j, j + 1, \ dots, \ textit {N} </math>. The variable <math> \, y_j </math> can be <math> \, 0,1, \ dots, W </math> in <math> \, j = 1,2, \ dots, N </math>.<br />
<br />
'''3.''' Solutions. Values <math> \, k_ {j} </math> on stage <math> \, j </math> describe the type of items <math> \, j </math>. Value <math> \, k_ {j} \ in [0, [W / F_ {j}]] </math>, where <math> \, [W / F_ {j}] </math> is the integral part of <math> \, W / F_ {j} </math>.<br />
<br />
Let <math> \, f_ {j} (y_ {j}) </math> is maximum total value of items loaded in phases <math> \, j, j +1, .., N </math> for a given state <math> \, y_ {j} </math>.<br />
<br />
The recurrence relation is the following:<br />
<br />
<math>\,f_{N} (y_{N} )=\mathop{\max }\limits_{\begin{array}{l} {k_{N} \in \{ 0,1,...,N\} ,} \\ {v_{N} =0,1,...,W} \end{array}} \{ v_{N} y_{N} \} </math><br />
<br />
<math>\,f_{j} (y_{j} )=\mathop{\max }\limits_{\begin{array}{l} {k_{j} =0,1,...,[W/F_{j} ]} \\ {v_{j} =0,1,...,W} \end{array}} \{ v_{j} y_{j} +f_{j+1} (y_{j} -F_{j} k_{j} )\} ,\, \, \, \, j=1,2,...,N-1</math><br />
<br />
The maximum value <math> \, k_ {j} </math> is bounded by <math> \, W / F_ {j} </math>. <br />
<br />
<br />
==Example==<br />
<br />
For our example, calculations begin with the third stage and are performed as follows.<br />
<br />
'''Stage 3'''.<br />
<br />
<math>\,f_{3} (y_{3})=\mathop{\max }\limits_{k_{3}} (30k_{3}), \max k_{3}=[5/1]=5 </math> <br />
<br />
[[File:zPic52.jpg]]<br />
<br />
'''Stage 2'''.<br />
<br />
<math>\,f_{2} (y_{2} )=\mathop{\max }\limits_{k_{2} } (80k_{3} +f_{2} (y_{2} +3k_{2} )), \max k_{2} =[5/3]=1 </math><br />
<br />
[[File:zPic53.jpg]]<br />
<br />
Values in columns are obtained using the recurrence relations. For example, the value in the column <math> \, v_ {2} k_ {2} = 0 </math> in <math> \, y_ {2} = 1 </math> is obtained as follows:<br />
<br />
<math>\,f_{2} (y_{2} )=\mathop{\max }\limits_{k_{2} } (80\cdot 0+f_{3} (1+3\cdot 0))=0+f_{3} (1)=0+30</math>, <br />
<br />
because from the table of step 3, <math> \, f_ {3} (1) = 30 </math>.<br />
<br />
'''Stage 1'''.<br />
<br />
<math>\,f_{1} (y_{1} )=\mathop{\max }\limits_{k_{1} } (65k_{1} +f_{2} (y_{1} +2k_{1} )), \max k_{1} =[5/2]=1</math> <br />
<br />
[[File:zPic54.jpg]]<br />
<br />
For a given <math> \, y_ {1} = W = 5 </math> the optimal solution is <math> \, (k_ {1 }^{*}, k_ {2 }^{*}, k_ {3} ^ {*}) = (2,0,1) </math>, and the total value of goods is equal to 160.</div>Storchhttp://scm.gsom.spbu.ru/Load-planning_problemLoad-planning problem2011-08-20T22:56:19Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Задача_о_загрузке_самолета Задача о загрузке самолета]'''<br />
<br />
To describe the problem and the method of solving the load-planning problem consider the method of dynamic programming and Bellman's optimality principle<br />
<br />
== Dynamic programming method==<br />
<br />
Dynamic programming is widely used in optimal control problems, planning and in solving various technical problems.<br />
<br />
Suppose that the process of control of the system <math>\, X </math> goes <math> \, n </math> steps. Given a state space <math>\, P </math> and control space <math>\, Q </math> with elements <math>\, p </math> and <math>\, q </math> respectively. It is assumed that the initial state <math>\, p_0 </math> is known. Consider a function <math> \, T </math>:<br />
<br />
<math>\, P\times Q\to P</math>, i.e. <math>\, T(p,q)=p',\, \, \, (p,q)\in P\times Q,\, \, p'\in P</math>.<br />
<br />
Function <math> \, T </math> is often referred to as a function of the dynamics of the controlled process.<br />
<br />
Multi-step guided process is realized as follows (see Fig. 1.)<br />
<br />
'''Step 1'''. The system is in the state <math> \, p_ {0} \ in P </math>. In this state the following control is used <math> \, q_ {1} \ in Q </math>. Mapping <math> \, T </math> sets the system into a new state <math> \, T (p_ {0}, q_ {1}) = p_ {1} </math>.<br />
<br />
'''Step 2'''. The system is in the state <math> \, p_ {1} \ in P </math>. In this state the following control is used <math> \, q_ {2} \ in Q </math> so <math> \, T (p_ {1}, q_ {2}) = p_ {2} </math>.<br />
<br />
'''Step ''k''''. The system is in the state <math>\,p_{k-1} \in P</math>. In this state the following control is used <math>\,q_{k} \in Q </math>, then <math>\,T(p_{k-1} ,q_{k} )=p_{k} </math>.<br />
<br />
'''Step''n'''''. The system <math>\,X </math> is in the state <math>\, p_{n-1} \in P </math>. When the control <math>\,q_{n} \in Q </math> is chosen we have <math>\,T(p_{n-1} ,q_{n} )=p_{n} </math>. The process ends.<br />
<br />
[[File:zPic51.jpg]]<br />
<br />
'''Fig. 1. The implementation of the multi-step control process.'''<br />
<br />
We denote <math>\, q = (q_ {1} ,..., q_ {k} ,..., q_ {n}), \, \, \, \, q_ {k} \ in Q, \, \, \, \, k = \overline {1, n} </math> - multistep control process. Then this initial state <math> \, p_ {0} </math> and control <math> \, q </math> corresponds to a trajectory <math> \, p = (p_ {0} ,..., p_ {k-1}, p_ {k}, p_ {k +1} ,..., p_ {n}) </math>, where <math> \, p_ {k} = T (p_ {k-1} , q_ {k}) </math>, <math> \, k = \overline {1, n} </math>.<br />
<br />
Assume that on control <math> \, q </math> and trajectory <math> \, p </math> is given an additive function:<br />
<br />
<math>\, \bar{K}(p,q)=f_{1} (p_{0} ,q_{1} )+...+f_{i} (p_{i-1} ,q_{i} )+...+f_{n} (p_{n-1} ,q_{n} )+f_{n+1} (p_{n} )= \sum _{i=1}^{n}f_{i} (p_{i-1} ,q_{i} ) +f_{n+1} (p_{n} ) </math>.<br />
<br />
Denote<br />
<br />
<math>\, K(p_{0} ,q)=\sum _{i=1}^{n}f_{i} (p_{i-1} ,q_{i} ) +f_{n+1} (p_{n} )</math>.<br />
<br />
value of the function <math> \, \ bar {K} (p, q) </math> on the trajectory of the process from the initial state <math> \, p_ {0} </math> in <math> \, q </math>.<br />
<br />
Now we can formulate the ''discrete optimal control'' problem. Find the optimal control <math> \, q ^ {*} </math>, which is the solution of the following problem:<br />
<br />
<math>\, \mathop{\max }\limits_{q} K(p_{0} ,q)=\max \left[\sum _{i=1}^{n}f_{i} (p_{i-1} ,q_{i} ) +f_{n+1} (p_{n} )\right]</math>.<br />
<br />
under dynamic constraints:<br />
<br />
<math>\, \left\{\begin{array}{l} {p_{i} =T(p_{i-1} ,q_{i} ),\, \, \, q_{i} \in Q,\, \, \, i=\overline{1,n}} \\ {p_{0} =p^{0}} \end{array}\right. </math> <br />
<br />
where <math>\, p_{0} </math> - given initial state of the process.<br />
<br />
Note that when the control <math> \, q_ {i} </math> is being choosing in step <math> \, i </math> we know the state of the process <math> \, p_ {i-1} </math> in the previous step, and the knowledge of <math> \, (p_ {i-1}, q_ {i}) </math> defines the future state of the process and the value of the functional. It is therefore natural to consider functions <math> \, q_ {i} = q_ {i} (p_ {i-1}) </math>, <math> \, i = \overline {1, n} </math> and set of functions<br />
<br />
(1) <math>\, q(\cdot )=(q_{1} (\cdot ),...,q_{k} (\cdot ),...,q_{n} (\cdot )) </math><br />
<br />
where <math>\,q_{k} (\cdot ): q_{k} =q_{k} (p_{k-1} ) </math>. Such set of functions <math>\,q(\cdot ) </math> is called a strategy.<br />
<br />
== Bellman's optimality principle.==<br />
<br />
''Optimal strategy''<br />
<br />
<math>\, q^{*} (\cdot )=(q_{1}^{*} (\cdot ),...,q_{k}^{*} (\cdot ),...,q_{n}^{*} (\cdot )) </math><br />
<br />
has the property that whatever the initial state <math> \, p </math> and the initial control is chosen <math> \, q_ {1} </math>, it remains the best strategy in the process with <math> \, n-1 </math> steps, which starts at the state <math> \, p_ {1} = T (p, q) </math>.<br />
<br />
From Bellman's optimality principle can be derived recurrence ''functional'' Bellman equation, which is the basis of computational procedures for dynamic programming.<br />
<br />
Denote <math> \, F_n (p) </math> - the maximum functional value in <math> \, n </math> - steps problem from the initial state <math> \, p </math>. Function <math> \, F_n (p) </math> is often called the ''Bellman’s function''. From the principle of optimality we have the following equation.<br />
<br />
'''The Bellman equation.'''<br />
<br />
(2) <math>\, F_{n} (p)=\mathop{\max }\limits_{q_{1} \in Q} [f_{1} (p,q_{1} )+F_{n-1} (T(p,q_{1} )) </math><br />
<br />
with the boundary condition<br />
<br />
<math>\, F_{0} (p)=f_{n+1} (p). </math><br />
<br />
'''The general scheme of dynamic programming'''<br />
<br />
Consider the idea of dynamic programming in the following example. Find:<br />
<br />
(3) <math>\, \mathop{\max }\limits_{x_{1} ...x_{n} } \sum _{j=1}^{n}f_{j} (x_{j} )</math>, <br />
<br />
<math>\, x_{j} \ge 0</math>, <math>\,x_{j} </math> - integer, <math>\,j=\overline{1,n}</math>.<br />
<br />
Because the variables <math> \, x_ {j} </math>, <math> \, j = \overline {1, n} </math> are independent, then<br />
<br />
<math>\, \mathop{\max }\limits_{x_{1} ,...,x_{n} } \sum _{j=1}^{n}f_{j} (x_{j} ) =\mathop{\max }\limits_{x_{n} } \left[f_{n} (x_{n} )+\mathop{\max }\limits_{x_{1} ,...,x_{n-1} } \sum _{j=1}^{n-1}f_{j} (x_{j} ) \right]</math>, <br />
<br />
(4) <math>\, \sum _{j=1}^{n-1}a_{j} x_{j} \le b-a_{n} x_{n} </math><br />
<br />
Denote <math> \, \mathop {\ max} \ limits_ {x_ {1} ,..., x_ {n-1}} \ sum _ {j = 1} ^ {n} f_ {j} (x_ {j}) </math> in the condition (4) through <math> \, F_ {n-1} (b-a_ {n} x_ {n}) </math>, then<br />
<br />
(6) <math>\, \mathop{\max }\limits_{x_{1} ,...,x_{n} } \sum _{j=1}^{n}f_{j} (x_{j} ) =\mathop{\max }\limits_{x_{n} } \left[f_{n} (x_{n} )+F_{n-1} (b-a_{n} x_{n} )\right] </math> <br />
<br />
Denote <math>\, \mathop{\max }\limits_{x_{1} ,...,x_{k} } \sum _{j=1}^{k}f_{j} (x_{j} ) =F_{k} (\xi ) </math> under condition<br />
<math>\, \sum _{j=1}^{k}a_{j} x_{j} \le \xi </math>.<br />
<br />
<math>\, x_{j} \ge 0 </math>, <math>\,x_{j} </math> - integer, <math>\,j=\overline{1,n}</math>.<br />
<br />
After transformations we obtain the following fundamental recurrence relation of dynamic programming<br />
<br />
(7) <math>\, F_{k} (\xi )=\mathop{\max }\limits_{x_{k} } \left[f_{k} (x_{k} )+F_{n-1} (\xi -a_{n} x_{n} )\right],\, \, \, k=\overline{1,n} </math><br />
<br />
subject to <math>\,0\le x_{k} \le \frac{\xi }{a_{k} } </math> .<br />
<br />
Use (7) to define calculation process:<br />
<br />
'''Construction of Bellman’s function'''.<br />
<br />
'''Step 1'''. Compute<br />
<br />
(8) <math>\,F_{1} (\xi )=\mathop{\max }\limits_{x_{1} } f_{1} (x_{1} ),\, \, \, x_{1} \le \xi </math>, <br />
<br />
where <math>\,\xi =\overline{0,b}</math> - a parameter of the process. Fill the table 1 by values <math>\,F_{1} (\xi ) </math> , <math>\,x_{1}^{0} (\xi )</math>, for <math>\,\xi =\overline{0,b}</math> <math>\,x_{1}^{0} (\xi )</math> - optimal solution of the problem (8).<br />
<br />
'''Step 2'''. Compute<br />
<br />
(9) <math>\, F_{2}(\xi )=\mathop{\max }\limits_{0\le x_{2} \le \frac{\xi }{a_{2}}} \left[f_{2}(x_{2})+F_{1}(\xi-a_{2} x_{2})\right] </math> <br />
<br />
Values <math> \, F_ {1} (\ xi-a_ {2} x_ {2}) </math> for different values of the argument <math> \, \ xi-a_ {2} x_ {2} </math > select from Table. 1. Fill in the table 2 with the following results: <math> \, F_ {2} (\ xi) </math>, <math> \, x_ {2} ^ {0} (\ xi) </math>, where <math> \, x_ {2} ^ {0} (\ xi) </math> - the optimal solution of problem (9).<br />
<br />
''' Step ''k'''''. <math>\,(1\le k\le n-1)</math>. Compute<br />
<br />
(10) <math>\, F_{k}(\xi )=\mathop{\max }\limits_{0\le x_{k} \le \frac{\xi}{a_{k}}} \left[f_{k}(x_{k})+F_{k-1}(\xi-a_{k}x_{k})\right] </math> <br />
<br />
Fill in the table of values <math> \, F_ {k} (\ xi) </math>, <math> \, x_ {k} ^ {0} (\ xi) </math>, <math> \, \ xi = \overline {0, b} </math>, where <math> \, x_ {k} ^ {0} (\ xi) </math> - the optimal solution of problem (10).<br />
<br />
'''Optimal solution computation'''.<br />
<br />
Assuming <math> \, \ xi = b </math> and <math> \, k = n </math> find <math> \, F_ {n} (b) </math> and <math> \, x_ {n} ^ {0} = x_ {n} ^ {0} (\ xi) </math>.<br />
<br />
<br />
Calculate in (10) the optimal value <math> \, x_ {n} ^ {0} = x_ {n} ^ {0} (\ xi) </math> and assume <math> \, \ xi_ {1}, {0} = b-a_ {n} x_ {n} ^ {0} </math>. Then, using the value of <math>\, \ xi _ {1} ^ {0} </math> of the table step <math> \, n-1 </math>, determine the optimal values of other variables <math> \, x_ {n-1} ^ {0} (\ xi _ {1} ^ {0}) </math>. Then determine the values <math> \, x_ {n-2} ^ {0} (\ xi_ {1} ^ {0}), \ dots, x_ {1} ^ {0} (\ xi _ {1} ^ {0}) </math>.<br />
<br />
{| border="1"<br />
| align="center" | <math>\,\xi </math>|| align="center" | <math>\,F_{1}(\xi)</math> || align="center" | <math>x_{1}^{0} (\xi )</math><br />
|-<br />
| align="center" |<math>\, 0 </math> || align="center" | <math>\, F_{1}(0)</math> || align="center" | <math>\, x_{1}^{0}(0)</math><br />
|-<br />
| align="center" |<math>\, 1 </math> || align="center" | <math>\, F_{1}(1)</math> || align="center" | <math>\, x_{1}^{0}(1)</math><br />
|-<br />
| align="center" | <math>\, \ldots </math>|| align="center" | <math>\, \ldots </math> || align="center" | <math>\, \ldots </math><br />
|-<br />
| align="center" | <math>\, b-1 </math> || align="center" | <math>\, F_{1} (b-1) </math> || align="center" | <math>\, x_{1}^{0} (b-1)</math><br />
|-<br />
| align="center" | <math>\, b </math> || align="center" | <math>\, F_{1} (b)</math> || align="center" | <math>\,x_{1}^{0}(b)</math><br />
|}<br />
<br />
''Table 1. Table for the first iteration''<br />
{| border="1"<br />
| align="center" | <math>\,\xi</math>|| align="center" | <math>\,F_{2}(\xi )</math> || align="center" | <math>\, x_{2}^{0}(\xi)</math><br />
|-<br />
| align="center" |<math>\, 0 </math> || align="center" | <math>\, F_{2}(0)</math> || align="center" | <math>\, x_{2}^{0}(0)</math><br />
|-<br />
| align="center" |<math>\, 1 </math> || align="center" | <math>\, F_{2}(1)</math> || align="center" | <math>\, x_{2}^{0}(1)</math><br />
|-<br />
| align="center" | <math>\, \ldots </math>|| align="center" | <math>\, \ldots </math> || align="center" | <math>\, \ldots </math><br />
|-<br />
| align="center" | <math>\, b-1 </math> || align="center" | <math>\, F_{2} (b-1) </math> || align="center" | <math>\, x_{2}^{0} (b-1)</math><br />
|-<br />
| align="center" | <math>\, b </math> || align="center" | <math>\, F_{2} (b)</math> || align="center" | <math>\,x_{2}^{0}(b)</math><br />
|}<br />
<br />
''Table 2. Table for the second iteration''<br />
<br />
To apply dynamic programming method the following conditions are to be satisfied:<br />
<br />
* The decision-making process should allow an interpretation as a multi-step process;<br />
<br />
* For each step it should be defined a set of state parameters <math> \, \ xi </math>, which do not depend on the number of steps;<br />
<br />
* Optimal solution in step <math> \, k </math> depends only on the current state and does not depend on the prehistory of the process.<br />
<br />
== The problem of loading an aircraft ==<br />
<br />
An aircraft is loaded by objects <math> \, N </math> of various types. Each object type <math> \, i </math> has weight <math> \, F_ {i} </math> and insurance cost <math> \, v_ {i} </math>, (<math> \ , i = \overline {1, N} </math>). Maximum load capacity of the aircraft is <math> \, W </math>. It is required to determine the maximum value of the goods whose weight must not exceed maximum permissible carrying capacity of aircraft. For definiteness, assume that <math> \, W = 5 </math> and there are three types of objects, details of which are listed in the table below:<br />
{| border="1"<br />
| align="center" | <math>\, \, \, \, i \, \, \, </math>|| align="center" | <math>\, \, \, \, F_{i}\, \, \, </math> || align="center" | <math>\, \, \, \, v_{i} \, \, \, </math><br />
|-<br />
| align="center" |<math>\, 1 </math> || align="center" | <math>\, 2 </math> || align="center" | <math>\, 65 </math><br />
|-<br />
| align="center" |<math>\, 2 </math> || align="center" | <math>\, 3 </math> || align="center" | <math>\, 80 </math><br />
|-<br />
| align="center" | <math>\, 3 </math>|| align="center" | <math>\, 1 </math> || align="center" | <math>\, 30 </math><br />
|}<br />
<br />
Consider the problem in general formulation. Denote the number of items such as <math> \, i </math> by <math> \, k_ {i} </math>. Then the problem of loading the aircraft can be written as:<br />
<br />
<math>\, \max z=\max (v_{1} k_{1} +v_{2} k_{2} +...+v_{N} k_{N} ) </math><br />
<br />
<math>\, \left\{\begin{array}{l} {F_{1} k_{1} +F_{2} k_{2} +...+F_{n} k_{n} \le W,} \\ {k\ge 0,\, \, i=\overline{1,N,}} \end{array}\right. </math> <br />
<br />
where <math>\, k </math> are integer.<br />
<br />
If it were possible to discard the requirement of integrality, it was a linear programming problem and it could be solved with the simplex method.<br />
<br />
Consider three main elements of a dynamic model.<br />
<br />
'''1.''' Step <math> \, j </math> is associated with type <math> \, j, j = 1,2 ,..., </math><br />
<br />
'''2.''' State <math> \, y_j </math> on stage <math> \, j </math> is the total weight of items, loaded on the previous stages <math> \, j, j + 1, \ dots, \ textit {N} </math>. The variable <math> \, y_j </math> can be <math> \, 0,1, \ dots, W </math> in <math> \, j = 1,2, \ dots, N </math>.<br />
<br />
'''3.''' Solutions. Values <math> \, k_ {j} </math> on stage <math> \, j </math> describe the type of items <math> \, j </math>. Value <math> \, k_ {j} \ in [0, [W / F_ {j}]] </math>, where <math> \, [W / F_ {j}] </math> is the integral part of <math> \, W / F_ {j} </math>.<br />
<br />
Let <math> \, f_ {j} (y_ {j}) </math> is maximum total value of items loaded in phases <math> \, j, j +1, .., N </math> for a given state <math> \, y_ {j} </math>.<br />
<br />
The recurrence relation is the following:<br />
<br />
<math>\,f_{N} (y_{N} )=\mathop{\max }\limits_{\begin{array}{l} {k_{N} \in \{ 0,1,...,N\} ,} \\ {v_{N} =0,1,...,W} \end{array}} \{ v_{N} y_{N} \} </math><br />
<br />
<math>\,f_{j} (y_{j} )=\mathop{\max }\limits_{\begin{array}{l} {k_{j} =0,1,...,[W/F_{j} ]} \\ {v_{j} =0,1,...,W} \end{array}} \{ v_{j} y_{j} +f_{j+1} (y_{j} -F_{j} k_{j} )\} ,\, \, \, \, j=1,2,...,N-1</math><br />
<br />
The maximum value <math> \, k_ {j} </math> is bounded by <math> \, W / F_ {j} </math>. <br />
<br />
<br />
==Example==<br />
<br />
For our example, calculations begin with the third stage and are performed as follows.<br />
<br />
'''Stage 3'''.<br />
<br />
<math>\,f_{3} (y_{3})=\mathop{\max }\limits_{k_{3}} (30k_{3}), \max k_{3}=[5/1]=5 </math> <br />
<br />
[[File:zPic52.jpg]]<br />
<br />
'''Stage 2'''.<br />
<br />
<math>\,f_{2} (y_{2} )=\mathop{\max }\limits_{k_{2} } (80k_{3} +f_{2} (y_{2} +3k_{2} )), \max k_{2} =[5/3]=1 </math><br />
<br />
[[File:zPic53.jpg]]<br />
<br />
Values in columns are obtained using the recurrence relations. For example, the value in the column <math> \, v_ {2} k_ {2} = 0 </math> in <math> \, y_ {2} = 1 </math> is obtained as follows:<br />
<br />
<math>\,f_{2} (y_{2} )=\mathop{\max }\limits_{k_{2} } (80\cdot 0+f_{3} (1+3\cdot 0))=0+f_{3} (1)=0+30</math>, <br />
<br />
because from the table of step 3, <math> \, f_ {3} (1) = 30 </math>.<br />
<br />
'''Stage 1'''.<br />
<br />
<math>\,f_{1} (y_{1} )=\mathop{\max }\limits_{k_{1} } (65k_{1} +f_{2} (y_{1} +2k_{1} )), \max k_{1} =[5/2]=1</math> <br />
<br />
[[File:zPic54.jpg]]<br />
<br />
For a given <math> \, y_ {1} = W = 5 </math> the optimal solution is <math> \, (k_ {1 }^{*}, k_ {2 }^{*}, k_ {3} ^ {*}) = (2,0,1) </math>, and the total value of goods is equal to 160.</div>Storchhttp://scm.gsom.spbu.ru/Multiproduct_static_model_with_a_limited_capacity_of_the_warehouseMultiproduct static model with a limited capacity of the warehouse2011-08-20T12:03:40Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://scm.gsom.spbu.ru/index.php/Многопродуктовая_статическая_модель_с_ограниченной_вместимостью_склада Многопродуктовая статическая модель с ограниченной вместимостью склада]'''<br />
<br />
Let us consider the case of static demand.<br />
<br />
== Basic assumptions of the model ==<br />
<br />
* consider the problem of managing multiple types of stock;<br />
<br />
* storage space is limited;<br />
<br />
* order cost is a constant;<br />
<br />
* price of the resource unit is constant;<br />
<br />
* carrying cost of resource is constant;<br />
<br />
* cost of placing an order is constant;<br />
<br />
* order cost is constant;<br />
<br />
* no deficit.<br />
<br />
== Basic notations ==<br />
<br />
There are two types of inventory <math>\, i</math>, <math>\, i=1,2,...,n</math>:<br />
<br />
* <math>\, D_{i}</math> - demand rate;<br />
<br />
* <math>\, h_{i}</math> - marginal carrying costs;<br />
<br />
* <math>\, K_{i}</math> - fixed order costs;<br />
<br />
* <math>\, TCU(y)</math> - total costs per period;<br />
<br />
* <math>\, y_{i}</math> - order quantity; <br />
<br />
* <math>\, y_{i}^{*}</math> - economic order quantity;<br />
<br />
* <math>\, a_{i}</math> - the space required to store the unit of resource;<br />
<br />
* <math>\, A</math> - the maximum space required to store <math>\, n</math> types of resources.<br />
<br />
== Inventory optimal control ==<br />
<br />
According to the assumptions of the model, consider dynamics of the resource stock <math>\, i</math>, (Fig. 1): <br />
<br />
[[File:Z3pic1.JPG]]<br />
<br />
''Fig. 1.''' Dynamics of changes in resource stock <math>\, i</math>.<br />
<br />
<br />
Multiproduct static model with limited capacity of the warehouse can be formalized as a nonlinear programming problem:<br />
<br />
<math>\min TCU(y_{1} ,y_{2} ,...,y_{n} )=\sum \limits _{i=1}^{n}\left(\frac{K_{i} D_{i} }{y_{i} } +\frac{h_{i} y_{i} }{2} \right)</math> <br />
<br />
<math>\sum \limits _{i=1}^{n}a_{i} y_{i} \le A</math><br />
<br />
<math>\, y_{i} >0</math><br />
<br />
<math>\,i=1,2,...,n</math>.<br />
<br />
''' Inventory optimal control '''<br />
<br />
For this problem of nonlinear programming the Lagrange function has the form:<br />
<br />
<math>L(\lambda ,y_{1} ,y_{2} ,...,y_{n} )=TCU(y_{1} ,y_{2} ,...,y_{n} )-\lambda \left(\sum \limits _{i=1}^{n}a_{i} y_{i} -A\right)=</math><br />
<br />
<math> =\sum \limits _{i=1}^{n}\left(\frac{K_{i} D_{i} }{y_{i} } +\frac{h_{i} y_{i} }{2} \right) -\lambda \left(\sum \limits _{i=1}^{n}a_{i} y_{i} -A\right)</math> ,<br />
<br />
where <math>\, \lambda <0</math> is a Lagrange multiplier.<br />
<br />
The Lagrange function for multiproduct static model with limited capacity of the warehouse is convex, hence, the optimal value <math>\, \lambda </math> and <math>\, y_ {i} </math> can be found from the first order conditions:<br />
<br />
<math> \frac{\partial L}{\partial \lambda } =-\sum \limits _{i=1}^{n}a_{i} y_{i} +A=0</math> (limitation on the capacity of a warehouse at the optimal point);<br />
<br />
<math>\frac{\partial L}{\partial y_{i} } =-\frac{K_{i} D_{i} }{y_{i}^{2} } +\frac{h_{i} }{2} -\lambda a_{i} =0</math> .<br />
<br />
The solution of the second equation is:<br />
<br />
<math>y_{i}^{*} =\sqrt{\frac{2K_{i} D_{i} }{h_{i} -2\lambda ^{*} a_{i} } }</math> .<br />
<br />
The optimal solution value <math>\, \lambda^{*}</math> with the desired accuracy can be found as follows:<br />
<br />
1. Set the initial value <math>\, \lambda =0</math> <br />
<br />
2. Set the value <math>\, \varepsilon </math> for decreasing the value <math>\, \lambda </math> (accuracy)<br />
<br />
3. Consistently reduce <math>\, \lambda </math> on the value of <math> \, \varepsilon </math>, substituting the value of <math>\, \lambda </math> in <math> y_ {i} = \sqrt {\frac {2K_ {i} D_ {i}} {h_ {i} -2 \lambda a_ {i}}} </math> and checking the performance limitations on the capacity of the warehouse.<br />
<br />
<br />
The optimal strategy for inventory management in our model has the form:<br />
<br />
'''Step 1.''' Calculate the optimal volume of orders, not including the restriction on the capacity of storage (see [[Basic economic order quantity]]) as follows:<br />
<br />
<math>y_{i}^{**} =\sqrt{\frac{2K_{i} D_{i} }{h_{i} } }</math>,<br />
<br />
<math>\, i=1,2,...,n</math>.<br />
<br />
'''Step 2.''' Subject to the values found <math>\, y_ {i }^{**}</math>, <math>\, i = 1,2 ,..., n </math > verify constraints on the capacity of the warehouse. If this restriction is satisfied, then the set of values <math>\, y_ {i }^{*}</math>, <math>\, i = 1,2 ,..., n </math> is the optimal solution for multiproduct static model with a limited capacity of the warehouse. Otherwise, the best solution is the set <math>\, y_ {i }^{*}</math>, <math>\, i = 1,2 ,..., n </math></div>Storchhttp://scm.gsom.spbu.ru/Multiproduct_static_model_with_a_limited_capacity_of_the_warehouseMultiproduct static model with a limited capacity of the warehouse2011-08-20T11:59:52Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://scm.gsom.spbu.ru/index.php/Многопродуктовая_статическая_модель_с_ограниченной_вместимостью_склада Многопродуктовая статическая модель с ограниченной вместимостью склада]'''<br />
<br />
<br />
Multiproduct static model with a limited capacity of the warehouse<br />
<br />
Consider the case of static demand.<br />
<br />
== The basic assumptions of the model ==<br />
<br />
* consider the problem of managing multiple types of stock;<br />
<br />
* storage space is limited;<br />
<br />
* order cost is a constant;<br />
<br />
* price of the resource unit is constant;<br />
<br />
* carrying cost of resource unit is a constant;<br />
<br />
* затраты на оформление, связанные с размещением заказа, - постоянная величина (константа);<br />
<br />
* order cost is a constant;<br />
<br />
* no deficit.<br />
<br />
== The basic notations ==<br />
<br />
There are two types of inventory <math>\, i</math>, <math>\, i=1,2,...,n</math>:<br />
<br />
* <math>\, D_{i}</math> - demand rate;<br />
<br />
* <math>\, h_{i}</math> - marginal carrying costs;<br />
<br />
* <math>\, K_{i}</math> - fixed order costs;<br />
<br />
* <math>\, TCU(y)</math> - total costs per unit of time;<br />
<br />
* <math>\, y_{i}</math> - order quantity; <br />
<br />
* <math>\, y_{i}^{*}</math> - economic order quantity;<br />
<br />
* <math>\, a_{i}</math> - the space required to store the unit;<br />
<br />
* <math>\, A</math> - the maximum space required to store <math>\, n</math> types of resources.<br />
<br />
== Inventory optimal control ==<br />
<br />
According to the assumptions of the model, consider dynamics of the resource stock <math>\, i</math>, fig. 1: <br />
<br />
[[File:Z3pic1.JPG]]<br />
<br />
''Fig. 1.''' Dynamics of changes in resource stock <math>\, i</math>.<br />
<br />
<br />
Multiproduct static model with a limited capacity of the warehouse can be formalized as a nonlinear programming problem:<br />
<br />
<math>\min TCU(y_{1} ,y_{2} ,...,y_{n} )=\sum \limits _{i=1}^{n}\left(\frac{K_{i} D_{i} }{y_{i} } +\frac{h_{i} y_{i} }{2} \right)</math> <br />
<br />
<math>\sum \limits _{i=1}^{n}a_{i} y_{i} \le A</math><br />
<br />
<math>\, y_{i} >0</math><br />
<br />
<math>\,i=1,2,...,n</math>.<br />
<br />
''' Inventory optimal control '''<br />
<br />
For the above problem of nonlinear programming Lagrange function has the form:<br />
<br />
<math>L(\lambda ,y_{1} ,y_{2} ,...,y_{n} )=TCU(y_{1} ,y_{2} ,...,y_{n} )-\lambda \left(\sum \limits _{i=1}^{n}a_{i} y_{i} -A\right)=</math><br />
<br />
<math> =\sum \limits _{i=1}^{n}\left(\frac{K_{i} D_{i} }{y_{i} } +\frac{h_{i} y_{i} }{2} \right) -\lambda \left(\sum \limits _{i=1}^{n}a_{i} y_{i} -A\right)</math> ,<br />
<br />
where <math>\, \lambda <0</math> is a Lagrange multiplier.<br />
<br />
The Lagrange function for multiproduct static model with a limited capacity of the warehouse is convex, hence, the optimal value <math>\, \lambda </math> and <math>\, y_ {i} </math> can be found from the first order conditions:<br />
<br />
<math> \frac{\partial L}{\partial \lambda } =-\sum \limits _{i=1}^{n}a_{i} y_{i} +A=0</math> (limitation on the capacity of a warehouse at the optimal point);<br />
<br />
<math>\frac{\partial L}{\partial y_{i} } =-\frac{K_{i} D_{i} }{y_{i}^{2} } +\frac{h_{i} }{2} -\lambda a_{i} =0</math> .<br />
<br />
The solution of the second equation is:<br />
<br />
<math>y_{i}^{*} =\sqrt{\frac{2K_{i} D_{i} }{h_{i} -2\lambda ^{*} a_{i} } }</math> .<br />
<br />
The optimal solution value <math>\, \lambda^{*}</math> with the desired accuracy can be found as follows:<br />
<br />
1. Set the initial value <math>\, \lambda =0</math> <br />
<br />
2. Set the value <math>\, \varepsilon </math> for decreasing the value <math>\, \lambda </math> (accuracy)<br />
<br />
3. Consistently reduce <math>\, \lambda </math> on the value of <math> \, \varepsilon </math>, substituting the value of <math>\, \lambda </math> in <math> y_ {i} = \sqrt {\frac {2K_ {i} D_ {i}} {h_ {i} -2 \lambda a_ {i}}} </math> and checking the performance limitations on the capacity of the warehouse.<br />
<br />
<br />
The optimal strategy for inventory management in our model has the form:<br />
<br />
'''Step 1.''' Calculate the optimal volume of orders, not including the restriction on the capacity of storage (see [[Basic economic order quantity]]) as follows:<br />
<br />
<math>y_{i}^{**} =\sqrt{\frac{2K_{i} D_{i} }{h_{i} } }</math>,<br />
<br />
<math>\, i=1,2,...,n</math>.<br />
<br />
'''Step 2.''' Subject to the values found <math>\, y_ {i }^{**}</math>, <math>\, i = 1,2 ,..., n </math > verify constraints on the capacity of the warehouse. If this restriction is satisfied, then the set of values <math>\, y_ {i }^{*}</math>, <math>\, i = 1,2 ,..., n </math> is the optimal solution for multiproduct static model with a limited capacity of the warehouse. Otherwise, the best solution is the set <math>\, y_ {i }^{*}</math>, <math>\, i = 1,2 ,..., n </math></div>Storchhttp://scm.gsom.spbu.ru/EOQ_with_price_gapEOQ with price gap2011-08-20T11:02:13Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/index.php/Экономичный_размер_запаса_с_разрывами_цен Экономичный размер запаса с разрывами цен]'''<br />
<br />
Consider the case of static demand.<br />
<br />
== The basic assumptions of the model ==<br />
<br />
* Number of units consumed per unit of time is a constant (demand rate);<br />
<br />
* Price of the resource unit depends on order volume. If the order quantity does not exceed a certain level of <math>\, q ^{*}</math>, then the price is constant <math>\, c_ {1} </math>, otherwise - the price is a constant <math>\, c_ {2} </math>, where <math>\, c_ {1}> c_ {2} </math>:<br />
<br />
<math>c=\left\{\begin{array}{l} {c_{1} ,\, \, y\le q^{*} ,} \\ {c_{2} ,\, \, y>q^{*} ;} \end{array}\right.</math> <br />
<br />
* Carrying cost of resource unit is a constant;<br />
<br />
*Order cost is a constant;<br />
<br />
*Lead time is zero.<br />
<br />
== The basic notations ==<br />
<br />
* <math>\, D</math> – demand rate;<br />
<br />
* <math>\, h</math> – marginal carrying costs;<br />
<br />
* <math>\, K</math> – fixed order costs;<br />
<br />
* <math>\, t_{0}</math> – order cycle time;<br />
<br />
* <math>\, TCU(y)</math> – total costs per unit of time;<br />
<br />
* <math>\, y</math> – order quantity;<br />
<br />
* <math>\, y^{*}</math> – economic order quantity.<br />
<br />
== Inventory optimal control==<br />
<br />
Costs of resource per unit of time are a function of the size of orders:<br />
<br />
<math>\left\{\begin{array}{l} {c_{1} \frac{y}{t_{0} } ,\, \, y\le q^{*} ,} \\ {c_{2} \frac{y}{t_{0} } ,\, \, y>q^{*} .} \end{array}\right.</math> <br />
<br />
Given the dependence of the order cycle time on the intensity of demand for the resource, <math>\, t_{0} = \frac {y} {D} </math>, the cost of the purchase of products per unit time can be represented as:<br />
<br />
<math>\left\{\begin{array}{l} {c_{1} \frac{y}{\left(\frac{y}{D} \right)} =Dc_{1} ,\, \, y\le q^{*} ,} \\ {c_{2} \frac{y}{\left(\frac{y}{D} \right)} =Dc_{2} ,\, \, y>q^{*} .} \end{array}\right.</math> <br />
<br />
<br />
The total cost per unit time can be represented as a function of order volume <math>\, y </math> as the sum of acquisition costs of resource per unit of time, the cost of ordering and storage costs of the resource per unit time:<br />
<br />
<math>\,TCU(y)=\left\{\begin{array}{l} {TCU_{1} (y)=Dc_{1} +\frac{K}{t_{0} } +h\left(\frac{y}{2} \right)t_{0} ,\, \, y\le q^{*} ,} \\ {TCU_{2} (y)=Dc_{2} +\frac{K}{t_{0} } +h\left(\frac{y}{2} \right)t_{0} ,\, \, y>q^{*} ,} \end{array}\right.</math> <br />
<br />
or:<br />
<br />
<math>TCU(y)=\left\{\begin{array}{l} {TCU_{1} (y)=Dc_{1} +\frac{KD}{y} +h\left(\frac{y}{2} \right)t_{0} ,\, \, y\le q^{*} ,} \\ {TCU_{2} (y)=Dc_{2} +\frac{KD}{y} +h\left(\frac{y}{2} \right)t_{0} ,\, \, y>q^{*} ,} \end{array}\right.</math> <br />
<br />
The graphs of the function <math>\, TCU_{1} (y)</math> and <math>\, TCU_{2} (y)</math> are the following, fig. 1: <br />
<br />
[[File:Z2pic1.JPG]]<br />
<br />
'''Fig. 1.''' The function of total costs<br />
<br />
The point <math>\, y_{\min }</math> is determined according to economic order quantity:<br />
<br />
<math> y_{\min } =\sqrt{\frac{2KD}{h} } >0</math>.<br />
<br />
In the point <math>\, q^{*}</math> the following inequality holds:<br />
<br />
<math>\, TCU_{1} (y_{\min } )=TCU_{2} (q^{*} )</math>,<br />
<br />
or:<br />
<br />
<math>TCU_{1} (y_{\min } )=Dc_{2} +\frac{KD}{q^{*} } +h\left(\frac{q^{*} }{2} \right)t_{0}</math>,<br />
<br />
then:<br />
<br />
<math>(q^{*} )^{2} +\left(\frac{2(Dc_{2} -TCU(y_{\min } ))}{h} \right)q^{*} +\frac{2KD}{h} =0</math>.<br />
<br />
When <math> \, y \ le q ^{*}</math> graph <math> \, TCU (y) </math> equal to <math> \, TCU_ {1} (y) </math >. When <math> \, y> q ^{*}</math> graph <math> \, TCU (y) </math> equal to <math> \, TCU_ {2} (y) </math>. In correspondence with a graph, consider the three areas on the x-axis: <math> \, 0 \ le y <y_ {\ min} </math>, <math> \, y_ {\ min} \ le y <q ^ {* } </math>, <math> \, y> q ^ {*} </math>, which are called, respectively:''A'',''B''and''C''. The optimum size of the order <math> \, y ^ {*} </math> depends on what area is the point <math> \, q ^ {*} </math>, Fig. 2, 3, 4:<br />
<br />
<br />
<math>y^{*} =\left\{\begin{array}{ll} {y_{\min } ,} & {q\in A} \\ {q,} & {q\in B} \\ {y_{\min } ,} & {q\in C} \end{array}\right.</math> <br />
<br />
[[File:Z2pic21.JPG]]<br />
<br />
'''Fig. 2.''' <math>\, q\in A</math> , <math>\, y^{*} =y_{\min }</math>.<br />
<br />
----<br />
[[File:Z2pic22.JPG]]<br />
<br />
'''Fig. 3.''' <math>\, q\in B</math> , <math>\, y^{*} =q</math> .<br />
<br />
----<br />
<br />
[[File:Z2pic23.JPG]]<br />
<br />
'''Fig. 4.''' <math>\, q\in C</math> , <math>\, y^{*} =y_{\min }</math>.<br />
<br />
----<br />
<br />
Optimal inventory control in the model is the following:<br />
<br />
'''Step 1.''' According to EOQ compute <math>y_{\min } =\sqrt{\frac{2KD}{h} } >0</math> . If <math>\, q\in A</math> , then <math>\, y^{*} =y_{\min }</math> , else, go to step 2.<br />
<br />
'''Step 2.''' Compute <math>\, q^{*}</math> from the following equation:<br />
<br />
<math> (q^{*} )^{2} +\left(\frac{2(Dc_{2} -TCU(y_{\min } ))}{h} \right)q^{*} +\frac{2KD}{h} =0</math> ,<br />
<br />
to determine the border areas <math>\, B</math> and <math>\, C</math> . If <math>\, q\in B</math> , then <math>\, y^{*} =q</math> , if <math>\, q\in C</math> , then <math>\, y^{*} =y_{\min }</math> .</div>Storchhttp://scm.gsom.spbu.ru/Basic_economic_order_quantityBasic economic order quantity2011-08-20T10:59:50Z<p>Storch: </p>
<hr />
<div>Let us consider the case of static demand. <br />
<br />
== The basic assumptions of the model ==<br />
<br />
* Number of units consumed per period is a constant (demand rate);<br />
<br />
* Price of the resource is constant;<br />
<br />
* Carrying cost of the resource is constant;<br />
<br />
* Order cost is constant;<br />
<br />
* Lead time is zero.<br />
<br />
==The basic notations==<br />
<br />
*<math>\, D</math> – demand rate;<br />
<br />
*<math>\, h</math> – marginal carrying costs;<br />
<br />
*<math>\, K</math> – fixed order costs;<br />
<br />
*<math>\, t_{0}</math> – order cycle time;<br />
<br />
*<math>\, TCU(y)</math> – total costs per period;<br />
<br />
*<math>\, y</math> – order quantity;<br />
<br />
*<math>\, y^{*}</math> – economic order quantity.<br />
<br />
'''Inventory optimal control'''<br />
<br />
According to the assumptions dynamics of inventory takes the following form (Fig. 1): <br />
<br />
[[File:zPic1.jpg]]<br />
<br />
Fig. 1. The dynamics of inventory in the economic order quantity model.<br />
<br />
Since the intensity of demand for the resource is constant, the average inventory level is <math>\, \frac {y} {2} </math> units. Therefore, the total cost per unit time can be explained as a function of order volume in the form of the cost of ordering a unit of time and storage costs of the resource per unit time:<br />
<br />
(1) <math> TCU(y)=\frac{K}{t_{0} } +h\left(\frac{y}{2} \right)t_{0}</math> .<br />
<br />
Given the dependence of the order cycle time, the intensity of demand for the resource, <math>\, t_ {0} = \frac {y} {D} </math>, equation (1) becomes:<br />
<br />
(2) <math>TCU(y)=\frac{KD}{y} +h\left(\frac{y}{2} \right) </math> .<br />
The first order condition for the function (2) becomes:<br />
<br />
(3) <math>\frac{d}{dy} \left(TCU(y)\right)=-\frac{KD}{y^{2} } +\frac{h}{2} =0</math> . <br />
The second order condition for the function (2) is:<br />
<br />
(4) <math>\frac{d^{2} }{dy^{2} } \left(TCU(y)\right)=\frac{2KD}{y^{3} }</math> . <br />
<br />
Therefore, the function <math>\, TCU(y)</math> is convex with respect to <math>\, y</math>, where <math>\, y>0</math> . Then, the solution of equation (3) of the form<br />
<br />
<math> y^{*} =\sqrt{\frac{2KD}{h} } >0</math><br />
<br />
is the minimum point of <math>\, TCU (y) </math>. Value <math> \, y ^{*}</math> is the economic order quantity.<br />
<br />
The optimal duration of order cycle becomes:<br />
<br />
(5) <math>\, t_{0}^{*} =\frac{y^{*}}{D}=\frac{1}{D}\sqrt{\frac{2KD}{h}}=\sqrt{\frac{2K}{Dh}}</math> <br />
<br />
Total minimum costs per period, <math>\, TCU^{*} </math> , takes the following form:<br />
<br />
(6) <math>TCU^{*} =TCU(y^{*} )=\frac{KD}{y^{*} } +h\left(\frac{y^{*} }{2} \right)=</math><br />
<br />
<math>=KD\sqrt{\frac{h}{2KD} } +\frac{h}{2} \sqrt{\frac{2KD}{h} } =\sqrt{\frac{KDh}{2} } +\sqrt{\frac{KDh}{2} } =</math><br />
<br />
<math>=\, \sqrt{2KDh}</math> .<br />
<br />
Optimal inventory control in the economic order quantity is the following:<br />
<br />
''How much to order?''. Order <math>y^{*} =\sqrt{\frac{2KD}{h} } </math> units of the resource.<br />
<br />
''When to order?'' After each <math>t_{0}^{*} =\frac{y^{*} }{D}</math> units of time.<br />
<br />
==Example.==<br />
<br />
On an assembly line of computers daily are consumed 50 processors. The cost of placing an order for the purchase of processors regardless of how much the party is $ 25. Carrying cost of a single processor per day is $ 0.25. What is the optimal inventory control strategy.<br />
<br />
'''Solution.'''<br />
<br />
<math>\, D=50 </math> processors per day,<br />
<br />
<math>\, h=$ 0,25</math> for carrying one processor,<br />
<br />
<math>\, K=$ 25</math> for order.<br />
<br />
Then economic order quantity is<br />
<br />
<math>y^{*} =\sqrt{\frac{2KD}{h} } =\sqrt{\frac{2\cdot 25\cdot 50}{0,25} } =100</math> <br />
<br />
processors, and the optimal order cycle time is<br />
<br />
<math>t_{0}^{*} =\frac{y^{*} }{D} =\frac{100}{50} =2</math> days.</div>Storchhttp://scm.gsom.spbu.ru/OutsourcingOutsourcing2011-08-19T10:03:33Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Аутсорсинг Аутсорсинг]'''<br />
<br />
While global statistics are difficult to come by on the scale of outsourcing, a Frost & Sullivan 2005 consulting report stated that the global market for outsourcing by Global Fortune 500 companies was valued at US $648 billion in 2004, a figure expected to increase to US $920 billion by 2007.<ref>Shared Services and Outsourcing (SSO): Hub Potential Analysis (Abridged by Select Verticals) (2005), http://www.mscmalaysia.my/codenavia/portals/msc/images/pdf/awards_accolades/frost_sullivan_sso.pdf.</ref> The “true” global market for all outsourcing at the current point in time is very likely to be much higher owing to growth, to definitional issues that would seem to omit much of what passes for outsourcing, and to the omission of firms lesser in scale. No review of outsourcing could ignore the definitional problem. A commonly held definition states that outsourcing is concerned with performing activities outside the firm that were previously and normally conducted within the firm.<ref name=McIvor2009>McIvor, R. (2009), “How the Transaction Cost and Resource-based Theories of the Firm Inform Outsourcing Evaluation,” ''Journal of Operations Management'', 27 (1), 45-63.</ref> The problem with this definition is that no clear distinction exists with the make-versus-buy decision. The make-versus-buy decision is very similar to functional spin-off and vertical integration. The make-versus-buy decision examines the choice of governance with market transactions at one end of the spectrum, hierarchies (or vertical integration) at the other end,<ref name=Williamson1975> Williamson, O.E. (1975), ''Markets and Hierarchies'', Free Press, New York. </ref> and with hybrid, alliance-type exchange as an intermediate form. Functional spin-off is a marketing term that may be defined as the subcontracting of a marketing function by a channel intermediary to another intermediary.<ref>Mallen, B. (1973), “Functional Spin-Off: A Key to Anticipating Change in a Distribution Channel,” ''Journal of Marketing'', 37 (3), 18-25.</ref> Spinning-off a function and shifting it a third party is essentially equivalent to the “buy” option of the make-versus-buy decision. One further problem with the common definition of outsourcing concerns the notion that innovations in communications, information and production technologies, products and component parts, transportation systems, and material handling equipment shift underlying cost structures, thereby increasing (or decreasing) the appeal of various make-versus-buy alternatives. Furthermore, these innovations foster new behaviors, practices, and, more important, new functions and processes that the firm must assess and decide whether to perform in-house (i.e., to integrate vertically) or to outsource (either to a market or through a hybrid form of exchange). A clear example is the infusion of electronics into automobliles -- at some point in time, manufacturers had to decide who would design, manufacture, integrate, and distribute the new and previously undreampt of innovation. In the search for efficiency and effectiveness, firms are in a constant state of flux as they experiment with alternatives that selectively increase or decrease the boundaries of the firm. Research on outsourcing, vertical integration, and the boundaries of the firm:<br />
* Has been conducted in a variety of settings including manufacturing,<ref> Ashwin, W.J. and R.L. Stump (1999), “The Contingent Effect of Specific Asset Investments on Joint Action in Manufacturer-Supplier Relationships: An Empirical Test of the Moderating Role of Reciprocal Asset Investments, Uncertainty, and Trust,” ''Journal of the Academy of Marketing Science'', 27 (3), 291-306.</ref> healthcare,<ref name=Moschuris2007> Moschuris, S.J. and M.N. Kondylis (2007), “Outsourcing in Private Healthcare Organisations: A Greek Perspective,” ''Journal of Health Organization Management'', 21 (2), 220-223.</ref> agriculture,<ref> Gillespie, J., R. Henring, C. Sandretto, and C. Hallahan (2007), “Forage Outsourcing in the Dairy Sector: The Extent of Use and Impact on Farm Profitability,” ''Agricultural and Resource Economics Review'', 39 (3), 399-414.</ref> transportation carriers,<ref name=Baker2003> Baker, G.P. and T.N. Hubbard (2003), “Make versus Buy in Trucking: Asset Ownership, Job Design, and Information,” ''American Economic Review'', 93 (3), 551-572.</ref> and chain restaurants;<ref> Combs, J.G. and D.J. Ketchen (1999), “Explaining Inter-firm Cooperation and Performance: Toward A Reconciliation of Predictions From the Resource-based View and Organizational Economics,” ''Strategic Management Journal'', 20 (9), 435-450.</ref><br />
* Has been applied to various functions including accounting,<ref> Maelah, R., A. Aman, N. Hamzah, R. Amiruddin and S.M. Auzair (2010), “Accounting Outsourcing Turnback: Process and Issues,” ''Strategic Outsourcing: An International Journal'', 3 (3), 226-245.</ref> information technology,<ref> Lacity, M.C. and R. Hirscheim (1993), “The Information Systems Outsourcing Bandwagon,” ''Sloan Management Review'', 35 (1), 73-86.</ref> supply chain management,<ref>Bengtsson, L. and M. Dabhilkar (2009), “Manufacturing Outsourcing and it Effect on Plant Performance – Lessons from KIBS Outsourcing,” ''Journal of Evolutionary Economics'', 19 (2), 231-257. </ref><ref> Maltz, A. (1994), “Outsourcing the Warehousing Function: Economic and Strategic Considerations,” ''Logistics and Transportation Review'', 30 (3), 46-53.</ref> product assembly,<ref> Glass, A.J. and K. Saggi (2001), “Innovation and Wage Effects of International Outsourcing,” ''European Economic Review'', 45 (1), 67-86.</ref> sourcing versus production of component parts,<ref> Leiblein, M.J. and D.J. Miller (2003), “An Empirical Examination of Transaction- and firm-level Influences on the Vertical Boundaries of the Firm,” ''Strategic Management Journal'', 24 (9), 839-859.</ref> and marketing;<ref name=Anderson1985> Anderson, E. (1985), “The Salesperson as Outside Agent or Employee: A Transaction Cost Analysis,” ''Marketing Science'', 4 (3), 234-254.</ref><br />
* Is dependent on a variety of approaches including game theory,<ref>Aron, R., S. Bandyopadhyay, S. Jayanty and P. Pathak (2008), “Monitoring Process Quality in Off-shore Outsourcing: A Model and Findings from Multi-country Survey,” ''Journal of Operations Management'', 26 (2), 303-321.</ref> statistical analysis of primary and secondary data,<ref name=Anderson1988>Anderson, E. (1988), “Transaction Costs as a Determinants of Opportunism in Integrated and Independent Sales Forces,” ''Journal of Economic Behavior and Organization'', 9 (3), 247-264.</ref> experimental design,<ref>Powell Mantell, S., M. Tatikonda and Y. (2006), “A Behavioral Study of Supply Manager Decision-making: Factors Influencing the Make versus Buy Evaluation,” ''Journal of Operations Management'', 24 (6), 822-838.</ref> case analysis,<ref> Ellram, Lisa M., Wendy L. Tate, Corey Billington (2008), “Offshore Outsourcing of Professional Services: A Transaction Cost Economics Perspective,” ''Journal of Operations Management'', 26 (2), 148-163.</ref> and economic modeling;<ref> Carlton, D.W. (1979), “Vertical Integration in Competitive Markets under Uncertainty,” ''Journal of Industrial Economics'', 27 (3), 189-209.</ref> and<br />
* Has largely adopted one of two theoretical perspectives: Transaction costs economics (TCE);<ref> Coase, R. (1937), “The Nature of the Firm,” ''Economica'' N.S., 4, 386-405.</ref><ref name=Williamson1975></ref> and, more recently, the resource-based view (RBV) of the firm.<ref name=Wernerfelt1984>Wernerfelt, B. (1984), “A Resource-based View of the Firm,” ''Strategic Management Journal'', 5 (2), 62-73.</ref><ref name=Barney1991>Barney, J.B. (1991), “Firm Resources and Sustained Competitive Advantage,” ''Journal of Management'', 17 (1), 99-120.</ref><br />
<br />
==Transaction Cost Economics (TCE)==<br />
TCE is primarily concerned with explaining and predicting where various functions (e.g., product design, warehousing) will be conducted on the market (buy) – hierarchy (make) continuum.<ref name=Williamson1975></ref> The theory is reliant on two behavioral assumptions and three transaction traits.<br />
* Behavioral assumptions:<br />
** Bounded rationality refers of the inability of decision makers to fashion fully reasoned decisions due to limited information processing capability. Information asymmetry between a buyer and seller may create additional rationality problems.<br />
** Opportunism refers to adapting one’s behavior to take advantage of a specific set of circumstances. The term “guile” is often used in relation to opportunism. This refers to crafty or artful deception. For instance, an incomplete contract between a buyer and a seller may lead the seller to behave in a fashion that leads to a goal (e.g., higher profit), but is detrimental to the spirit of the exchange relationship.<br />
* Transaction trait variables:<br />
** Uncertainty refers to an inability to anticipate future states of the world. In general, uncertainty exists in the level of demand, in various processes related to production, supply chain management, and marketing, and in products themselves due to both changing consumer preferences and to innovations resulting from new product development.<br />
** Frequency is straightforward and refers to repetitive volume.<br />
** Asset specificity refers to the extent to which items used in a transaction are dedicated solely to that transaction (or repetitive transactions with the same customer or supplier). For example, a manufacturer of cheese will require refrigerated containers for shipping purposes. These containers, however, may be used to ship other dairy products as well as fresh produce and packaged meat. Specificity of the “refrigerated container” asset would thus be low as the assets may be applied to different products and buyer-seller pairs. In contrast, the assets used to unload coal at an electric utility may be dedicated to the repeated transactions between the utility and a specific vendor. In this case, the assets have little value outside of the transaction and asset specificity is therefore high. Asset specificity comes in three forms: (1) physical (as in machinery); (2) human (as in a specialized selling knowledge that cannot be applied to other products and hence customers); and (3) site specificity (related to a geographical advantage).<br />
<br />
The variables and assumptions about behavior form a complex web of concepts that explain and predict the make-versus-buy decision and relations between companies. For example, when product uncertainty is high (i.e., product churning), supplier contracts quickly lose validity due to changing component part specifications. The cost of rewriting contracts to reflect changing requirements may be excessive and detrimental to the “buy” option.<ref name=McIvor2009></ref> Outsourcing the production of component parts may lead to opportunism and the “hold-up” problem if production machinery asset specificity is high. The general tenet of TCE is that low asset specificity, uncertainty, and frequency associate with a greater likelihood of the transaction being governed by market exchange (the “buy” option) as opposed to hierarchical exchange (the “make” option, or vertical integration). Williamson<ref name=Williamson1975></ref> indicated that asset specificity should dominate uncertainty and frequency as the primary factor predicting vertical integration. Research has borne this sentiment out. Asset specificity associates with:<br />
* Internal product production;<ref> Masten, S.E. (1984), “The Organization of Production: Evidence from the Aerospace Industry,” ''Journal of Law and Economics'', 27 (2), 403-417.</ref><ref> Masten, S.E., W. Meehan and E.A. Snyder (1989), “Vertical Integration in the U.S. Auto Industry: A Note on the Influence of Transaction Specific Assets,” ''Journal of Economic Behavior and Organization'', 12 (2), 265-273.</ref><ref>Monteverde, K. (1995), “Technical Dialog as an Incentive for Vertical Integration in the Semiconductor Industry,” ''Management Science'', 41 (10), 1624-1638.</ref><ref> Monteverde, K. and D.J. Teece (1982), “Supplier Switching Costs and Vertical Integration in the Automobile Industry,” ''Bell Journal of Economics'', 13 (1), 206-213.</ref><br />
* A vertically integrated export channel;<ref name=Gatignon1988>Gatignon, H. and E. Anderson (1988), “The Multinational Corporation’s Degree of Control Over Foreign Subsidiaries: An Empirical Test of a Transaction Cost Explanation,” ''Journal of Law, Economics and Organization'', 4 (3), 305-336.</ref><ref> Klein, S., G.L. Frazier and V. Roth (1990), “A Transaction Cost Analysis Model of Channel Integration in International Markets,” ''Journal of Marketing Research'', 27 (2), 196-208.</ref><br />
* Integration into private trucking and private warehousing;<ref> Maltz, A. (1993), “Private Fleet Use: A Transaction Cost Approach,” ''Transportation Journal'', 32 (3), 46-53.</ref><ref>Maltz, A. (1994), “Outsourcing the Warehousing Function: Economic and Strategic Considerations,” ''Logistics and Transportation Review'', 30 (3), 46-53.</ref><br />
* Internal integration of computer services;<ref> Poppo, L. and T. Zenger (1998), “Testing Alternative Theories of the Firm: Transaction Cost, Knowledge-based and Measurement Explanations of make-or-buy Decisions in Information Services,” ''Strategic Management Journal'', 19 (9), 853-877.</ref><br />
* Vertical integration through the use of an in-house sales force;<ref name=Anderson1985></ref><ref> Anderson, E. and D. Schmittlein (1984), “Integration of the Sales Force: An Empirical Examination,” ''Rand Journal of Economics'', 15 (3), 385-395.</ref><br />
* And a vertically integrated channel of distribution.<ref>Anderson, E. and A.T. Coughlan (1987), “International Market Entry and Expansion via Independent or Integrated Channels of Distribution,” ''Journal of Marketing'', 51 (1), 71-81.</ref><br />
* Asset specificity has been found to interact with environmental uncertainty in predicting vertical integration<ref name=Gatignon1988></ref><br />
A number of other research studies have been undertaken that examine other elements of the TCE framework. Asset specificity is correlated positively with sales force opportunism,<ref name=Anderson1988></ref> contract complexity<ref>Reuer, J.J. and A. Arino (2007), “Strategic Alliance Contracts: Dimensions of and Determinants of Contractual Complexity,” ''Strategic Management Journal'', 28 (3), 313-330.</ref> and length,<ref>Joskow, P.L. (1987), “Contract Duration and Relationship-Specific Investments: Empirical Evidence from Coal Markets,” ''American Economic Review'', 77 (1), 168-185.</ref> time horizon alliance length,<ref>Parkhe, A. (1993), “Strategic Alliance Structuring: A Game Theoretic and Transaction Cost Examination of Interfirm Cooperation,” ''Academy of Management Journal'', 36 (4), 794-829.</ref> and supplier continuity expectation.<ref> Heide, J. and G. John (1990), “Alliances in Industrial Purchasing: The Determinants of Joint Action in Buyer-Seller Relationships,” ''Journal of Marketing Research'', 27 (1), 24-36.</ref> Vertical integration is more likely when the fraction of total cost represented by a specific input<ref>Lieberman, M.B. (1991), “Determinants of Vertical Integration: An Empirical Test,” ''Journal of Industrial Economics'', 39 (5), 541-466.</ref> and product complexity<ref name=Moschuris2007></ref> are high.<br />
<br />
==Resource-based View (RBV)==<br />
The RBV aspires to explain and competitive advantage through analysis firm resources. Wernerfelt defined a resource as “anything which could be thought of a strength or weakness of a given firm.”<ref name=Wernerfelt1984></ref> Barney built upon this, stating that a resource “includes all assets, capabilities, organizational processes, firm attributes, information knowledge, etc., controlled by a firm that enable the firm to conceive of and implement strategies that improve its efficiency and effectiveness.”<ref name=Barney1991></ref> Specifically:<br />
* A competitive advantage is derived when a firm implements a value enhancing strategy not implemented by competitors;<br />
* A sustained competitive advantage is derived when a value enhancing strategy is not implemented by competitors and when competitors are unable to copy the strategy’s benefits;<br />
* A major assumption is that firm resources within an industry may be heterogeneous and immobile;<br />
* Four resource traits drive the ability to generate a sustained competitive advantage:<br />
** Valuable: A resource may lead to a competitive advantage if it is valuable. The firm must be able to apply the resource to take advantage of an opportunity or to thwart a threat;<br />
** Rarity: A resource should be rare in that if all firms in an industry possess a valuable resource, then the ability to create a sustained advantage is limited;<br />
** Imperfectly imitable: A resource should be difficult to copy. Three forces drive this imperfection: (1) long term historical conditions specific to the firm (2) the connection between the competitive advantage and the resource is fuzzy and not well understood (causal ambiguity); and (3) the resource is highly complex from a social perspective;<br />
** Substitutability: there exist no substitute resources that act as proxies for the original resource.<ref name=Barney1991></ref><br />
The application of the RBV to the make-versus-buy decision is more recent and limited relative to the application of TCE. Idiosyncratic investments by the firm in the form of shared knowledge routines with suppliers and customers<ref> Holcomb, Tim R., and Michael A. Hitt (2007), “Toward a Model of Strategic Outsourcing,” Journal of Operations Management, 25 (2), 464-481.</ref> and relationship building,<ref> Madhok, A. and S.B. Tallman (1998), “Resources, Transactions, and Rents: Managing Value Through Interfirm Collaborative Relationships,” Organization Science, 9 (3), 326-339.</ref> both of which are treated as resources, may positively affect the performance of outsourcing efforts. Performance, in terms of product quality, improved continually when component design and production was retained in-house. Firms that outsourced the same process immediately reaped the rewards of partnering with leading outsourcers, however quality performance remained flat across time. The explanation is in-house work allowed adaptive, feedback behaviors and knowledge acquisition (resource), while outsourced work tapped the extant knowledge of the partner, but never allowed the client firm to acquire knowledge itself.<ref> Novak, S. and S. Stern (2008), “How does Outsourcing Affect Performance Dynamics? Evidence from the Automobile Industry,” Management Science, 54 (12), 1963-1979.</ref> Pharmaceutical businesses are more likely to outsource clinical trials when the purpose is the production data from and they are less likely to outsource clinical trials when the purpose is the production of knowledge (a resource).<ref>Azoulay, P. (2004), “Capturing Knowledge within and across Firm Boundaries: Evidence from Clinical Development,” American Economic Review, 94 (5), 1591-1612.</ref> The effective adoption of fleet monitoring technology (a resource) associates with shippers integrating into private carriage<ref name=Baker2003></ref><br />
<br />
==Practical Implications==<br />
According to Chopra and Mendl,<ref>Chopra, S. and P. Mendl (2007), ''Supply Chain Management: Strategy, Planning, and Operations'', Upper Saddle River, NJ: Pearson. </ref> outsourcing is feasible if the supply chain surplus can be increased without affecting risk for the client company. The supply chain surplus equals the difference between the value of the product to the end-user and all supply chain costs. The supply chain surplus thus equals the supply chain profit. In general, a third party (or contractor) can increase the supply chain surplus if they can combine activities or processes across customers (or clients) such that the scale of the contractor efforts and their size provide benefits that exceed what the client firm is capable of by itself. Combining activities and processes across potential clients may be accomplished through a combination one or more of the following functions:<br />
* Combining Production Capacity: A contractor can generate economies of scale in production by combining small scale requirements of indvividual clients into significantly larger facilities.<br />
* Combining Transportation Assets: A contractor may combine the transportation asset and management requirements of a large number of clients, thereby creating sigificant scale and learning effects. Examples include DHL, UPS, and Deutsche Bahn Mobility Logistics.<br />
* Combining Warehouse Assets: Again, the assets needs of clients may be aggregated by a contractor to a higher level thereby creating scale effects.<br />
* Combining Knowledge and Learning: A contractor may offer specialized services and combine the service requirements across clients. Potential clients lack the scale required to invest and generate a return on these specialized services. Examples include customs brokerage, inventory management services, and network design services.<br />
<br />
The largest outsourcing contractors offer a wide variety of services to potential clients and create customized packages. The ability of a contractor to take advantage of the supply chain surplus and the reduction of risk by the client follow from the three critical transaction variables identified by TCE and from RBV insights:<br />
* Asset Specificity: A high level of asset specificty on the part of a specific client reduces the ability of the outsourcing contractor to combine the functions, activities, and processes with other clients. This reduces the ability of the contractor to create scale effects. Furthermore, client risk may increase due to the potential for opportunistic behavior by the contractor. The large body of research supporting the connection between asset specifcity and the lack of vertical integration and/or outsourcing empirically supports the difficultes in outsourcing when asset specifcity is high.<br />
* Frequency and Scale: Although higher transaction frequency and certainty on the part of the client would seem to reduce the ability of a contractor to create supply chain surplus and thus favor vertical integration, TCE research does not provide consistent support. In practice, we can identify large clients that outsource a signifcant part of their supply chain operations: e.g., HP with UPS Supply Chain Solutions. The supply chain asset specificity of these large clients is typically low.<br />
* The decision to outsource is frequently couched in terms of whether a process or function represents a core capability. The RBV would advocate that the critical factor is whether the resources behind a function or process lead to a long term sustained competitive advantage. If so, then the firm should put let of an emphsasis on outsourcing.<br />
<br />
While a nubmber of benefits are assicated with outsourcing, risks and problems may be present.<br />
* Several industry experts have advocated that outsourcing a broken or ill-conceived process does not solve the problem. Rather, the broken process is simply outsourced and may be more difficult to manage from a remote distance.<br />
* Contracting is critical to the succes of an outsourcing arrangement. As mentioned before, contracts seem to behave as respoitories of knowledge, however, they are much more in terms of setting expectations, controlling opportunistic behavior, and regulating price and volume. A senior manager at UPS Supply Chain Solutions has said that "the most important elements of a contract are the performance measures."<ref>Brian Carrier, UPS-SCS, personal conversation with the author (2010).</ref> Shared and detailed performance metrics allow the parties to create a common knowledge base and shared expectations (thereby building trust) while simultanesouly reducing opportunism.<br />
* Outsourcing may result in the contractor increasing and improving their knowledge base relative to that of the client, whose knowledge base may remain static. There are several fashions in which knowledge (a resource) may be impacted by outsourcing. A contractor may take over specific marketing functions and thus the client's knowledge about certain aspects of the market is not direct, but filtered through the contractor. A contractor may provide immediate access to frontier knowledge in product design, however, across time the client fails to build additional product resources that might lead to a long term sustained competitive advantage.<br />
* Despite effective contracts, outsourcing may associate with higher than expected coordination costs. This is a fundamental TCE concept. Market, hybrid, and vertcial integation modes all consume coordination costs. The issue is how these costs for each of the contractor and client are balanced against the risks and the increase in the supply chain surplus.<br />
* A 2008 Deloitte Consulting report<ref>WhySettle for Less? http://www.deloitte.com/assets/Dcom-Albania/Local%20Assets/Documents/ce_cons_outs_report_08(2).pdf</ref> on the results of a survey of 300 businesses found that:<br />
** 39% of respondents had, at some during their career, cancelled an outsourcing contract and shifted to another vendor.<br />
** Functions had been in-sourced 50% of the time when managers were disatisfied with an outsourcing arrangement. These same dissatified managers realized that more time should have been spent on vendor evaluation (55%) and that more time should have been spend on defining key performance measures (49%).<br />
** Outsouring problem resolution had been pushed up to senior management 61% of the time during the first year of an outsourcing contract, although this percentage diminished across time.<br />
** Despite these problems, the majority stated that ROI goals had been met. <br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Purchasing & Sourcing]]</div>Storchhttp://scm.gsom.spbu.ru/OutsourcingOutsourcing2011-08-19T10:03:19Z<p>Storch: </p>
<hr />
<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Аутсорсинг Аутсорсинг!]'''<br />
<br />
While global statistics are difficult to come by on the scale of outsourcing, a Frost & Sullivan 2005 consulting report stated that the global market for outsourcing by Global Fortune 500 companies was valued at US $648 billion in 2004, a figure expected to increase to US $920 billion by 2007.<ref>Shared Services and Outsourcing (SSO): Hub Potential Analysis (Abridged by Select Verticals) (2005), http://www.mscmalaysia.my/codenavia/portals/msc/images/pdf/awards_accolades/frost_sullivan_sso.pdf.</ref> The “true” global market for all outsourcing at the current point in time is very likely to be much higher owing to growth, to definitional issues that would seem to omit much of what passes for outsourcing, and to the omission of firms lesser in scale. No review of outsourcing could ignore the definitional problem. A commonly held definition states that outsourcing is concerned with performing activities outside the firm that were previously and normally conducted within the firm.<ref name=McIvor2009>McIvor, R. (2009), “How the Transaction Cost and Resource-based Theories of the Firm Inform Outsourcing Evaluation,” ''Journal of Operations Management'', 27 (1), 45-63.</ref> The problem with this definition is that no clear distinction exists with the make-versus-buy decision. The make-versus-buy decision is very similar to functional spin-off and vertical integration. The make-versus-buy decision examines the choice of governance with market transactions at one end of the spectrum, hierarchies (or vertical integration) at the other end,<ref name=Williamson1975> Williamson, O.E. (1975), ''Markets and Hierarchies'', Free Press, New York. </ref> and with hybrid, alliance-type exchange as an intermediate form. Functional spin-off is a marketing term that may be defined as the subcontracting of a marketing function by a channel intermediary to another intermediary.<ref>Mallen, B. (1973), “Functional Spin-Off: A Key to Anticipating Change in a Distribution Channel,” ''Journal of Marketing'', 37 (3), 18-25.</ref> Spinning-off a function and shifting it a third party is essentially equivalent to the “buy” option of the make-versus-buy decision. One further problem with the common definition of outsourcing concerns the notion that innovations in communications, information and production technologies, products and component parts, transportation systems, and material handling equipment shift underlying cost structures, thereby increasing (or decreasing) the appeal of various make-versus-buy alternatives. Furthermore, these innovations foster new behaviors, practices, and, more important, new functions and processes that the firm must assess and decide whether to perform in-house (i.e., to integrate vertically) or to outsource (either to a market or through a hybrid form of exchange). A clear example is the infusion of electronics into automobliles -- at some point in time, manufacturers had to decide who would design, manufacture, integrate, and distribute the new and previously undreampt of innovation. In the search for efficiency and effectiveness, firms are in a constant state of flux as they experiment with alternatives that selectively increase or decrease the boundaries of the firm. Research on outsourcing, vertical integration, and the boundaries of the firm:<br />
* Has been conducted in a variety of settings including manufacturing,<ref> Ashwin, W.J. and R.L. Stump (1999), “The Contingent Effect of Specific Asset Investments on Joint Action in Manufacturer-Supplier Relationships: An Empirical Test of the Moderating Role of Reciprocal Asset Investments, Uncertainty, and Trust,” ''Journal of the Academy of Marketing Science'', 27 (3), 291-306.</ref> healthcare,<ref name=Moschuris2007> Moschuris, S.J. and M.N. Kondylis (2007), “Outsourcing in Private Healthcare Organisations: A Greek Perspective,” ''Journal of Health Organization Management'', 21 (2), 220-223.</ref> agriculture,<ref> Gillespie, J., R. Henring, C. Sandretto, and C. Hallahan (2007), “Forage Outsourcing in the Dairy Sector: The Extent of Use and Impact on Farm Profitability,” ''Agricultural and Resource Economics Review'', 39 (3), 399-414.</ref> transportation carriers,<ref name=Baker2003> Baker, G.P. and T.N. Hubbard (2003), “Make versus Buy in Trucking: Asset Ownership, Job Design, and Information,” ''American Economic Review'', 93 (3), 551-572.</ref> and chain restaurants;<ref> Combs, J.G. and D.J. Ketchen (1999), “Explaining Inter-firm Cooperation and Performance: Toward A Reconciliation of Predictions From the Resource-based View and Organizational Economics,” ''Strategic Management Journal'', 20 (9), 435-450.</ref><br />
* Has been applied to various functions including accounting,<ref> Maelah, R., A. Aman, N. Hamzah, R. Amiruddin and S.M. Auzair (2010), “Accounting Outsourcing Turnback: Process and Issues,” ''Strategic Outsourcing: An International Journal'', 3 (3), 226-245.</ref> information technology,<ref> Lacity, M.C. and R. Hirscheim (1993), “The Information Systems Outsourcing Bandwagon,” ''Sloan Management Review'', 35 (1), 73-86.</ref> supply chain management,<ref>Bengtsson, L. and M. Dabhilkar (2009), “Manufacturing Outsourcing and it Effect on Plant Performance – Lessons from KIBS Outsourcing,” ''Journal of Evolutionary Economics'', 19 (2), 231-257. </ref><ref> Maltz, A. (1994), “Outsourcing the Warehousing Function: Economic and Strategic Considerations,” ''Logistics and Transportation Review'', 30 (3), 46-53.</ref> product assembly,<ref> Glass, A.J. and K. Saggi (2001), “Innovation and Wage Effects of International Outsourcing,” ''European Economic Review'', 45 (1), 67-86.</ref> sourcing versus production of component parts,<ref> Leiblein, M.J. and D.J. Miller (2003), “An Empirical Examination of Transaction- and firm-level Influences on the Vertical Boundaries of the Firm,” ''Strategic Management Journal'', 24 (9), 839-859.</ref> and marketing;<ref name=Anderson1985> Anderson, E. (1985), “The Salesperson as Outside Agent or Employee: A Transaction Cost Analysis,” ''Marketing Science'', 4 (3), 234-254.</ref><br />
* Is dependent on a variety of approaches including game theory,<ref>Aron, R., S. Bandyopadhyay, S. Jayanty and P. Pathak (2008), “Monitoring Process Quality in Off-shore Outsourcing: A Model and Findings from Multi-country Survey,” ''Journal of Operations Management'', 26 (2), 303-321.</ref> statistical analysis of primary and secondary data,<ref name=Anderson1988>Anderson, E. (1988), “Transaction Costs as a Determinants of Opportunism in Integrated and Independent Sales Forces,” ''Journal of Economic Behavior and Organization'', 9 (3), 247-264.</ref> experimental design,<ref>Powell Mantell, S., M. Tatikonda and Y. (2006), “A Behavioral Study of Supply Manager Decision-making: Factors Influencing the Make versus Buy Evaluation,” ''Journal of Operations Management'', 24 (6), 822-838.</ref> case analysis,<ref> Ellram, Lisa M., Wendy L. Tate, Corey Billington (2008), “Offshore Outsourcing of Professional Services: A Transaction Cost Economics Perspective,” ''Journal of Operations Management'', 26 (2), 148-163.</ref> and economic modeling;<ref> Carlton, D.W. (1979), “Vertical Integration in Competitive Markets under Uncertainty,” ''Journal of Industrial Economics'', 27 (3), 189-209.</ref> and<br />
* Has largely adopted one of two theoretical perspectives: Transaction costs economics (TCE);<ref> Coase, R. (1937), “The Nature of the Firm,” ''Economica'' N.S., 4, 386-405.</ref><ref name=Williamson1975></ref> and, more recently, the resource-based view (RBV) of the firm.<ref name=Wernerfelt1984>Wernerfelt, B. (1984), “A Resource-based View of the Firm,” ''Strategic Management Journal'', 5 (2), 62-73.</ref><ref name=Barney1991>Barney, J.B. (1991), “Firm Resources and Sustained Competitive Advantage,” ''Journal of Management'', 17 (1), 99-120.</ref><br />
<br />
==Transaction Cost Economics (TCE)==<br />
TCE is primarily concerned with explaining and predicting where various functions (e.g., product design, warehousing) will be conducted on the market (buy) – hierarchy (make) continuum.<ref name=Williamson1975></ref> The theory is reliant on two behavioral assumptions and three transaction traits.<br />
* Behavioral assumptions:<br />
** Bounded rationality refers of the inability of decision makers to fashion fully reasoned decisions due to limited information processing capability. Information asymmetry between a buyer and seller may create additional rationality problems.<br />
** Opportunism refers to adapting one’s behavior to take advantage of a specific set of circumstances. The term “guile” is often used in relation to opportunism. This refers to crafty or artful deception. For instance, an incomplete contract between a buyer and a seller may lead the seller to behave in a fashion that leads to a goal (e.g., higher profit), but is detrimental to the spirit of the exchange relationship.<br />
* Transaction trait variables:<br />
** Uncertainty refers to an inability to anticipate future states of the world. In general, uncertainty exists in the level of demand, in various processes related to production, supply chain management, and marketing, and in products themselves due to both changing consumer preferences and to innovations resulting from new product development.<br />
** Frequency is straightforward and refers to repetitive volume.<br />
** Asset specificity refers to the extent to which items used in a transaction are dedicated solely to that transaction (or repetitive transactions with the same customer or supplier). For example, a manufacturer of cheese will require refrigerated containers for shipping purposes. These containers, however, may be used to ship other dairy products as well as fresh produce and packaged meat. Specificity of the “refrigerated container” asset would thus be low as the assets may be applied to different products and buyer-seller pairs. In contrast, the assets used to unload coal at an electric utility may be dedicated to the repeated transactions between the utility and a specific vendor. In this case, the assets have little value outside of the transaction and asset specificity is therefore high. Asset specificity comes in three forms: (1) physical (as in machinery); (2) human (as in a specialized selling knowledge that cannot be applied to other products and hence customers); and (3) site specificity (related to a geographical advantage).<br />
<br />
The variables and assumptions about behavior form a complex web of concepts that explain and predict the make-versus-buy decision and relations between companies. For example, when product uncertainty is high (i.e., product churning), supplier contracts quickly lose validity due to changing component part specifications. The cost of rewriting contracts to reflect changing requirements may be excessive and detrimental to the “buy” option.<ref name=McIvor2009></ref> Outsourcing the production of component parts may lead to opportunism and the “hold-up” problem if production machinery asset specificity is high. The general tenet of TCE is that low asset specificity, uncertainty, and frequency associate with a greater likelihood of the transaction being governed by market exchange (the “buy” option) as opposed to hierarchical exchange (the “make” option, or vertical integration). Williamson<ref name=Williamson1975></ref> indicated that asset specificity should dominate uncertainty and frequency as the primary factor predicting vertical integration. Research has borne this sentiment out. Asset specificity associates with:<br />
* Internal product production;<ref> Masten, S.E. (1984), “The Organization of Production: Evidence from the Aerospace Industry,” ''Journal of Law and Economics'', 27 (2), 403-417.</ref><ref> Masten, S.E., W. Meehan and E.A. Snyder (1989), “Vertical Integration in the U.S. Auto Industry: A Note on the Influence of Transaction Specific Assets,” ''Journal of Economic Behavior and Organization'', 12 (2), 265-273.</ref><ref>Monteverde, K. (1995), “Technical Dialog as an Incentive for Vertical Integration in the Semiconductor Industry,” ''Management Science'', 41 (10), 1624-1638.</ref><ref> Monteverde, K. and D.J. Teece (1982), “Supplier Switching Costs and Vertical Integration in the Automobile Industry,” ''Bell Journal of Economics'', 13 (1), 206-213.</ref><br />
* A vertically integrated export channel;<ref name=Gatignon1988>Gatignon, H. and E. Anderson (1988), “The Multinational Corporation’s Degree of Control Over Foreign Subsidiaries: An Empirical Test of a Transaction Cost Explanation,” ''Journal of Law, Economics and Organization'', 4 (3), 305-336.</ref><ref> Klein, S., G.L. Frazier and V. Roth (1990), “A Transaction Cost Analysis Model of Channel Integration in International Markets,” ''Journal of Marketing Research'', 27 (2), 196-208.</ref><br />
* Integration into private trucking and private warehousing;<ref> Maltz, A. (1993), “Private Fleet Use: A Transaction Cost Approach,” ''Transportation Journal'', 32 (3), 46-53.</ref><ref>Maltz, A. (1994), “Outsourcing the Warehousing Function: Economic and Strategic Considerations,” ''Logistics and Transportation Review'', 30 (3), 46-53.</ref><br />
* Internal integration of computer services;<ref> Poppo, L. and T. Zenger (1998), “Testing Alternative Theories of the Firm: Transaction Cost, Knowledge-based and Measurement Explanations of make-or-buy Decisions in Information Services,” ''Strategic Management Journal'', 19 (9), 853-877.</ref><br />
* Vertical integration through the use of an in-house sales force;<ref name=Anderson1985></ref><ref> Anderson, E. and D. Schmittlein (1984), “Integration of the Sales Force: An Empirical Examination,” ''Rand Journal of Economics'', 15 (3), 385-395.</ref><br />
* And a vertically integrated channel of distribution.<ref>Anderson, E. and A.T. Coughlan (1987), “International Market Entry and Expansion via Independent or Integrated Channels of Distribution,” ''Journal of Marketing'', 51 (1), 71-81.</ref><br />
* Asset specificity has been found to interact with environmental uncertainty in predicting vertical integration<ref name=Gatignon1988></ref><br />
A number of other research studies have been undertaken that examine other elements of the TCE framework. Asset specificity is correlated positively with sales force opportunism,<ref name=Anderson1988></ref> contract complexity<ref>Reuer, J.J. and A. Arino (2007), “Strategic Alliance Contracts: Dimensions of and Determinants of Contractual Complexity,” ''Strategic Management Journal'', 28 (3), 313-330.</ref> and length,<ref>Joskow, P.L. (1987), “Contract Duration and Relationship-Specific Investments: Empirical Evidence from Coal Markets,” ''American Economic Review'', 77 (1), 168-185.</ref> time horizon alliance length,<ref>Parkhe, A. (1993), “Strategic Alliance Structuring: A Game Theoretic and Transaction Cost Examination of Interfirm Cooperation,” ''Academy of Management Journal'', 36 (4), 794-829.</ref> and supplier continuity expectation.<ref> Heide, J. and G. John (1990), “Alliances in Industrial Purchasing: The Determinants of Joint Action in Buyer-Seller Relationships,” ''Journal of Marketing Research'', 27 (1), 24-36.</ref> Vertical integration is more likely when the fraction of total cost represented by a specific input<ref>Lieberman, M.B. (1991), “Determinants of Vertical Integration: An Empirical Test,” ''Journal of Industrial Economics'', 39 (5), 541-466.</ref> and product complexity<ref name=Moschuris2007></ref> are high.<br />
<br />
==Resource-based View (RBV)==<br />
The RBV aspires to explain and competitive advantage through analysis firm resources. Wernerfelt defined a resource as “anything which could be thought of a strength or weakness of a given firm.”<ref name=Wernerfelt1984></ref> Barney built upon this, stating that a resource “includes all assets, capabilities, organizational processes, firm attributes, information knowledge, etc., controlled by a firm that enable the firm to conceive of and implement strategies that improve its efficiency and effectiveness.”<ref name=Barney1991></ref> Specifically:<br />
* A competitive advantage is derived when a firm implements a value enhancing strategy not implemented by competitors;<br />
* A sustained competitive advantage is derived when a value enhancing strategy is not implemented by competitors and when competitors are unable to copy the strategy’s benefits;<br />
* A major assumption is that firm resources within an industry may be heterogeneous and immobile;<br />
* Four resource traits drive the ability to generate a sustained competitive advantage:<br />
** Valuable: A resource may lead to a competitive advantage if it is valuable. The firm must be able to apply the resource to take advantage of an opportunity or to thwart a threat;<br />
** Rarity: A resource should be rare in that if all firms in an industry possess a valuable resource, then the ability to create a sustained advantage is limited;<br />
** Imperfectly imitable: A resource should be difficult to copy. Three forces drive this imperfection: (1) long term historical conditions specific to the firm (2) the connection between the competitive advantage and the resource is fuzzy and not well understood (causal ambiguity); and (3) the resource is highly complex from a social perspective;<br />
** Substitutability: there exist no substitute resources that act as proxies for the original resource.<ref name=Barney1991></ref><br />
The application of the RBV to the make-versus-buy decision is more recent and limited relative to the application of TCE. Idiosyncratic investments by the firm in the form of shared knowledge routines with suppliers and customers<ref> Holcomb, Tim R., and Michael A. Hitt (2007), “Toward a Model of Strategic Outsourcing,” Journal of Operations Management, 25 (2), 464-481.</ref> and relationship building,<ref> Madhok, A. and S.B. Tallman (1998), “Resources, Transactions, and Rents: Managing Value Through Interfirm Collaborative Relationships,” Organization Science, 9 (3), 326-339.</ref> both of which are treated as resources, may positively affect the performance of outsourcing efforts. Performance, in terms of product quality, improved continually when component design and production was retained in-house. Firms that outsourced the same process immediately reaped the rewards of partnering with leading outsourcers, however quality performance remained flat across time. The explanation is in-house work allowed adaptive, feedback behaviors and knowledge acquisition (resource), while outsourced work tapped the extant knowledge of the partner, but never allowed the client firm to acquire knowledge itself.<ref> Novak, S. and S. Stern (2008), “How does Outsourcing Affect Performance Dynamics? Evidence from the Automobile Industry,” Management Science, 54 (12), 1963-1979.</ref> Pharmaceutical businesses are more likely to outsource clinical trials when the purpose is the production data from and they are less likely to outsource clinical trials when the purpose is the production of knowledge (a resource).<ref>Azoulay, P. (2004), “Capturing Knowledge within and across Firm Boundaries: Evidence from Clinical Development,” American Economic Review, 94 (5), 1591-1612.</ref> The effective adoption of fleet monitoring technology (a resource) associates with shippers integrating into private carriage<ref name=Baker2003></ref><br />
<br />
==Practical Implications==<br />
According to Chopra and Mendl,<ref>Chopra, S. and P. Mendl (2007), ''Supply Chain Management: Strategy, Planning, and Operations'', Upper Saddle River, NJ: Pearson. </ref> outsourcing is feasible if the supply chain surplus can be increased without affecting risk for the client company. The supply chain surplus equals the difference between the value of the product to the end-user and all supply chain costs. The supply chain surplus thus equals the supply chain profit. In general, a third party (or contractor) can increase the supply chain surplus if they can combine activities or processes across customers (or clients) such that the scale of the contractor efforts and their size provide benefits that exceed what the client firm is capable of by itself. Combining activities and processes across potential clients may be accomplished through a combination one or more of the following functions:<br />
* Combining Production Capacity: A contractor can generate economies of scale in production by combining small scale requirements of indvividual clients into significantly larger facilities.<br />
* Combining Transportation Assets: A contractor may combine the transportation asset and management requirements of a large number of clients, thereby creating sigificant scale and learning effects. Examples include DHL, UPS, and Deutsche Bahn Mobility Logistics.<br />
* Combining Warehouse Assets: Again, the assets needs of clients may be aggregated by a contractor to a higher level thereby creating scale effects.<br />
* Combining Knowledge and Learning: A contractor may offer specialized services and combine the service requirements across clients. Potential clients lack the scale required to invest and generate a return on these specialized services. Examples include customs brokerage, inventory management services, and network design services.<br />
<br />
The largest outsourcing contractors offer a wide variety of services to potential clients and create customized packages. The ability of a contractor to take advantage of the supply chain surplus and the reduction of risk by the client follow from the three critical transaction variables identified by TCE and from RBV insights:<br />
* Asset Specificity: A high level of asset specificty on the part of a specific client reduces the ability of the outsourcing contractor to combine the functions, activities, and processes with other clients. This reduces the ability of the contractor to create scale effects. Furthermore, client risk may increase due to the potential for opportunistic behavior by the contractor. The large body of research supporting the connection between asset specifcity and the lack of vertical integration and/or outsourcing empirically supports the difficultes in outsourcing when asset specifcity is high.<br />
* Frequency and Scale: Although higher transaction frequency and certainty on the part of the client would seem to reduce the ability of a contractor to create supply chain surplus and thus favor vertical integration, TCE research does not provide consistent support. In practice, we can identify large clients that outsource a signifcant part of their supply chain operations: e.g., HP with UPS Supply Chain Solutions. The supply chain asset specificity of these large clients is typically low.<br />
* The decision to outsource is frequently couched in terms of whether a process or function represents a core capability. The RBV would advocate that the critical factor is whether the resources behind a function or process lead to a long term sustained competitive advantage. If so, then the firm should put let of an emphsasis on outsourcing.<br />
<br />
While a nubmber of benefits are assicated with outsourcing, risks and problems may be present.<br />
* Several industry experts have advocated that outsourcing a broken or ill-conceived process does not solve the problem. Rather, the broken process is simply outsourced and may be more difficult to manage from a remote distance.<br />
* Contracting is critical to the succes of an outsourcing arrangement. As mentioned before, contracts seem to behave as respoitories of knowledge, however, they are much more in terms of setting expectations, controlling opportunistic behavior, and regulating price and volume. A senior manager at UPS Supply Chain Solutions has said that "the most important elements of a contract are the performance measures."<ref>Brian Carrier, UPS-SCS, personal conversation with the author (2010).</ref> Shared and detailed performance metrics allow the parties to create a common knowledge base and shared expectations (thereby building trust) while simultanesouly reducing opportunism.<br />
* Outsourcing may result in the contractor increasing and improving their knowledge base relative to that of the client, whose knowledge base may remain static. There are several fashions in which knowledge (a resource) may be impacted by outsourcing. A contractor may take over specific marketing functions and thus the client's knowledge about certain aspects of the market is not direct, but filtered through the contractor. A contractor may provide immediate access to frontier knowledge in product design, however, across time the client fails to build additional product resources that might lead to a long term sustained competitive advantage.<br />
* Despite effective contracts, outsourcing may associate with higher than expected coordination costs. This is a fundamental TCE concept. Market, hybrid, and vertcial integation modes all consume coordination costs. The issue is how these costs for each of the contractor and client are balanced against the risks and the increase in the supply chain surplus.<br />
* A 2008 Deloitte Consulting report<ref>WhySettle for Less? http://www.deloitte.com/assets/Dcom-Albania/Local%20Assets/Documents/ce_cons_outs_report_08(2).pdf</ref> on the results of a survey of 300 businesses found that:<br />
** 39% of respondents had, at some during their career, cancelled an outsourcing contract and shifted to another vendor.<br />
** Functions had been in-sourced 50% of the time when managers were disatisfied with an outsourcing arrangement. These same dissatified managers realized that more time should have been spent on vendor evaluation (55%) and that more time should have been spend on defining key performance measures (49%).<br />
** Outsouring problem resolution had been pushed up to senior management 61% of the time during the first year of an outsourcing contract, although this percentage diminished across time.<br />
** Despite these problems, the majority stated that ROI goals had been met. <br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Purchasing & Sourcing]]</div>Storchhttp://scm.gsom.spbu.ru/Supplier_evaluation_and_developmentSupplier evaluation and development2011-08-17T18:51:46Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Оценка_и_развитие_поставщика Оценка и развитие поставщика]'''<br />
<br />
Supplier evaluation and supplier development may be throught of as a two-step process toward the improvement of the sourcing and purchasing function. The importance of sourcing is driven by the fact that in many manufacturing businesses, the cost of purchased materials often accounts for up to 50% of the cost of goods sold.<ref>http://www.handsongroup.com/lean-articles/lean-supplier-evaluation-checklist</ref> Supplier evaluation is essentially a system for scoring the competencies of suppliers so that buyers are able to select more qualified vendors. Supplier development is a tool to encourage suppliers to engage in continuous quality and process improvement so that key performance metrics of the firm's supply base (e.g., lead time) continually improve. A review of 76 research papers studying supplier evaluation revealed that the most important evaluation criteria were:<br />
* Product quality<br />
* Delivery: e.g., [[lead time]]; on-time delivery<br />
* Cost (or price)<ref>Thanaraksakul, W. and B. Phruksaphanrat (2009), "Supplier Evaluation Framework Based on Balanced Scorecard with Integrated Corporate Social Responsibility Perspective," Proceedings of the MultiConference of Engineers and Computer Scientists, Volume 2, March 18-20, Hong Kong</ref><br />
<br />
In addition to these critical supplier evaluation criteria, a number of other important factors have been identified. These include:<br />
* Supplier flexibility: The extent to which a supplier can handle various changes including alterations in units ordered and in-transit adjustments to destinations without sacrificing cost and quality<br />
* Lot size requirements and frequency: Higher minimum lot sizes requirements and low frequency may affect [[inventory carrying cost]] as both cycle and safety stock may increase<br />
* Financial stability of the supplier: This is of great importance for critical parts/materials, especially when the planned or actual number of suppliers is low. The importance declines for common inputs or commodities when the available pool of suppliers is large<br />
* Supplier information coordination skills: Capabilities in both the form of communication (e.g., [[EDI]]) and in the substance (e.g., the ability of a supplier to integrate the buyer's production plans into their schedules) is of importance. More integrated coordination drives down various functional costs and provide additional revenue opportunities. For example, supply chain coordination at various levels may: <br />
** Reduce costs: The [[bullwhip effect]] may be controlled, thereby driving down safety stock and inventory carrying cost<br />
** Increase revenue: Better coordination allows more effective matching of supply to demand (e.g., through CPFR), thereby reducing forced markdowns and the cost of lost sales<br />
* Supplier engineering/design skills: Suppliers that are able to share design expertise influence total cost as expertise may be applied to designing products for manufacturability<ref>Chopra, S and P. Mendl (2007), ''Supply Chain Management: Strategy, Planning and Operation'', Upper Saddle River, New Jersey: Pearson.</ref><br />
<br />
==Supplier Development==<br />
Supplier development may be defined as "any effort of a firm to increase performance and/or capabilities to meet the firm's short- and long-term supply needs."<ref name=Krause1997>Krause, D.R. (1997), "Supplier Development: Current Practices and Outcomes," ''International Journal of Purchasing and Materials Management'', 33(2), 12-19.</ref> From a study of 527 purchasing managers, a rank order of the five most frequently used supplier development tools (out of 14 tools) were:<br />
* Provision of of feedback to suppliers on supplier evalution results<br />
* Site visits by supplier personnel to buyer facilities to better understand the use of the parts, materials, and/or components<br />
* Site visits by buyer personnel to supplier facilities help improve supplier performance<br />
* Written or verbal requests by the buyer to the supplier indicating improved performance requirements<br />
* Promise of future benefits.<ref name=Krause1997></ref><br />
The 14 tools were grouped into three factors of supplier development:<br />
* Direct firm involvement: e.g., site visits<br />
* Incentives: e.g., promises of more business<br />
* Competition: e.g., use of multiple vendors<br />
The same research indicated that managers believed that defect rates, on-time delivery, [[lead time]], and the [[perfect order rate]] had all improved due to supplier development programs. Also, managers perceived that the long-term orientation of the exchange relationship with the vendor had increased due to supplier development programs. Other research has also provided a link between supplier development programs and performance. Supplier incentives and supplier evaluation associate with more direct involvement (e.g., site visits), which in turn associates with improved supplier performance.<ref>Krause, D.R., T.V. Scannell, and R.J. Calantone (2000), "A Structural Analysis of the Effectiveness of Buying Firms' Strategies to Improve Supplier Performance," ''Decision Science'', 31 (1), 33-55.</ref> Buyer commitment to and shared values with suppliers predict managerial ratings on organizational cost reduction performance, however, buyer commitment to suppliers and supplier development programs predict managerial ratings on organizational improvement in product quality and supplier delivery performance.<ref>Krause, D.R., R.B. Handfield, and B>b> Tyler (2007), "The Relationships between Supplier Development, Commitment, Social Capital Accumulation and Performance Improvement," ''Journal of Operations Management'', 25 (2), 528-545.</ref> Furthermore, higher asset specificity (see [[outsourcing]]) in terms of direct involvement with a specific supplier (meaning that such efforts have little value with another supplier), the more the buyer trusts the supplier, and the more the supplier applies strategic resources to the relationship with the buyer, the better the supplier performance: e.g., lead time, quality levels.<ref>Humphreys, P.K., W.L. Li, and L.Y. Chan (2004), "The Impact of Supplier Development on Buyer-Supplier Relationships," ''Omega'', 32 (2), 131-143.</ref><br />
<br />
<br />
In practice, a large number of businesses operate supplier development programs. For example, Intel sourced locally when entering the Malaysian market in 1972 and thus embarked on a seven step supplier development program that started with indentifying capable and willing suppliers and ended with a supplier acquiring ''global supplier status''.<ref>http://www.rvr.aim.edu/fckeditor2/userfiles/file/publications/Intel%20Case%20Book/13_C%20Intel%20SCM%20Malaysia%20CAse.pdf</ref> The international importance of supplier development is reflected by the publication by the United Nations of a ''Guide to Supplier Development'' to assist contractors in developing countries to acquire supply arrangements with large multinational enterprises.<ref>http://www.unido.org/fileadmin/import/9607_GuidetoSupplierDevelopment.pdf</ref>. At a national level, many countries enact local content rules as a condition of market access. For example, Russian Decree 166 (of 2005)<ref>http://www.rotobo.or.jp/events/forum/presentation/1-4-01Babiner.pdf</ref> provided various economic incentives to automobile manufacturers loacted in Russia to increase local content. These sorts of initiatives not only encourage established foreign suppliers to invest in the host country, but also lead the manufacturer to develop local suppliers to meet quality, delivery, and cost requirements.<ref>http://www.just-auto.com/interview/fords-man-in-st-petersburg_id92523.aspx</ref> Furthermore, a range of supplier development programs are designed to further social justice, often in response to government legislation or from pressure by socially oriented non-government organizations. In the United States, many businesses develop suppliers that are minority- or women-owned. Ford recently announced that its sourcing from tier-one minority- and women-owned business increased from US $2.7 billion in 2009 to US $4.1 billion in 2010.<ref>http://targetmarketnews.com/storyid05161102.htm</ref> In many instances, the issue is not one of supplier development to meet social justice standards, but rather of screening out substandard suppliers that do not meet social justice norms. For example, various companies monitor suppliers, with varying levels of exctitude, to ensure, among others, prohibitions against child labor and environmentally damaging practices.<br />
==References==<br />
<references /><br />
<br />
[[Category:Purchasing & Sourcing]]</div>Storchhttp://scm.gsom.spbu.ru/Total_cost_analysisTotal cost analysis2011-08-17T16:02:44Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/index.php/Анализ_общих_затрат Анализ общих затрат]'''<br />
<br />
Total cost analysis represents the concept that the sum of the functional costs within the firm should be managed in addition to managing the individual costs independent of one another. The functions included in a total cost analysis include transportation, warehousing, order processing, inventory management, production, and purchasing. The linking of functional costs into a total cost perspective allows the firm to make functional trade-offs in aligning functions in a unified and integrated fashion. The unifying objective should be to minimize total cost subject to meeting a prespecified [[customer service]] level. Without the customer service constraint, a trivial solution to minimizing cost is to minimize operations. In some cases, the functional trade-off may be relativgely straightforward. For example, transportation mode selection may require a trade-off of mode speed (with faster modes charging a higher rate per relevant weight unit) against the transit time inventory carrying cost. A fast mode (e.g., air) will have a high freight rate and a low in transit inventory carrying cost rate, while a slower mode (e.g., rail) will have a lower freight rate and a higher in transit inventory carrying cost rate. In other cases, the trade-offs are relatively complex. For instance, the network design problem seeks to solve the issue of the number, location, and capacity of production and warehouse facilities, the modes to be used when servicing flows from production facilities to warehouses and from warehouses to customers, and the assignment of customers to warehouses and of products to be manufactured at production facilities. The costs being traded-off in this instance include those related to transportation, production, and warehousing. When a solution to the network design problem is sought for a global business, the processes involved including data collection, model verification, and model analysis are not trival and generally require sophisticated software packages.<br />
<br />
==Example==<br />
<br />
A practical example of total cost anlsyis is found in the case of Hewlett Packard (HP) and production of a specialized laptop<ref>Callioni, G., X. de Montgros, R. Slagmulder, L.K. Van Wassenhove, and L. Wright (2005), "Inventory Driven Cost," ''Harvard Business Review'', 83 (3), 135-151.</ref>. In the baseline or current network configuation, a number of regional facilities were utilized where final laptop configuation was undertaken. This final configuation included features related to the power system, the keyboard, the language of materials and of the software, and regional or local packaging requirements. The production of the base product for the entire globe was undertaken at a single location in the United States. This configuation took advantage of form postponement (see [[order penetration point]]), as final configuration was only conducted at regional faciilities after orders were recevied, and of geographic speculation, as HP speculated on the quantity of the base product required at each regional facility based on forecasts. Since larger scale bulk shipments could be ultilized when shipping from the U.S. production facility to the regional facilities, outbound freight costs were effectively managed. However, HP was not taking advantage of [[risk pooling]] effect across space and found itself holding significant safety stocks at each regional facility. This network configuration traded the high cost of the inventory carrying cost against the low cost of freight. An alternative configuration that HP considered and eventually adopted was that of centralizing all production in the U.S. Under this configuration the level of form postponment would not change as the firm would continue to wait for orders before completing the final configuration. The level of geographic postponement would change as HP would not longer specualtion on where inventory was needed before the arrival of orders. The Table shows the percentage cost change for several functions in a shift from the current configuration (geographic speculation) to the proposed configuration (geographic postponenment). The centralization of production would result in some production savings, presumably from a scale effect. The freight cost were expected to increase dramatically, by +56.8%. This is the result of the displacement of bulk shipments from the production facility to the regional facilities with small lot (or express) shipments from the production facility to final customers. HP recently had expanded and clarified the fashion in which it measured inventory carrying costs. Three such costs are provided in the table: (1) an inventory fincnace cost; (2) an inventory devaluation cost, which represents write-downs on inventory; and (3) an inventory obsolescence cost, which reflected inventory write-offs. As seen in the Table, proposed configuration would result in a dramatic reduction of inventory cost. This is primarily a function of the the risk pooling effects across space - less safety stock is required. Thus the proposed network configuration would result in higher freight cost, but lower productoin and inventory cost. Both systems configurations were expected to maintain similar service levels. The total cost of the proposed solution was 28.3% less than the current configuration. The proposed configuration was eventually adopted.<br />
<br />
<br />
{| border="1"<br />
!colspan="3"|Total Cost Analysis: Comparing Two Network Configurations<br />
|-<br />
| Cost || Current Configuration: Use of Regional Facilities || Proposed Configuration: One Centralized Facility<br />
|-<br />
| Production || align="center" | 100% || align="center" | -21.0%<br />
|-<br />
| Freight || align="center" | 100% || align="center" | +56.8%<br />
|-<br />
| Inventory finance || align="center" | 100% || align="center" | -51.9%<br />
|-<br />
| Inventory devaluation || align="center" | 100% || align="center" | -63.5%<br />
|-<br />
| Inventory obsolescence || align="center" | 100% || align="center" | -58.1%<br />
|-<br />
| Total || align="center" | 100% || align="center" | -28.3%<br />
|}<br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Selecting_the_customer_service_levelSelecting the customer service level2011-08-17T12:02:53Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/index.php/Выбор_уровня_обслуживания_клиентов Выбор уровня обслуживания клиентов]'''<br />
<br />
One approach to evaluating the optimal service level for the firm is to adopt the profit maximization economics model which states that, in a perfectly competitive market, the firm should produce output at that point where marginal revenue equals marginal cost. Replacing the number of units provided as the indicator of output with service as the indicator of output suggests that the model may be applied to a variety of customer service variables including [[fill rate]]s, on-time delivery, lead-time, and goods damaged during shipment. Let us assume that the values on the horizontal axis in Figure 1 represent the fill rate with a viable range of 90% to 100%. Marginal revenue increases at a decreasing rate as the service level output increases. As the firm increases its fill rate, supply is increased, and therefore the unit price declines. Since demand for input factors increases, marginal cost increases at an increasing rate as the fill rate increases. The third line in Figure 1 represents profit (or revenue minus cost). Profit is maxmimized where the slope of the cost curve equals the slope of the revenue curve. This occurs at an approximate 95% fill rate<ref>Ballou, R.H. (1992), ''Business Logistics Management'', Prentice Hall, Upper Saddle River: NJ</ref>.<br />
<br />
<lines size=400x300 title="Figure 1: Assesing the Optimal Service Level" ymin=-200 ymax=800 colors=FF5521,8AB800,334500 xlabel ylabel=5 grid=xy legend><br />
,Revenue,Cost,Profit<br />
90,200,100,100<br />
91,320,102,218<br />
92,420,104.5,315<br />
93,500,110,390<br />
94,560,120,440<br />
95,600,140,455<br />
96,620,180,440<br />
97,630,250,380<br />
98,635,350,285<br />
99,638,500,138<br />
100,640,700,-60<br />
</lines><br />
<br />
==Managerial Implications==<br />
From a managerial perspective, a number of variables go into evaluating the cost and revenue curves. On the cost side, improving the on-time delivery rates, for example, may include information technology infrastructure investments which would be fixed over a range of improved service levels. The firm may be required to invest in better forecasting tools or better ways to improve communications among business functions (e.g., sales, production, and distribution). Some costs might be variable and rise according with improvements in on-time delivery. For example, a larger proportion of shipments may require speedier and hence more expensive modes of transport. The creation of revenue curve is often problematic due to the challenges of evaluating customer response to different levels of various logistics customer service variables. Furthermore, the cost and revenue curves may not be constructed, but rather replaced with income statements showing profit at various service levels. The net goal of profit maximization remains unchanged.<br />
<br />
In a competitive industry, the revenue curve faced by two competitors should look rather similar. However, in practice it is often the case that different firms possess different cost curves. This would be due to dissimilarities in strategic decisions over supply chain investments, skill sets, learning rates, and openness to change, among others. In Figure 2, Firms 1 and 2 operate in one market and both face the same revenue curve in relation to the service level (again, we may assume that the sevice level is represented by a fill rate). The cost curve for Firm 1 is shifted downward relative to that of Firm 2. From the profit curves, Firm 1 should select a profit maximizing fill rate of 95%. Firm 2 should select a profit maximizing fill rate of 96%. Firm 1 would want to operate with a profit maximizing service level lower than the profit maximizing service level of Firm 2. However, Firm 1 may select a “match the competition” heuristic to determine its customer service level and thus select a non-optimal service level. Suppose that Firm 2 continually seeks ways to open a gap between itself and its competitors by implementing fashions to shift its cost curve downward. Rivalry of this sort for Firm 1 is troublesome as it elects to compete on its service level and not on its underlying cost structure. Efforts are required to shift cost curves, not merely move along them.<br />
<br />
<lines size=400x300 title="Figure 2: Competitive Optimal Service Levels" ymin=-200 ymax=800 colors=FF5521,8AB800,334500,2D00B8,7160a5 xlabel ylabel=5 grid=xy legend><br />
,Revenue, Firm 1 Cost,Firm 1 Profit, Firm 2 Cost,Firm 2 Profit<br />
90,200,100,100,100,100<br />
91,320,105,215,101,219<br />
92,420,112,308,103,317<br />
93,500,122,378,106,394<br />
94,560,137,423,111,449<br />
95,600,167,433,120,480<br />
96,620,220,400,133,487<br />
97,630.5,290,340,160,470<br />
98,635,390,245,230,405<br />
99,638,520,118,400,238<br />
100,640,700,-60,700,-60<br />
</lines><br />
<br />
==Example 1==<br />
In a simple example, let us assume that each of the revenue and cost curves may be represent by straigtforward formulas where x=[[fill rate]] with a range of 0 to 100:<br />
<br />
<math>\text{Cost}=\,\!x+.1x^2</math><br />
<br />
<math>\text{Revenue}=\,\!20x-800-.0002x^2</math><br />
<br />
Taking the first derivative of the cost and revenue formulas and setting them equal yields:<br />
<br />
<math>\,\!1+.2x=20-.0002x</math><br />
<br />
Solving for x yields 94.9, which equals an approximate fill rate of 95%<br />
<br />
==Example 2==<br />
A more realistic yet simple example better illustrates the business process underlying the evaluation of the optimal service level. Suppose the current late delivery rate of a firm is 95%. As seen in Table 1, the firm generates &euro;100 million in billed revenue at this late delivery rate. The late delivery penalties are evaluated as the late delivery rate multiplied by the billed revenue. Net revenue equals the difference between the two. The cost of goods sold equals 35% of the billed revenue as a late delivery penalty does not detract from the production value of the product. A gross margin of &euro;60 million with &euro;40 million in fixed expenses yields a profit before interest and taxes of &euro;20 million. A shown in Table 1, the billed revenue will increase as the late delivery rate declines. Acquiring these billed revenue values may not be a simple matter. Sources of input could include interviews with sales and logistics staff and with customers. The additional expenses to reduce late delivery might come from several sources. For example, the firm may use free on board origin pricing (which means that the customer pays the freight charge). However, customers might only be willing to pay standard delivery rates. The firm, in order to decrease the late delivery rate, may absorb the difference between standard and premium (i.e., faster) freight charges. Furthermore, decreasing the late delivery rate may require investments in improved forecasting tools and information technologies. As seen in Table 1, these additional expenses were determined to be &euro;3 million and &euro;8 million respectively for late delivery rates of 4% and 3%. Profit is maximized (&euro;24.1 million) at the 4% late delivery rate.<br />
<br />
{| border="1"<br />
!colspan="4"|Table 1: Evaluating the Optimal Service Level (&euro;'000)<br />
|-<br />
| || 5% Late delivery rate || 4% Late delivery rate || 3% Late delivery rate<br />
|-<br />
| Billed revenue ||align="right" | 100 000 || align="right" | 110 000 ||align="right" | 115 000<br />
|-<br />
| Late penalties (late delivery rate &times; billed revenue) ||align="right" | 5 000 || align="right" |4 400 ||align="right" | 3 450<br />
|-<br />
| Net revenue ||align="right" | 95 000 ||align="right"| 105 600 ||align="right"| 111 550<br />
|-<br />
| Cost of good sold (35% of billed revenue) || align="right" |35 000 || align="right" |38 500 || align="right" |40 250<br />
|-<br />
| Gross margin || align="right" |60 000 || align="right" |67 100 || align="right" |71 300<br />
|-<br />
| Fixed expenses || align="right" |40 000 || align="right" |40 000 || align="right" |40 000<br />
|-<br />
| Additional expenses to reduce late delivery rate || ||align="right" | 3 000 ||align="right" | 8 000<br />
|-<br />
| Total expenses ||align="right" | 40 000 ||align="right" | 43 000 ||align="right" | 48 000<br />
|-<br />
| Profit before interest and taxes || align="right" | 20 000 || align="right" | 24 100 || align="right" | 23 300<br />
|-<br />
|}<br />
<br />
==References==<br />
<references /><br />
<br />
[[Category:Customer Service]]</div>Storchhttp://scm.gsom.spbu.ru/Risk_poolingRisk pooling2011-08-16T20:39:01Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Объединение_риска Объединение риска]'''<br />
<br />
Risk pooling involves the process of aggregating objects into a larger group whereby the risk of the group is less than the sum of risk of the individual objects. This may be mathematically expressed as:<br />
<br />
<br />
<math>\big(\mbox{Risk from pooling}=\mbox{Risk of}\sum O_i\big)\le\big(\mbox{Unpooled risk}=\sum \mbox{Risk} O_i\big)</math><br />
<br />
Where:<br />
<br />
*Oi = object i.<br />
<br />
One of the major applications of risk pooling is in the insurance industry. However, it has also been applied in various other fields including economics and supply chain management. In economics, vertcial integration (see [[outsourcing]]) is less likely when the firm forms "a small part of total demand for the input since they would lose the risk pooling economics of large markets as they integrate. Incentives for integration may increase if the demand by other firms for inputs is highly variable, thereby driving up the price” <ref>Carlton, D.W. (1979), “Vertical Integration in Competitive Markets under Uncertainty,” ''Journal of Industrial Economics'', 27 (3), p.204.</ref>. In supply chain management, the two major applications of risk pooling center on form postponement and geographic postponement. In form postponement, the objects being aggregated are products (i.e., risk pooling across products) and its opposite is referred to as form speculation. In form postponement, action on the final form of a product uis delayed until after an order is received (see [[order penetration point]]). In geographic postponement, the objects being aggregated are geographic regions (i.e., risk pooling across space), with its corresponding opposite labeled geographic speculation. Under geographic postponement, a smaller number of warehouses are utilized. The firm thus postpones the decision of where inventory should be lpaced until after an order is received.<br />
<br />
If the risk of the objects are independent of one another, then a high risk from one object will offset the low risk from another object. If this occurs, then ''risk from pooling'' < ''unpooled risk''. The greater the correlation of the risk of between various objects, the smaller the difference between the ''risk from pooling'' and the ''unpooled risk''<ref>Simchi-Levi, D., P. Kaminsky and E. Simchi-Levi (2000), ''Designing and Managing the Supply Chain'', Irwin Mc-Graw Hill, Boston, p.56-60.</ref>. The fundamental benefit from risk pooling in supply chain management is that lower risk loosely equates with lower variance and lower variance in a supply chain system generally equates with less safety stock. Through lower safety stock, risk pooling may lower the inventory carrying cost without sacrificing service levels. The final analysis involves a trade-off between the benefits of risk pooling (i.e., lower safety stock) and the cost of implementing the risk pooling strategy.<br />
<br />
==Example: Risk Pooling Across Products==<br />
<br />
The well known Dell example of delayed assembly until after orders arrive well illustrates the concept of assemble-to-order. Component parts are ready for assembly, however, the final configuration of the product is delayed (or postponed) until after orders have arrived. HP illustrates the strategy of form speculation: products are made-to-stock based on forecasting (see [[order penetration point]]). Supposed a company manufacturers two products, SKU 4501 and 4502. The production [[lead time]] for each product is 21 days and we shall assume for expository purposes that the lead times are constant. As seen in Table 1, respective average weekly demand for the SKUs are 1200 and 2200 and respective standard deviations in weekly demand are 170 and 230. Using the [[inventory model with uncertainty in demand and lead time]] provides respective average safety stock levels of 1,597 amd 2,161, for a total average safety stock level of 3,758.<br />
<br />
{| border="1"<br />
!colspan="3"|Table 1: Unpooled Risk (Form Speculation); In-stock probability = 98% (z=2.05)<br />
|-<br />
| Product || SKU 4501 || SKU 4502<br />
|-<br />
| Production [[lead time]] in days = L || 21 || 21 days<br />
|-<br />
| Average weekly demand || 1200 || 2200<br />
|-<br />
| Standard deviation in weekly demand = SD || 170 || 230<br />
|-<br />
| Safety stock = z &times; SD &radic; L || 2.05 &times; 170 &radic;21 = 1,597 || 2.05 &times; 230 &radic;21 = 2,161<br />
|-<br />
!colspan="3"|Total amount of safety stock = 1,597 + 2,161 = 3,758<br />
|}<br />
<br />
Now suppose that the firm examines an alternative policy based on the idea that the majority of product is common to both SKUs. The production lead time for the common "base" product is 20 days and, as seen in Table 2, just one day is required for the final configuration of both SKUs. The standard deviation of demand for the "base" product equals the square root of the sum of the standard deviations of demand squared. This assumes that Var(X+Y) = Var(X) + Var(Y). This is where the risk pooling concept comes into effect. From a statistical persepctive, the Var(X+Y) = Var(X) + Var(Y) + 2Covariance(X,Y). In other words, we are assuming that the demand for the two SKUs is independent and that the Cov(SKU 5401, SKU 4502)=0. The analysis shown in Table 2 therefore represents the "best case" scenario in terms of reduction in safety stock resulting from risk pooling or form postponement given the values of the remaining parameters in this model. The remainder of the analysis is similar to that shown in Table 1. Safety stock is evaluated for the "base" product as well as for the two finished SKUs. The sum equals 3,442, which therefore represents a "best case" reduction of 8.40% of inventory.<br />
<br />
{| border="1"<br />
!colspan="4"|Table 2: Pooled Risk (Form Postponement); In-stock probability = 98% (z=2.05)<br />
|-<br />
| Product || Base Product || SKU 4501 || SKU 4502<br />
|-<br />
| Production [[lead time]] in days = L || 20 || 1 || 1<br />
|-<br />
| Average weekly demand || 3400 || 1200 || 2200<br />
|-<br />
| Standard deviation in weekly demand = SD || &radic; (170&sup2; + 230&sup2;) = 286 || 170 || 230<br />
|-<br />
| Safety stock = z &times; SD &radic; L || 2.05 &times; 286 &radic;20 = 2,622 || 2.05 &times; 170 &radic;1 = 349 || 2.05 &times; 230 &radic;1 = 472<br />
|-<br />
!colspan="4"|Total amount of safety stock = 2,622 + 349 + 472 = 3,442<br />
|-<br />
!colspan="4"|Percentage reduction in safety stock = (3,758 - 3,422) / 3,758 = 8.40%<br />
|}<br />
<br />
One cannot conclude from the this analysis that form postponement always leads to a reduction in safety stock. With the assumption that demand across products is independent, the general formula utilized in Tables 1 and 2 is expressed as:<br />
<br />
<br />
<math>\mbox{Safety stock}=z\sqrt{LTb}\Bigg(\sqrt{\sum_{t=1}^{T}SDP_i^2}+\sum_{t=1}^{T}SDP_i\sqrt{LTP_i}\Bigg)</math><br />
<br />
Where:<br />
*LTb = Production lead time for base product<br />
*LTPi = Production lead time for product i (in this case LTb + LTPi must be contrained to 21)<br />
*SDPi = Standard deviation in demand for product i<br />
<br />
We may then evaluate the change in safety stock for alternative base product production lead times. As seen in Table 3, only when the base product production lead time equals 19 and 20 days does the level of safety stock decline (by 1% and 8% resepctively). The relationship between base product production lead time and change in safety stock is shown in Chart 1. For all other base product production lead times, safety stock inventory increases relative to the case of no risk pooling (or complete form speculation as shown in Table 1). In these instances, the firm should consider a make-to-stock orientation.<br />
<br />
<br />
{| border="1"<br />
!colspan="21"|Table 3: Percentage change (+/-) in Safety Stock at Various Base Product Production Lead Times; In-stock probability = 98% (z=2.05)<br />
|-<br />
| Base product production lead time (days) ||1||2||3||4||5||6||7||8||9||10||11||12||13||14||15||16||17||18||19||20||<br />
|-<br />
| Percentage change (+/-) in safety stock ||13%||17%||20%||21%||22%||23%||23%||23%||22%||22%||21%||20%||18%||16%||14%||11%||8%||4%||-1%||-8%<br />
|}<br />
<br />
<br />
<lines size=500x200 title="Chart 1: Percentage Change (Plus/Minus) in Safety Stock" ymin=-10 ymax=25 colors=2D00B8 xlabel ylabel=7 grid=xy legend><br />
, Change in Safety Stock<br />
1,13.2<br />
2,17.2<br />
3,19.6<br />
4,21.2<br />
5,22.2<br />
6,22.7<br />
7,22.9<br />
8,22.8<br />
9,22.4<br />
10,21.7<br />
11,20.8<br />
12,19.5<br />
13,18.0<br />
14,16.1<br />
15,13.9<br />
16,11.2<br />
17,8.0<br />
18,4.0<br />
19,-1.1<br />
20,-8.4<br />
</lines><br />
<br />
==Example: Risk Pooling Across Space - The Square Root Rule==<br />
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Risk pooling across space suggests that the objects being aggregated are geographic regions. This is equivalent to [[geographic postponement]] since the firm delays descions on where products are needed until after orders have arrived. The primary operationalization of risk pooling across space is through the use of fewer warehouses. Similar to the case of risk pooling across products, the extent of risk reduction will depend on the covariation of demand (positive, negative, null) among the regions. The general experience of the business community is that risk pooling across space associates with lower variance in demand. This ultimately leads to lower safety stock inventory. A heuristic that captures the reduction in demand from risk pooling across space is known as the square root rule<ref>Zinn, W; M. Levy, and D.J. Bowersox (1989), "Measuring the Effect of Inventory Centralization/Decentralization on Aggregate Safety Stock: The "Square Root Law" Revisited", ''Journal of Business Logistics'', 10 (1), 1-14.</ref>.<br />
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Square Root Rule<br />
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<math>\mbox{Total inventory at existing facilities (Ic)}=\mbox{If}\sqrt{\frac {\mbox{nc}}{\mbox{nf}}}</math><br />
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Where:<br />
* If = Total inventory at future facilities<br />
* nc = number of current facilities<br />
* nf = number of future facilities<br />
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If a business operates five warehouses and the value of inventory at each warehouse equals &euro;100,000, then the total value of inventory equals 5 &times; &euro;100,000 = &euro;500,000. How much inventory would be needed if one warehouse were operated?<br />
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*Given: Ic = &euro;500,000; nc = 5; nf = 1<br />
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<math>\mbox{500,000}=\mbox{If}\sqrt{\frac {5}{1}}</math><br />
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* Therefore, If = &euro;223,607<br />
* This represents a 55% reduction in inventory<br />
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The reduction in invetory from risk pooling across space was obtained through a decline in safety stock. The economic argument for a reduction in the number of warehouses requires a [[total cost analysis]] as the use of fewer warehouses may lead to a shift in the underlying transportation cost structrure. Furthermore, the square root rule is a simplified model that assumes: (1) transshipments between facilities is not common; (2) lead times variance is neglible; (3) the service levels across facilities is constant; and (4) the distribution of demand at the facilities is normal.<br />
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==References==<br />
<references /><br />
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[[Category:Supply Chain Strategy]]</div>Storchhttp://scm.gsom.spbu.ru/Inventory_model_with_uncertainty_in_demand_and_lead_timeInventory model with uncertainty in demand and lead time2011-08-16T18:19:57Z<p>Storch: </p>
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<div>'''Russian: [http://ru.scm.gsom.spbu.ru/Модель_запасов_в_условиях_неопределенности Модель запасов в условиях неопределенности]'''<br />
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The inventory model with uncertainty in demand and lead time is designed to offer an inventory ordering policy that includes a reorder point and an order quantity when demand and lead time are not constant.<ref>Simchi-Levi, D., P. Kaminsky and E. Simchi-Levi (2000), ''Designing and Managing the Supply Chain'', Boston: Irwin Mc-Graw Hill.</ref>. The assumptions of the model are that demand and lead time are normally distributed. The model accounts for an inventory service level, but does not include an out-of-stock penalty. The model consists of three elements: safety stock, the redorder point (RP) and the order-up-to level (OL). The reorder point and the order-up-to-level refer to the inventory position which is equal to to the amount on of inventory on hand plus that on order. This will be demonstrated in the example provided below.<br />
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<math>\mbox {Safety stock} = z\cdot \sqrt {LT \cdot \sigma D^2+D^2 \cdot \sigma LT^2}</math><br />
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<math>\mbox {Reoder point (RP)} = D \cdot LT + \mbox {Safety stock}</math><br />
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<math>\mbox {Order-up-to-level (OL)} = \,\!\mbox {EOQ + RP}</math><br />
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<math>\mbox {Average inventory level} = \frac {1}{2} \,\!\mbox {EOQ} + \mbox {Safety stock}</math><br />
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Where:<br />
* D = average demand<br />
* &sigma;D = standard deviation in demand<br />
* LT = lead time<br />
* &sigma;LT = standard deviation in lead time<br />
* z = standard normal distribution transformation for setting the inventory service level<br />
* EOQ = [[economic order quantity]] (provided below)<br />
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<math>EOQ =\sqrt{\frac{2KD}{h} }</math><br />
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Where:<br />
* K = fixed order cost<br />
* D = average demand<br />
* c = inventory carrying cost rate<br />
* v = the relpacement value of one unit of inventory<br />
* h = inventory carrying cost rate per unit per relevant time period<br />
* If D is expressed annually, then h = c &times; v<br />
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==Example==<br />
Suppose that an electric utility company consumes various types of tranformers. The utility keeps track of usage and of lead times for all the different transformer models utilized. One model has a landed cost of &euro;1,500 per unit (v). The utility requires 10 transformers per month (D). The distribution of demand is normal with a standard deviation of 2 (&sigma;D). The lead time (LT) is 0.5 of a month (or about 15 days). It as well is normally distributed with a standard deviation of 0.10 (&sigma;LT) of a month (about 3 days). The utility wants a high service level so it selects a z value of 2.33 (or a 99% inventory service level). The actual service level in reality is higher than this as utility companies have cooperative arrangements with neighboring utilities to supply transformers if an out-of-stock situation occurs. We shall for the purpose of this example, ignore this special feature. The fixed order cost is very low as the transformer is a standard stock product that is purchased from a long term vendor. A purchasing manager for the utility receives a report each day containing the inventory position for all transformers. If the inventory position falls below the reorder point, the software flags the manager. An electronic invoice is then sent to the vendor. The fixed order cost is minimal and is estimated to be &euro;5. The annual inventory carrying rate (c) is relatively low as obsolesence, theft, loss, and shrinkage are minimal. The carrying cost rate consists primarily of insurance, a warehousing handling fee, and the cost of capital. It is estimated to be 0.15.<br />
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What should be the order policty of the utility regarding this transformer, how much inventory will typically be on hand, and what is annual inventory hold cost per year?<br />
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<math>\mbox {Safety Stock} = z\cdot \sqrt {LT \cdot \sigma D^2+D^2 \cdot \sigma LT^2} = 2.33 \cdot \sqrt {0.5 \cdot 2^2 + 10^2 \cdot 0.10^2} = 4.03 </math><br />
<math>\,\!\mbox {(round down to 4 units)} </math><br />
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<math>\mbox {Reoder point (RP)} = D \cdot LT + \mbox {Safety stock} = 10 \cdot 0.50 + 4 = 9</math><br />
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<math>\mbox {Order-up-to-level (OL)} = \,\!\mbox {EOQ + RP} = 3 + 9 = 12</math><br />
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<math>\,\!\mbox {Where:}</math><br />
<math>EOQ =\sqrt{\frac{2KD}{h}} = \sqrt{\frac{2 \cdot 5 \cdot 10}{0.15 \cdot 1,500 / 12}} = 2.31</math><br />
<math>\,\!\mbox {(round up to 3 units)} </math><br />
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<math>\mbox {Average inventory level} = \frac {1}{2} \,\!\mbox {EOQ} + \mbox {Safety stock} = \frac {1}{2} \cdot 3 + 4 = 5.5</math><br />
<math>\,\!\mbox {units} </math><br />
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<math>\mbox {Annual inventory carrying cost} = c \cdot v \cdot \mbox {number of units} =0.15 \cdot 1,500 \cdot 5.5 = 1,238</math><br />
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Given these inputs, the reorder policy should be (9;12) - this is, when the inventory position falls below 32 units, sufficient inventory should be order to bring the inventory position back up to 36. Three issues should be raised:<br />
* In the evaluation of the EOQ, note that the carrying cost per unit in the denominator must reflect the relevant time period. Demand and lead time were expressed in monthly terms. The carrying cost rate was expressed annually. Division of (c&times;v) by 12 provides the apporporiate inventory holding cost per unit per month.<br />
* The order policy of (9;12) guarantees an inventory service level of 99%.<br />
* The policy refers to the inventory position. Suppose that the inventory information system tracks stock on a continual basis and once a day flags are issued if orders need to be placed. Table 1 provides a hypothetical demand pattern for the public utility. On day 1, the inventory on hand is 10, demand is zero, and the inventory position (the sum of the two) equals 10. This is within the inventory policy limit set by the (9;12) rule. On day 2, demand is one unit, inventory on hand falls to 9, and the position equals 9. Again. no action is required. Day 4 demand is two units. The position, without any action would fall to 7. An order of five units is required to bring the position to its upper limit of 12. On day 6, another transformer is demanded, however, the position remains greater than or equal to 9. No action is required. One result of this is that it is possible to have multiple orders on hand, spread across a 15 day period, with orders expected to arrive every several days.<br />
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{| border="1"<br />
!colspan="6"|Table 1: Illustration of Inventory Position: The Public Utility Case (9;12)<br />
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| Day || Demand || Inventory on Hand || Inventory on order || Action required || Inventory Position<br />
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| 1 || 0 || 10 || 0 || None || 10 <br />
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| 2 || 1 || 9 || 0 || None || 9<br />
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| 3 || 0 || 9 || 0 || None || 9<br />
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| 4 || 2 || 7 || 5 || Order 5 units || 12<br />
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| 5 || 0 || 7 || 5 || None || 12<br />
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| 6 || 1 || 6 || 5 || None || 11<br />
|-<br />
|}<br />
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==References==<br />
<references \ref><br />
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[[Category:Inventory Management]]</div>Storch