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  1. 1. Evaluation of postponement strategies <br />in mass customizationwith service guarantees<br />SHAO et. al.<br />Presenter: Tuan Tran<br />Digital Product Lab – Dongguk University<br />October 11th 2011<br />
  2. 2. Contents<br />Introduction<br />Model description<br />Comparison of postponement strategies<br /><ul><li>Product redesign strategy
  3. 3. Process reversal strategy
  4. 4. Comparison of two strategies
  5. 5. Case analysis</li></ul>Numerical example<br />Concluding remarks<br />2<br />Digital Product Lab<br />
  6. 6. Introduction<br />Competitive market >> Companies have to extend their product lines to meet diverse customer demands.<br />Mass customization >> new competitive paradigm >> companies customise products in response to individual customer orders, while retaining their operational performance (Davis 1987)<br />Mass customization is generally described as a process by which firms apply technology and management methods to provide product variety and customization at a low cost through flexibility and quick responsiveness (Davis 1987, Pine et al. 1993, Kotha 1995).<br />3<br />Digital Product Lab<br />
  7. 7. Introduction<br />Postponement is one of the practical methods to mass customization (Kotha 1995, Lampel and Mintzberg 1996, Feitzinger and Lee 1997).<br />It implies that the process would not commit the work-in-process into a particular finished product until a later point (Lee and Tang 1997).<br />Postponement strategies >> reduce the risks associated with product variety by exploiting the commonality between items and by designing the production and distribution processes to delay the point of differentiation (Aviv and Federgruen 2001a). <br />Delaying product differentiation >> increase flexibility, reduce uncertainties and decrease the costs of complexity by reducing the variety of components and processes within the system (Garg and Tang 1997, Yang et al 2004a, Nair 2005).<br />4<br />Digital Product Lab<br />
  8. 8. Introduction/Problem definition<br />This paper >> consider a manufacturer in search of postponement strategies in mass customization with service guarantees. <br />Production process consists of several stages. Beginning stages >> manufactures and stocks a common product that can then be customised at the later stages. <br />Service guarantees >> Manufacturer should deliver customised products within a limited period >> the location of product differentiation point is a significant decision. <br />Positioning of the differentiation point at the upstream stages >> reduce the investment in the value-added component inventory, but may also impact the company’s responsiveness to customer orders.<br />5<br />Digital Product Lab<br />
  9. 9. Introduction/Problem definition<br />Example: IBM used to deliver RS6000 server machines later than the customer requested arrival data due to an upstream differentiation point leading to a sizable percentage of late orders (Swaminathan and Tayur 1998a) <br />By properly designing the product structure and the supply chain process, the product differentiation point in mass customization can be delayed to increase the flexibility and responsiveness to customer demand.<br />6<br />Digital Product Lab<br />
  10. 10. Introduction/Literature<br />Alderson (1950): the first to propose the postponement concept from a marketing management perspective.<br />Bucklin (1965): brings postponement into the distribution channel.<br />Yang et al. (2004b):The scope of postponement has expanded from marketing to the whole supply chain, including purchasing, manufacturing, distribution.<br />Zinn and Bowersox (1988): propose two different postponement strategies, e.g. form postponement (including manufacturing, assembly, packaging and labelling postponement) and time postponement<br />7<br />Digital Product Lab<br />
  11. 11. Introduction/Literature<br />Lee and Tang (1997): provide a classification of possible postponement strategies through redesigning products and restructuring process.<br />Swaminathan and Lee (2003): The ability of a firm to implement a successful postponement strategy depends on how well the firm can tailor its process and product characteristics to the market requirements<br />Swaminathan and Lee (2003): provide a comprehensive review on analytical models for evaluating postponement alternatives.<br />8<br />Digital Product Lab<br />
  12. 12. Introduction/Literature<br />Lee (1996): presents inventory models that support product/process design for postponement.<br />Lee and Whang (1998): explore the postponement model further by assuming that demands are not independent and identically distributed over time.<br />Lee and Tang (1997): provide a few analytical models to analyze the costs and benefits of three kinds of postponement strategies (standardization, modular design, and process restructuring)<br />Garg and Tang (1997): present a model to evaluate postponement strategies for product families with multiple points of differentiation.<br />9<br />Digital Product Lab<br />
  13. 13. Introduction/Literature<br />Lee and Tang (1998) & Jain and Paul (2001): present the operations reversal model to determine which sequence of operations results in optimal operational performance. <br />Aviv and Federgruen (2001a): characterize the benefits of postpone-ment in more general setting, where parameters of the demand distributions fail to be known with accuracy or where consecutive demands are correlated. <br />Aviv and Federgruen (2001b): model the costs and benefits of postponement strategies in capacitated multi-item inventory systems with random and seasonally fluctuating demands.<br />10<br />Digital Product Lab<br />
  14. 14. Introduction/Literature<br />Swaminathan and Tayur (1998a): provide a final assembly model with production capacity constraints.<br />Gupta and Benjaafar(2004): adopt queuing approximations to analyze a system where both make-to-stock and make-to-order environments are utilised while delaying the point of differentiation. <br />Graman and Magazine (2002): develop a single-period, multiple-product, capacitated postponement capacity.<br />Tibben-Lembke and Bassok (2005): present an inventory model for delayed customization problem in which the company considers using both regular production and postponement.<br />11<br />Digital Product Lab<br />
  15. 15. Introduction/Literature<br />There are also some papers considering the application of postponement in practice (see Lee et al . 1993, Kotha 1996, Swaminathan and Tayur 1998b, Brown et al. 2000, Thonemann and Brandeau 2000).<br />There is lack of research on comparison of different postponement strategies in the extant literature.<br /> We assume the expected customer waiting time or service level is determined by market competition; and we find that the processing time and value added at the considered stages are the two main factors determining the choice of postponement strategy.<br />12<br />Digital Product Lab<br />
  16. 16. Contents<br />Introduction<br />Model description<br />Comparison of postponement strategies<br /><ul><li>Product redesign strategy
  17. 17. Process reversal strategy
  18. 18. Comparison of two strategies
  19. 19. Case analysis</li></ul>Numerical example<br />Concluding remarks<br />13<br />Digital Product Lab<br />
  20. 20. Model description<br />Consider a firm that mass customizes products out of generic components according to customer orders. <br />Firm produces common modules or components, and then stores them at the differentiation point. <br />The upstream production process >> forecast-driven. The final downstream from the differentiation point >> order-driven, which differentiates the products to specific customer orders. <br />Example: A computer manufacturer, which assembles computers to customer orders at its distribution centre (figure 1).<br />14<br />Digital Product Lab<br />
  21. 21. Model description<br />15<br />Digital Product Lab<br />
  22. 22. Model description<br />Assume the mass customization system has N stages, and the differentiation point is located at the end of stage k (see figure 2). <br />Customer demand during a single period(D), is a random variable with a continuous distribution represented by the cumulative distribution function (cdf) F(x) and continuous density function f(x). <br />Assume that demands in different periods are independent.<br />16<br />Digital Product Lab<br />
  23. 23. Model description<br />17<br />Digital Product Lab<br />
  24. 24. Model description<br />Suppose the customization process is flexible and no capacity limit is imposed on the customization phase. <br />When a customer order comes >> can start customizing products if the general components needed are available at the differentiation point.<br />Periodic review based-stock replenishment policy is applied at the differentiation point.<br />18<br />Digital Product Lab<br />
  25. 25. Model description<br />The sequence of events for the model<br />Beginning of each period >> customer orders arrive. <br />Then >> generic component inventory is used to customize the products to meet the customer orders.<br />If there is no sufficient on-hand inventory at the differentiation point to meet all customer orders>> the excess is backlogged until more inventories are available from upstream production processes.<br />Next, inventory is reviewed, and production to replenish the component inventory to a given inventory position is initiated. <br />Finally, all costs and revenues are incurred.<br />19<br />Digital Product Lab<br />
  26. 26. Model description<br />20<br />Digital Product Lab<br />Notation:<br />
  27. 27. Model description<br />Difficult to determine an exact value for stockout costs >> this model considers service level measures instead of stockout costs. <br />Service levels generally refers to either the probability of not stocking out or the proportion of demand satisfied directly from inventory, or fill rate (Zeng and Hayya 1999).<br />This study >> choose two service level measures that are commonly adopted in mass customization operations: expected average customer order lead time & proportion of demand satisfied within target time periods(see Lee 1996).<br />21<br />Digital Product Lab<br />
  28. 28. Model description<br />T: Manufacturer’s response time to customer orders<br />tw: waiting time for components if there is no enough inventory on-hand at the differentiation point when the customer orders arrive.<br />22<br />Digital Product Lab<br />
  29. 29. Model description<br />An individual order arriving in a particular period could be satisfied in<br />periods ( ~ tw = 0) >> best service level<br />23<br />Digital Product Lab<br />
  30. 30. Model description<br />The longest response time is<br />the total production time of the customized products, where<br />24<br />Digital Product Lab<br />
  31. 31. Model description<br />25<br />Digital Product Lab<br />
  32. 32. Model description<br />26<br />Digital Product Lab<br />
  33. 33. Model description<br />27<br />Digital Product Lab<br />
  34. 34. Model description<br /><ul><li> Objective function >> represents inventory holding cost at the differentiation point and the total average WIP inventory cost before the differentiation point.
  35. 35. Constraint (1) defines the average customer waiting time, and constraint (2) defines the fill rate within a target waiting time window.
  36. 36. This paper >> focuses on analyzing the impact of postponement strategies on inventory costs >> ignore the restructuring costs and production costs in the model</li></ul>28<br />Digital Product Lab<br />
  37. 37. Model description<br />29<br />Digital Product Lab<br />
  38. 38. Contents<br />Introduction<br />Model description<br />Comparison of postponement strategies<br /><ul><li>Product redesign strategy
  39. 39. Process reversal strategy
  40. 40. Comparison of two strategies
  41. 41. Case analysis</li></ul>Numerical example<br />Concluding remarks<br />30<br />Digital Product Lab<br />
  42. 42. Product redesign<br />Product redesign strategy >> adopts standardization or modular design concepts. <br />Standardization: Replace some customized components with common components. <br />Modular design: Decompose the complete product into submodules that can be easily assembled together<br />Through product redesign >> manufacturer can delay the customization operations. <br />Companies adopting product redesign approach: Xilinx (Brown et al. 2000), Lucent Technologies (Hoyt and Lopez-Tello 2001) and IBM (Swaminathan and Tayur 1998a).<br />31<br />Digital Product Lab<br />
  43. 43. Product redesign<br />To implement product redesign strategy to delay the point of differentiation >> assume the firm redesigns the product structure to replace specific components at stage k + 1, so customization operations start at stage k + 2 and the differentiation point is postponed from the end of stage k to the end of stage k +1 (figure 3).<br />32<br />Digital Product Lab<br />
  44. 44. Product redesign<br />33<br />Digital Product Lab<br />
  45. 45. Product redesign<br />34<br />Digital Product Lab<br />
  46. 46. Product redesign<br />35<br />Digital Product Lab<br />
  47. 47. Product redesign<br />Value of component standardization and modularization to postpone the differentiation point may be different at different stages in the production process.<br />Proposition 2 implies >> the benefit of component standardization and modularization decreases as the costs of standardized or modularized components increase. <br />~> It is not beneficial to standardize or modularize components to postpone the point of product differentiation if the components have high values. <br />In contrast, if the components have low value, inventory costs may be reduced through component standardization or modularization.<br />36<br />Digital Product Lab<br />
  48. 48. Product redesign<br />Product redesign approach, vanilla boxes (common semi-finished products used to produce different products) can be designed to postpone the point of differentiation. <br />IBM introduced the vanilla boxes in one of the two assembly plants for RS6000 server machine production considering the increasing in service time expectations and the costs in terms of vanilla boxes (Swaninathan and Tayur 1998a). <br />Our results indicate >> under the condition that service can be guaranteed >> the benefits of designing vanilla boxes in the production process are associated with the costs of the vanilla boxes.<br />37<br />Digital Product Lab<br />
  49. 49. Process reversal<br />Process reversal approach: Re-sequences process steps in making a product or in the supply chain operations so that common process steps shared by customized products are performed before customization process steps. <br />Well known cases of process reversal for postponement include HP (Kopczak and Lee 1993) and Benetton (Aviv and Federguen 2001).<br />38<br />Digital Product Lab<br />
  50. 50. Process reversal<br />Early 1990s >> HP Europe sold different DeskJet printers in many markets, differentiated in terms of the power supply module, power cord terminator, and manual. <br />Traditionally, localization took place in the Vancouver plant. In order to solve the inventory and shortage problems incurred at the European distribution centre, HP Europe reversed localization operation and transportation operation.<br /> It demonstrates the benefits of postponing localization until the printers arrive at the European distribution centre. <br />Benetton, an Italian apparel manufacturer improved its ability to meet market demand with fewer inventory by reversing the dyeing and knitting stages.<br />39<br />Digital Product Lab<br />
  51. 51. Process reversal<br />To implement process reversal approach to delay the point of differentiation >> assume stage k + 2 is a common process for all customized products and stage k + 1 and k + 2 can be reversed. <br />The firm redesigns the processes to reverse stage k +1 and stage k + 2 (figure 4).<br />40<br />Digital Product Lab<br />
  52. 52. Process reversal<br />41<br />Digital Product Lab<br />
  53. 53. Process reversal<br />42<br />Digital Product Lab<br />
  54. 54. Process reversal<br />43<br />Digital Product Lab<br />
  55. 55. Comparison/Process reversal<br />From proposition 3, if stage k + 2 is a short operation and adds high value, it is not beneficial to reverse stage k + 1 and stage k + 2. <br />If stage k + 2 is a long operation and adds little value, then the reversal of stage k + 1 and k + 2 would yield great benefits. The longer is stage k + 2, the greater benefits the operations reversal would yield. <br />It is probably intuitive as to why HP Europe could benefit from the operations reversal of localization and shipping. In this case, the reversal of localization and shipping delays the point of product differentiation. <br />The benefits of HP Europe’s operations reversal strategy largely depends on the shipping process.<br />The localization process is relatively short. But the shipping process takes about 4 weeks and adds no value to the printers.<br />44<br />Digital Product Lab<br />
  56. 56. Compare strategies<br />In this paper >> analyze the situation where it is possible to either standardize the components or change the sequence of operations in a process so that products get differentiated later. <br />For delaying the point of differentiation >> which approach is better?<br />We compare the inventory costs of these two postponement strategies.<br />45<br />Digital Product Lab<br />
  57. 57. Compare strategies<br />46<br />Digital Product Lab<br />
  58. 58. Compare strategies<br />47<br />Digital Product Lab<br />
  59. 59. Compare strategies<br />From proposition 4, if the lead time of stage k + 1 is longer than that of stage k + 2, and the value added at stage k +1 is lower than that at stage k + 2, it is better to adopt product redesign approach to postpone the point of differentiation from stage k to stage k + 1.<br />If the lead time of stage k + 1 is shorter than that of stage k + 2, and the value added at stage k + 1 is larger than that at stage k + 2, it is better to adopt process reversal approach.<br />Proposition 4 indicates that processing time and value added at the considered stages are two main factors determining the choice of postponement strategies. <br />We further discuss about the comparison of product design and process reversal in the following case.<br />48<br />Digital Product Lab<br />
  60. 60. Case Analysis<br />Anny: Chinese biological and medical product manufacturer, addresses the problem of postponement. <br />One of its main products is Anny Liquid, which contains a live bacteria type of ecological dietetic liquid. The products are distributed by 10 subsidiary companies which are responsible for different regions. <br />To avoid horizontal channel conflict that one distributor sells the products to other markets, Anny distinguishes the products distributed by different subsidiaries with different product packing.<br />49<br />Digital Product Lab<br />
  61. 61. Case Analysis<br />Traditional production process of Anny Liquid >> 6 stages: mixing, fermenting, transfusing, inspecting, packaging and shipping (see table 1).<br />50<br />Digital Product Lab<br />
  62. 62. Case Analysis<br />The manufacturing process is guided by the orders from the 10 subsidiary companies. <br />The subsidiary companies place orders every week based on their sales forecasts and inventory. <br />Once receiving orders from different subsidiary companies, the manufacturer decides how much to produce and place an order for different packing materials from an outsider supplier.<br />The original product differentiation takes place at the mixing stage (see figure 5a). The purchasing lead time of packing materials is 2 days.<br />51<br />Digital Product Lab<br />
  63. 63. Case Analysis<br />52<br />Digital Product Lab<br />
  64. 64. Case Analysis<br />It is usually difficult for the subsidiary companies to accurately forecast their sales demands. <br />The dynamic and intensely competitive market >> challenged Anny’s operations.<br />To reduce the problem of stockout level and excess inventory faced by the subsidiary companies >> Anny decides to adapt its operations strategy to reduce average order lead time from 25 days to 6 days. <br />Two solutions are considered by the management.<br />53<br />Digital Product Lab<br />
  65. 65. Case Analysis<br />Solution A: postpone the differentiation point from the mixing stage to the end of packaging stage (figure 5b).<br />Stages from mixing to packaging are all standardized and products destined to different regions are differentiated by sticking different stamps on the products just before delivery to the distribution centre (DC).<br />54<br />Digital Product Lab<br />
  66. 66. Case Analysis<br />Solution B: postpone the differentiation point by standardizing all stages before packaging and reversing the operations of packaging and shipping to DC (figure 5c). <br />In this solution, packaging operations are carried out at the DC.<br />55<br />Digital Product Lab<br />
  67. 67. Case Analysis<br />Two solutions have different impact on the company’s operations. <br />In solution A, the manufacturer holds high value finished products from packaging stage to DC.<br />But in solution B, the manufacturer holds no finished products and packages the products just before delivery to the regional distribution centres(RDCs). <br />In the case of Anny, packing materials cost 56% of total costs. Considering the packing material costs, the company adopts solution B. <br />Due to postponing the differentiation point to the packaging stage at the DC through reversing the operations of shipping to DC and packaging, the company significantly reduces its inventory levels and inventory costs meanwhile improves the responsiveness to market.<br />56<br />Digital Product Lab<br />
  68. 68. Case Analysis<br />This paper’s model explains the results well. <br />According to proposition 4, solution B is preferred to solution A because value added at packaging stage is larger than value added at the shipping stage and the operations time at packaging stage is shorter than the shipping operation.<br />57<br />Digital Product Lab<br />
  69. 69. Contents<br />Introduction<br />Model description<br />Comparison of postponement strategies<br /><ul><li>Product redesign strategy
  70. 70. Process reversal strategy
  71. 71. Comparison of two strategies
  72. 72. Case analysis</li></ul>Numerical example<br />Concluding remarks<br />58<br />Digital Product Lab<br />
  73. 73. Numerical Example<br />We analyze numerical examples comparing the product redesign and process reversal strategies<br />The mass customization system in this example has 3 stages with stable processing times at each stage.<br />The manufacturer produces generic components at stage 1 and processes them at stage 2 and stage 3 to provide customized products (figure 6a). <br />All one-period demands are normally distributed with mean demand μ = 100 and standard deviation of σ = 50. Demands at different periods are independent.<br />59<br />Digital Product Lab<br />
  74. 74. Numerical Example<br />60<br />Digital Product Lab<br />
  75. 75. Numerical Example<br />The manufacturer can either standardize the process of stage 2 (figure 6b) or reverse stages 2 and 3 to make stage 3 a common process (figure 6c). <br />We examine three settings of processing times ti , namely ( t1 , t2 , t3 ) = (4, 1, 3), (4, 2, 2), (4, 3, 1). <br />Base stock policy is applied at the differentiation point. <br />The manufacturer sets service levels with expected customer order lead time of τ and the fill rate of θ in τ0 periods.<br />61<br />Digital Product Lab<br />
  76. 76. Numerical Example<br />62<br />Digital Product Lab<br />
  77. 77. Numerical Example<br />The corresponding inventory policies for scenario without postponement and scenarios with one-period, two-period and three-period postponement are given in table 2.<br />63<br />Digital Product Lab<br />
  78. 78. Numerical Example<br />64<br />Digital Product Lab<br />
  79. 79. Numerical Example<br />As shown in table 2, the optimal base stock level and inventory on-hand at the differentiation point in each scenario is non-decreasing with the fill rate in τ0 periods and non-increasing with expected customer order lead time. <br />When the expected customer order lead time is short and the target fill rate is relatively low, constraint of the fill rate is loose and base stock level is mainly determined by the expected customer order lead time.<br />65<br />Digital Product Lab<br />
  80. 80. Numerical Example<br />Figure 7 shows that when the service levels are unchanged, the base stock levels are non-increasing with the postponed time periods. <br />For instance, the base stock levels keep constant at the service level of τ = 4.2 and θ = 99%, and decrease when postponement strategies are adopted at the service level of τ = 4.2 and θ = 92%.<br />66<br />Digital Product Lab<br />
  81. 81. Numerical Example<br />67<br />Digital Product Lab<br />
  82. 82. Numerical Example<br />As expected from proposition 1, figure 8 shows that when the service level keeps unchanged, postponement can reduce the inventory level at the differentiation point and the inventory level decreases with the postponed time periods.<br />68<br />Digital Product Lab<br />
  83. 83. Numerical Example<br />In order to compare the different postponement strategies, we fix the service level parameter τ at 4.2 and θ at 96% in 5 periods. <br />Table 3 reports numerical examples of total inventory costs of product redesign strategy and process reversal strategy in the three scenarios with different values of Δh2 and Δh3 . <br />69<br />Digital Product Lab<br />
  84. 84. Numerical Example<br />In the 3 scenarios, we find that it is not always beneficial to postpone the differentiation point. <br />In product redesign strategy, the benefits of postponement decrease with Δh2.<br />We further find that the benefits of postponement increase with the processing time of stage 2 when Δh2 is fixed. <br />In process reversal strategy, the benefits of postponement increase with Δh2 and decrease with t2 when the total value added in stage 2 and 3 is fixed. <br />70<br />Digital Product Lab<br />
  85. 85. Numerical Example<br />In scenarios I and II, where t2 is longer than or equal to t3, the cost increment of product redesign strategy relative to process reversal strategy is positive when Δh2 is lager than Δh3. As expected from proposition 4, process reversal strategy is preferred. <br />In scenario III, where t2 is shorter than t3 , the cost increment of product redesign strategy relative to process reversal strategy is negative when Δh2 is smaller than Δh3. Therefore product redesign strategy is preferred.<br />71<br />Digital Product Lab<br />
  86. 86. Contents<br />Introduction<br />Model description<br />Comparison of postponement strategies<br /><ul><li>Product redesign strategy
  87. 87. Process reversal strategy
  88. 88. Comparison of two strategies
  89. 89. Case analysis</li></ul>Numerical example<br />Concluding remarks<br />72<br />Digital Product Lab<br />
  90. 90. Concluding remarks<br />In this paper, we introduce and develop a model for evaluating two different postponement strategies in mass customization with service guarantees. <br />Delayingproduct differentiation point through product redesign and process reversal lowers the inventory levels. But such strategies may increase inventory costs. <br />We evaluate and compare the postponement strategies by considering the total inventory cost.<br />When considering the inventory costs, it is not beneficial to delay the point of differentiation if the considered stage is a high value-added process. <br />However, it is better to delay the point of differentiation if the considered stage has a relatively long time operation and adds little value. <br />73<br />Digital Product Lab<br />
  91. 91. Concluding remarks<br />Our results show that processing time and value added at the considered stages are two main factors influencing the decision of postponement strategies. <br />The case study and numerical examples demonstrate that cost savings can be realised when the right strategy is considered. <br />Our research provides guidance for managers regarding application of mass customization to cost-effectively meet customer demand with service time constraints.<br />74<br />Digital Product Lab<br />
  92. 92. Concluding remarks<br />Further works in the future:<br />Production congestion should be incorporated. <br />Further research should apply queuing models to consider the waiting time in the mass customization system. <br />Production costs, restructuring costs and competition should be considered. <br />75<br />Digital Product Lab<br />
  93. 93. Concluding remarks/Future<br />Future research should consider the impact of the order lead time competition on the decision of postponement strategies. <br />More general postponement structures should be analyzed. In practice, different postponement strategies may have different unit production time and cost. <br />Futureresearch should consider other postponement strategies such as time postponement, and extend the model to consider different unit production time to find the more general results.<br />76<br />Digital Product Lab<br />
  94. 94. Thank you very much<br />77<br />Digital Product Lab<br />