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Specialization: Production Engineering and Logistics Report number: 2013.TEL.7761
Title: Strategic positioning of the customer order decoupling point
Author: M. Kramer
Title (in Dutch) Strategische positionering van het klant order ontkoppel punt
Assignment: literature Confidential: no
Initiator (university): Dr.ir. H.P.M. Veeke Supervisor: Dr.ir. H.P.M. Veeke
Delft University of Technology
FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl
Student: M. Kramer Assignment type: Literature
Supervisor (TUD): H.P.M. Veeke Creditpoints (EC): 10 Specialization: PEL
Report number: 2013.TEL.7761 Confidential: No
Subject: Strategic positioning of the customer order decoupling point
The customer order decoupling point has been a widely described phenomena in manufacturing, logistics and supply chain operations. Although there is consensus about the phenomena itself there are many differentiating views on how it should be used.
Your assignment is to describe the phenomena and the impact it has on processes and give an overview of the differentiating views regarding this phenomena.
The report should comply with the guidelines of the section. Details can be found on the website.
The professor,
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Summary
Nowadays the customer demand instant fulfillment of their needs, another trend is increased the demand for tailor made products. The changing customer demand poses an interesting challenge for the production of these goods. The customer order decoupling point (CODP) is the point in production at which the product is produced for a specific customer taking the customer specifications in account. As such the phenomena has gained increased attention.
The choice for the CODP is one of -the many- strategic decisions that have to be made when designing a production process as it relates to the processing order, timing and efficiency. Thereby, it creates an interesting tension field between marketing, sales, product quality and production. This tension field results in an interesting variety of perspectives about the CODP.
The most important result of implementing a CODP is that the material flow is divided into two sub processes: the pre- and post-CODP processes. The CODP can be placed in different positions in the value chain. By this placement the respective lengths of the pre- and post-CODP processes is determined. There are four commonly acknowledged post-CODP positions, which on their place correspond with different CODP strategy names. These four strategies are: Make-to-stock (MTS), assemble-to-order (ATO), make-to-order (MTO) and engineer-to-order (ETO).
These CODP strategies describe the traditional view of production and engineering as a sequence where the engineering (or design) precedes the production. In this sequential view it is impossible to start with production activities before the final design is known. By separating engineering and manufacturing it is possible to consider the production value added activities and the engineering value added activities to be non-sequential. As a result, six 2-dimensional perspectives on COPD can be formulated. With the production CODP positions in one dimension and the engineering CODP’s on the other dimension.
There is a strong consensus that pre- and post-CODP operations differ significant. Consensus can be found in literature on how the processes perform on process characteristics as efficiency, flexibility and lead time. On the basis of the characteristics, main motivators for upstream and downstream shifting can be derived: The main drivers for upstream shifting are reduction of customer lead time and increase the production efficiency. The main driver for downstream shifting is to increase the knowledge of the customer order at the time of production. Besides the difference in process characteristics, there is also a significant difference in (organizational) attributes. The attributes are a derivative of the production characteristics, and provide a general understanding of the attributes found in practice.
2 For the positioning of the CODP different methods exist. The found methods can be placed in three categories. The first based on a trade-off between the pre- and post-CODP characteristics. In other words if the CODP is shifted backwards the process will inherit more post-CODP characteristics and if the CODP is shifted forwards more pre-CODP characteristics are inherited. The second method is based on the P:D ratio. This ratio describes the relative time needed for production and the time the customer need has to be fulfilled. The general view is that the CODP cannot be shifted further backwards than the point where these the production time equals the demand time. The last method is based on specific production characteristics. The general idea is that based on some dominant production characteristics a practical position should be found. Typical production characteristics associated with this method are product diversity, capacity bottle neck and relative production cost.
In most cases the CODP is considered as a fixed point, however companies discern more than one CODP strategy in their production processes. This non-fixed CODP phenomena has led to a differentiated view on the COPD in literature, the dynamic CODP. The idea behind a dynamical CODP is that the optimal placement of the CODP depends on the circumstances of the specific moment. The three main sets of circumstances addressed are operational hybridity, long term hybridity and assortment hybridity.
The CODP is often mentioned in association with two operational paradigms, being mass customization and leagile production. The goal of mass customization is to combine mass production with high product variability. In mass customization one of the most important parameters is the entry point of the customer order. Thus the positioning of the CODP plays a central role in mass customization. In leagile production the process is divided in a lean and agile process. The division between these processes is the CODP. Therefore the CODP also plays a central role in leagile production.
Although there is a general consensus on the phenomena and the characteristics associated with the CODP, the methods for placing the CODP differ in literature. The general perception is that CODP is, strategically positioned static point in the process. However in practice a dynamical CODP is often used. Although no winning CODP blueprint can be comprised, strategically positioning of the CODP is an powerful tool in an operations engineer toolbox. This literature review has provides an insight of the possibilities offered of this tool.
To put all the arguments given in perspective the central question should be “does it create more value overall?”. Whether more value is created depends on the specific cost-buildup of production and the specific revenue-buildup of sales. Which are unique for every company, thus making each CODP consideration unique.
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Contents
Summary ... 1
Contents ... 3
1. Introduction ... 4
2. The customer order decoupling point ... 5
2.1 Background... 5
2.2 Definition Customer Order Decoupling Point ... 5
2.3 CODP strategies ... 7
3. Separation of engineering and production CODP’s ... 9
3.1 Engineering and Production CODP ‘s ... 9
3.1 Production and engineering CODP combination ...10
3.3 Two dimensional CODP perspective ...11
4. Pre- and post CODP process characteristics ...12
4.1 Typical pre- and post-CODP performance characteristics ...12
4.2 Motivators for upstream and downstream shifting ...13
4.3 Typical attributes pre- and post-CODP processes ...14
4.4 Relation between production cost and product variability ...14
5. CODP positioning methods ...16
5.1 Characteristics trade-off ...16
5.2 P:D ratio based methods ...17
5.3 Methods based on single production characteristics ...19
6. Dynamic CODP positions...21
6.1 Operational hybridity ...21
6.2 Long term hybridity...22
6.3 Assortment hybridity ...22
7. CODP in mass customization and leagile production ...24
7.1 Mass customization ...24
7.2 CODP and mass customization typology ...24
7.3 The “mass” of mass customization ...25
7.4 Leagile production ...26
7.5 Leagile production and the CODP ...26
8. Concluding Remarks ...28
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1. Introduction
The current age, with computer and internet technologies, has changed the customer demand and made the world respond quicker. Nowadays the customer demand needs to be fulfilled instantly (de Treville, de Shapiro, & Hameri, 2004). About 10 years ago there was the 24 hour photo service, which later became an hour photo service. Today there is the instant photo service. Another trend is the demand for tailor made products. With increasing wealth customers are willing to pay high premiums for choice, customization possibilities and options. The changing customer demand poses an interesting challenge for the positioning of the customer order decoupling point (CODP). As such the phenomena has gained increased attention (Rudberg & Wikner, 2004).
The customer order decoupling point (CODP) is the point in production at which the product is produced for a specific customer taking the customer specifications in account (Olhager, 2003). The choice for the CODP is one of (the many) strategic decisions that have to be made when designing a production process as it relates to the processing order, timing and efficiency. Thereby, it creates an interesting tension field between marketing, sales, product quality and production (Berry & Hill, 1992). This tension field results in an interesting variety of perspectives about the CODP.
This literature study will address the following question: How can the phenomena CODP and the impact it has on processes be described? To answer this question this literature overview will roughly consist of two parts. The first part will be dedicated to the definition of CODP (Chapter 2), the difference between CODP for engineering and production processes (Chapter 3). Chapter 4 will describe the generally accepted theory on the impact positioning of the CODP has on process characteristics. The second part of this study will address divergent views on the positioning of the CODP. It consists of proposed positioning methods (Chapter 5), the use of dynamic CODP positioning (Chapter 6) and the role of CODP in mass customization and leagile paradigms (Chapter 7). This study will conclude with concluding remarks on the literature discussed.
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2. The customer order decoupling point
This first chapter will elaborate on the definition of the customer order decoupling point. In paragraph 2.1 a background of the introduction of the CODP will be given. Afterwards the evolved CODP definitions will be discussed. In the final paragraph the standardized CODP strategies will be introduced.
2.1 Background
The concept CODP was introduced as a strategic decision in a logistical context by German Sherman, a director at the management consulting firm McKinsey & company in 1984 (Sun, Jib & Suna, 2008). In his article “the rediscovery of logistics” he argues that in the logistical systems made for the relatively stable market situation of the 1960’s and 1970’s are becoming an increasing competitive disadvantage (Sharman, 1984). He describes six trends that are the underlying causes for this increasing disadvantage:
Decreasing production lifecycles
Growing range of customer tastes and demands
Shift of power from manufacturer towards retailer
Increasing cost of materials and distribution
Search for scale advantages
Flexibility introduced by computers
Sherman poses an integrated view to regain competitive advantage. This integrated view consist of three parts. The first part is the shift from an efficiency perspective to an effectivity perspective. This means a shift from a minimum amount of resources per process step to a minimum amount of processes needed to produce an end product. Secondly, he posed to redesign the production. In this step he states that “although the ways to manage the flows of materials are virtually infinite, the one key variable in every logistics configuration is the point at which the product becomes earmarked for a particular customer” (Sharman, 1984). Last step defined by Sharman, is to ensure the production process stays balanced to the desired competitive position. The second step of this integrated view, the point of ‘earmarking’ has been evolved as the concept customer order decoupling point as it is regarded today.
2.2 Definition Customer Order Decoupling Point
Sherman (1984) describes the customer order decoupling point as a point in process where the product is earmarked for a specific customer. Although this is a striking visualisation, in this literature study the more formal definition of Olhager (2003) is used: “The customer order decoupling point is the stage where a particular product is linked to a specific customer
6 order”. This definition can be expanded with the fact that at this point the customer specifications are taken in to account. Therefore, the CODP is characterised as the point where the product specifications get frozen and the last point where inventory is held (Sharman, 1984). Other definitions including Mather (1993) emphasize the role of strategic stock at this point. This is the reason the CODP is mostly depicted as an image of a stock pictogram (CODP
).
The most important result of implementing a CODP is that the material flow is divided into two sub processes: the pre- and post-CODP processes. This leads to a schematical representation as depicted in figure 2-1. The main difference between the processes is that the pre-CODP process is forecast driven based on speculation and the post-CODP process is demand driven based on the customer orders. There is a strong consensus among literature that these pre- and post-CODP operations are significantly different (Olhager, 2010). These differences in characteristics will be addressed in chapter three.
Pre-CODP
processes Pre-CODP processes
Input CODP Output
Order specifications
.
Figure 2-1 Schematic representation of a production chain
The CODP can describe a material flow on different aggregation level. Whereas Olhager & Ostlund (1990), Giesberts & Van der Tang (1992), Van der Vlist, Hoppenbrouwers, & Hegge, (1997), Lethonen (1999), D’Alessandro & Baveja (2000), and van Donk (2001) primarily deal with production or manufacturing operations. Sharman (1984), Hoekstra & Romme (1992), Fisher (1997), Pagh & Cooper (1998) and Mason-Jones, Naylor, & Towill (2000) primarily deal with supply chains. Both manufacturing and supply chain processes are material flows upon which transformation processes are performed. Thus the distinction between these processes is a matter of scope. Therefore in this literature review no distinction is made.
In this literature overview the term CODP is used since it corresponds with the direct translation for the most frequent used Dutch term (Klant-Order-Ontkoppel-Punt). In the studied literature a broader terminology is used that would suffice for the customer order decoupling point considering the definition. The terms order penetration point, order fulfilment strategy and product delivery strategy are found as equivalents as the CODP. Also in some cases only the transition from push to pull processes where discusses or the use of the CODP
7 strategies without using the term CODP itself. These CODP strategies will be discussed in the next section.
2.3 CODP strategies
The CODP can be placed in different positions in the value chain. By this placement the respective lengths of the pre- and post-CODP processes is determined. There are four commonly acknowledged CODP positions, which on their place correspond with different CODP strategy names. These four strategies are: Make-to-stock (MTS), assemble-to-order (ATO), make-to-order (MTO) and engineer-to-order (ETO) (Wikner & Rudberg, 2005). The most common representation of these strategies is represented in figure 2-2.
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MTS ATO MTO ETOValue-added material flow
Raw
materials productsFinished
Speculation Speculation Commitment Commitment Speculation Sp. Commitment Com.
Figure 2-2 CODP strategies the make-to-stock, assemble-to-stock, make- to-order and engineer-to-order strategies. (Wikner & Rudberg, 2005)
In this representation there are three value adding processes identified: engineering, fabrication (of intermediate parts) and assembly, as is depicted in figure 2-3. In the case of an engineer-to-order strategy the customer specifications are entered before starting the engineering phase and the production and assembly are customer specific. In the case of make-to-stock the engineering has been done before the customer specifications are known, but before starting production the customer specifications are entered, resulting in a customer specific production and assembly. In the case of the assemble to order the engineering and production have been done before entering the customer specifications. Than only the assembly will be customer specific. In the last case of make to stock all activities are performed without any customer specific processes.
8 Engineering Fabrication
Input Assembly Output
MTO
ETO ATO MTS
Figure 2-3: Value added activities and the related CODP strategies
Besides these commonly referred strategies, there are other variants found in literature, for example: Purchase-to-order, ship-to-order, ship-to-stock and design-to-order. However there are endless CODP strategies possible. It depends on what value added activities are performed and in what order. Some will have a standardized name while in other cases a CODP strategy will have not.
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3. Separation of engineering and production CODP’s
The CODP strategies in Chapter 2 describe the traditional view of production and engineering as a sequence where the engineering (or design) precedes the production. In this sequential view it is impossible to start with production activities before the final design is known (Wikner & Rudberg, 2005). In practice it is easy to give examples where production activities are performed while the design is not fully committed. Take for instance glasses. The frames and standardized lenses are pre produced however the “engineering” is performed under the customer specifications. Therefore this chapter will take a closer look to the separation of engineering and production CODP’s. The different perspectives is described in section 3.1, whereas section 3.2 addresses the, a combination of the engineering and production CODP. Finally, section 3.3 introduces a two dimensional approach to the CODP.
3.1 Engineering and Production CODP ‘s
In this chapter, the value added activities as presented in chapter 2 will be divided into two categories. Where fabrication and assembly are considered as production value added activities and engineering will be considered as a separate value added activities. By separating these categories it is possible to consider the production value added activities and the engineering value added activities to be non-sequential.
The production value added activities have a set of CODP strategies, being make-to-order, assemble-to-order and make-to-stock. Much like the production CODP’s the engineering CODP’s can be divided into three main categories. These categories are engineer-to-order (ETO), adopt-to-order (AdTO) and engineer-to-stock (ETS). These CODP positions are depicted in figure 3-1.
A process is called engineer-to-order when all engineering and design activities are performed under customer commitment. An example of engineer-to-order can be found in architecture. There the design usually starts with a customer contacting an architect. The architect will start from scratch designing a building hence all design activities are performed under customer commitment. On the other extreme all engineering and design activities are performed under speculation without taking any customer specifications in to account. This is called engineer-to-stock. An example of design-to-stock can be found in consumer electronics. For consumer electronics the complete design of the product is performed under speculation.
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Engineering
Fabrication Assembly
MTO ATO MTS
ETO AdTO ETS
Fabrication designs Assembly designs
Figure 3-1 Engineering and production CODP positions
The last category, adopt-to-order, is when some of the engineering activities are performed under speculation and some of the activities are performed under customer commitment. Examples of adopt-to-order can be found in kitchen design. Usually a kitchen is build up out of predesigned sub segments (counters, cabinets etcetera). However the final design is tailored to the specific customer needs.
3.1 Production and engineering CODP combination
The three engineering CODP’s can also be combined with the production COPD’s. It is quite common to have a similarity in the amount of speculation in the engineering process and the production process (Wikner & Rudberg, 2005). For example the designed house will usually not only be engineered-to-order but also be made-to-order. Likely, the adopt-to-order designed kitchen will usually also be assembled-to-order and the designed-to-stock consumer electronics will usually be made-to-stock.
However this similarity is common, it is not necessary. For example it is possible that a product is completely designed-to-stock but the product is assembled to order. This is common for products with a high variability. Take the car luxury car business for example. None of the car engineering or design activities are performed under customer specifications, all modular parts are pre-designed. However the production of the car will be performed in an assemble-to-order matter. Also examples can be given for an engineer-to-stock, make-to-order combination. An example is in modern text book production. A book content of a book
11 can be ready made (engineer-to-stock) however it can be printed in a make-to-order matter. This is most common for low volume production.
3.3 Two dimensional CODP perspective
This chapter described the extension of the typical CODP perspective with a separation of the engineering (or design) perspective and the production perspective. In general there are three production CODP positions. Make-to-order, assemble-to-order and make-to-stock. The engineering perspective can also be generalized in three positions, engineer-to-order, adapt-to-order and engineer-to-stock. Combining these perspectives, results in nine CODP combinations, represented in figure 3-1. However, it is impossible to perform more production activities than design activities (Wikner & Rudberg, 2005). For example an engineer-to-order, make-to-stock combination is infeasible. As a result, six 2-dimensional perspectives on COPD can be formulated. Production dimension En gi ne er in g di m en si on 1 2 4 3 5 6 Infeasable COPD Strategies Feasable COPD Strategies
1 Engineer-to-order and make-to-order 2 Adapt-to-order and make-to-order 3 Engineer-to-stock and make-to-order 4 Adapt-to-order and assemble-to-order 5 Engineer-to-stock and assemble-to-order 6 Engineer-to-stock and make-to-stock Generalized 2-dimensional COPD strategies
MTO ATO MTS ET S A d TO
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4. Pre- and post CODP process characteristics
In chapter 2 it was already pointed out that there is a strong consensus among literature that pre- and post-CODP operations are significantly different. This chapter addresses how these pre- and post-CODP processes differ. The first section gives an overview of the typical pre- and post-CODP performance characteristics. From this overview the typical motivators for CODP shifting will be derived in section 4.2. The next section presents the typical attributes of the processes (section 4.3). In the last section (4.4) a close look is taken at one of the biggest contradictions, the tension between variability and cost effects.
4.1 Typical pre- and post-CODP performance characteristics
To be able to describe the characteristics of a process, a set of assessment criteria have to be comprised. To give a full representation of criteria, this literature study combines supply oriented criteria (Bikker, Analyse en ontwerp van de Produktie-organisatie) with demand oriented characteristics of Hill & Hill (2009). Consequently, the set of assessment criteria that will be addressed are:
Production cost
Flexibility
Product lead time
Risk
Quality
Control
Innovative power.
Consensus can be found in literature on how the processes perform on each of the characteristics above. An overview of the points of general point of view in literature is presented in table 4-1.
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Characteristic Point of view pre-CODP pr.Advantage post-CODP pr.Advantage
Production cost
Productivity The more standardised activities, as in pre-CODP processes the higher the productivity
Machinery occupation The more decoupled the production the more levelled the production rate and thereby the higher the machine occupation Inventory cost The more activities performed under speculation the more the
need for inventory Flexibility
Volume flexibility The more activities that are performed under commitment the more flexbile the process is towards volume flexibility
Product flexibility The earlier the customer specifications are known the more the product possibilities can be offered
Product lead time The more activities that are performed before the customer
order is known, the shorter the product lead time is. Risk
Inventory The higher the inventory the higher the risk. And pre-CODP processes need more inventory
Meeting delivery com. The more the that are activities performed under commitment, the more risk that the commitment is not met
Quality Although the quality control is typically different (process vs
product quality focus) there is no advantage to pre- or post-CODP processes
Control The more activities performed under speculation, the more
predictable the process is. And predictability enhances stable control
Inovative Power The more responsive to the customer demand the more
innovative companies tend to be
Table 4-1 Literature overview on characteristics in pre or post CODP processes
4.2 Motivators for upstream and downstream shifting
On the basis of the characteristics shown in table 4-1, main motivators for upstream and downstream shifting can be presented. The main drivers for upstream shifting are reduction of customer lead time and increase the production efficiency. Since more activities are performed before the customer order is placed, the lead time will decrease. The production efficiency can also be increased since the production is decoupled from the customer demand, enabling more leveled, pre-planned and standardized production. However, when the CODP is shifted upstream the production also increases the risk of the speculation based production and will be unable to accommodate product customization (Olhager, 2003).
The main driver for downstream shifting is to increase the knowledge of the customer order at the time of production. This knowledge enables higher level of customer specific customization, reduces the need for safety stock and reduces the need for speculation based production. On the other hand, more excess production capacity should be built in to meet the customer lead time demands (Olhager, 2003).
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4.3 Typical attributes pre- and post-CODP processes
Besides the difference in process characteristics, there is also a significant difference in (organizational) attributes. The attributes are a derivative of the production characteristics, and provide a general understanding of the attributes found in practice. An overview of the typical pre- and post-CODP attributes is given in table 4-2. These attributes are comprised of different sources (Olhager (2003), Visser & van Goor (2006) & Miltenburg (2005)).
Attributes Pre-CODP processes Post-CODP processes
Product type Standard, commodities Special
Product range Predetermined, narrow Wide
Demand High volume, predictable Low volume, volatile
Competitive advantage Price, delivery speed Design, flexibility
Process Line, high volume batch Job shop, low volume batch
Contol Based on forecast Based on orders
Facilities layout Product focus Process focus
Quality Process quality focus Product quality focus
Organisation Centralised, hierarchical Decentralised, coaching
Employee type Specialist, 8 hours a day Generalist, 6-10 hours a day
Production planning Rate based material planning Time phased material planning
Delivery promise Based on stock availability Based on lead time agreement and
capacity availability
Software systems Simple MRP package Complex ERP package
Performance measures Cost, productivity Flexibility, delivery lead times
Risk Unsellable products Lead time, available capacity
Table 4-2 Typical pre- and post-CODP process attributes
4.4 Relation between production cost and product variability
It is generally acknowledged that having an higher product variability decreases the ability to produce efficiently. Also an higher product standardization increases the ability to produce efficiently (Pil & Holweg, 2004). In the motivations for up- and downstream CODP shifting these adversaries play an important role. To give a better insight relation between variability and cost effects, an overview of points of view is presented in table 4-3.
15 Dowell (2006), Zipkin (2001), Increased product variety allows a closer match between
Agrawal (2001), Randall (2001), customer preferences and offered products, but, on the other Gimeno (1999), Ulrich (1998) hand, higher product variety could lead to operational
inefficiencies
Dowell (2006) A firm’s degree of breadth within a market affects its performance and its very survival, making productline breadth one of the most important strategic choices that a firm must make
Fujita (2002) The optimization of product variety must compromise between different objectives
Kim (1999) Higher product variety increases overhead, administrative and manufacturing costs
Stalk (1988) By reducing product variety to half of its original size, productivity would be increased by more than 30%, while costs would be reduced by at least 17%
Berry (1997) The adverse cost and margin implications of adding product variety may depend on the misalignment between marketing and manufacturing strategies
Mather (1992) Unlimited product variety is clearly not the way to be successful
Yeh (1991) As the product line increases, variety related costs also increase dramatically
Kekre (1990) A broader product line helps to achieve higher market share, which in turn would lower manufacturing costs and lead to higher profitability
Hayes (1984) A broad product line would result in high unit costs due to ever increasing overhead expenses
Point of view
References Positive effects
of variability
Cost effects of variability
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5. CODP positioning methods
The first part of this study addressed the the concept CODP. It concluded that the positioning of the CODP influences the performance of the process. This chapter presents different methods that can be used to decide on the positioning of the CODP. These methods can be divided in three categories. First perspective discussed, describes methods based on a trade-off between process characteristics (section 5.1). The second section addresses methods based on a trade-off between the product and the customer demand. The last section (5.3) presents methods that are based on specific production characteristics.
5.1 Characteristics trade-off
In the previous chapter the typical characteristics of the pre- and post-CODP process have been presented. The trade-off positioning method is the most discussed method in literature and is based on the proposition that a process cannot perform well on every “yardstick” (Skinner, 1994). The trade-off method states that the process will inherit the pre- and post-CODP characteristics based on their respective relative lengths. So if the post-CODP is shifted forwards the process will inherit more post-CODP characteristics and if the CODP is shifted backwards it will inherit more pre-CODP characteristics. This pressure field is illustrated in figure 5-1. The trade-off method is basically about setting priorities and matching these priorities with the CODP-strategies.
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Value-added material flow Raw
materials productsFinished
CODP Pre-COPD
characteristics characteristicsPost-COPD
Figure 5-1: Trade-off pressure field on the CODP positioning
The trade-off method is often associated with the theory of order-winners and qualifiers. This theory states that not every “yardstick” has the same effect on the competitive advantage. The customer demands are separated in qualifiers, which represent a minimum level of fulfilment that is desired to even consider the product. After this qualifying level of fulfilment is reached surpassing the level will not create extra competitive advantage. On the other hand
17 order winners which do not have a minimal level of fulfilment but are essential to acquire orders (Hill & Hill, 2009).
The trade-off method is based on the fundamental assumption that the characteristics progress linearly throughout the process. For example that halfway through the process half the lead time is lapsed. In real processes this is mostly not the case since most processes do not pose linear characteristics (Zeng, Tseng, & Lu, 2006). Non linearity in processes characteristics can be illustrated by the production of cheese, which roughly consists of cheese production, cheese ripening and packaging. The production and the packaging of cheese take a fraction of the production time while the ripening can take up to years. The impact of this non linearity is that shifting the CODP does not have a linear effect on the process performances. This non linearity has given rise to divagated views in literature that will be discussed in following sections.
5.2 P:D ratio based methods
The P:D ratio describes the ratio between the total lead time of the product (P) and the total customer lead time of the product (D). Or in other words what percentage of the production should be performed to speculation to meet the customer lead time D. The P:D ratio is a term first described by Shigeo Shingo in his book about the Toyota production system (Mather, 1993). The P:D is visualized in figure 5-2.
Production time
Demand time
= P
= D Speculation neeeded
Figure 5-2: The P (production time) and D (demand time) of the P:D ratio
The general theory behind the P:D ratio is that a certain range of P:D ratio corresponds to a certain CODP strategy (Hoekstra & Romme, 1992). An overview of the corresponding production strategies is shown in figure 5-3. This figure shows that a P:D ratio larger than 1 indicates that the production time is longer than the demand time therefore part of the production should be performed under speculation. Hence it corresponds to either Make-to-stock or Assemble-to-order. Where if the P:D ratio is smaller than 1 production can be performed under a Make-to-order strategy. When the P:D ratio is smaller than 1 also a make-to-stock strategy is possible, however than the risk is increased, because there is more action performed under speculation than necessary (Mather, 1993).
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MTS ATO MTO ETOValue-added material flow Raw
materials productsFinished
Speculation Speculation Commitment Commitment Speculation Sp. Commitment Com. P/D >> 1 P/D < 1 P/D > 1 P/D = 1
Figure 5-3: CODP-strategies combined with the most preferred P:D ratio’s
Olhager (2003) described a variant on the P:D ratio. This positioning method identifies the relative demand volatility and the P:D ratio as the leading factors for the positioning of the CODP (Olhager, 2003). This method states that if the volatility is high a make-to-stock strategy would present to much inherent risk. On the other hand if the P:D ratio is larger than one a make-to-order strategy will not meet market demands. The last statement in this method is that products with high volatility and a P:D ratio larger than one can best be delivered using a assemble-to-order strategy. This method can be presented in a model, which is shown in figure 5-4.
R el at iv e de m an d vo la til ity P:D ratio H ig h Lo w < 1 > 1 MTO ATO MTS MTS ATO MTO 1
Figure 5-4: Position method based on the P:D ratio and the relative volatility
The main point of disagreement with the P:D ratio approach lies in the definition of the customer lead time. The reality is that there are four values of D (Wikner & Rudberg, 2005).
19 First of all the promised lead time, secondly the lead time the customer wishes, third the lead time that would provide a competitive edge and last the achieved customer lead time. Thereby the choice of production strategy is reduced to a choice of demand lead time. This discards all operational considerations. To illustrate, the delivery and production of fresh orange juice in a restaurant is considered. By the theory of the P:D ratio this process would be advised to be performed under a make to order situation since the production time is shorter than the time the customer expects to wait. However, in reality a restaurant or bar will make it to stock because it is much more efficient to produce a certain batch or orange juice than it is to produce a single cup.
5.3 Methods based on single production characteristics
The P:D ratio is a demand perspective view for the positioning of the customer order decoupling point. Many other positioning methods have their roots in the production perspective. In these methods the positioning of the CODP is lead by a single production characteristic.
The most common discussed production characteristic to have a determining impact on the positioning of the CODP is the product diversity profile of production. This profile is the result of dividing the product diversity at any given production stage through the total number of (potential) end products (Pil & Holweg, 2004). Typically this ratio increases through production. The most appropriate location of the CODP is where before the biggest increase in diversity, e.g. a production process of sofas. The model range is typically quite straightforward, but the use of cover fabric is typically quite high. Hence the production of the frames and filling is made to speculation and the fabric is applied according to the customer specifications. The reason for this positioning technique is the favorable storage cost and relative high flow of products or relative high batch size in the pre-CODP processes.
The second positioning method based on a production characteristic is the positioning of the CODP after the process bottleneck. By situating the CODP after the bottleneck the bottleneck process is placed in the forecast driven process phase and decoupled from the demand fluctuations (Olhager & Ostlund, 1990). Decoupling from demand fluctuations generally leads to a better utilization of the bottleneck. This method is most applicable for processes with a strong differentiation in production capacity, mostly introduced by large difference in capital intensity of machinery.
Another described positioning method is positioning the CODP before the most expensive production step (Zeng, Tseng, & Lu, 2006). By excluding this step the risks and storage cost resulting from the speculative production. Again this situation is most applicable for processes with a high differentiation of cost intensity. Figure 5-5 presents such a nonlinear process. This
20 situation could be found in jewelry production. Here it could be interesting to positioning the CODP right before the precious metal is molded since this step represents the most expensive activity.
Percentage of prodcution activities performed 100%
10 0% Pe rc en ta ge o f pr od uc tio n co st m ad e Relative inexpensive
production activities production activitiesRelative expencive Relative inexpensive production activities
0%
Figure 5-5: Process with a nonlinear production cost build-up
Besides the more common mentioned characteristics there also a set of less generally applicable positioning methods are found. The first is perishability characteristics. In case of diversity of perishability the CODP is typically laid before the increase in perishability (Soman, van Donk, & Gaalman, 2004). Another situation is in case of unpredictable and fluctuating demand. In that situation there are two approaches, shifting the CODP forward to reduce the risks of speculation or shifting the CODP far backward to level production and induce a better machine utilization (Lin & Shaw, 1998).
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6. Dynamic CODP positions
Previous chapters describe the CODP as a fixed point in the process. However most companies discern more than one CODP strategy in their production processes (Soman, van Donk, & Gaalman, 2004). This non-fixed CODP phenomena has led to a differentiated view on the COPD in literature; the dynamic CODP. This section describes three types of dynamic CODP that can be found in literature: operational hybridity (6.1), long term hybridity (6.2) and assortment hybridity (6.3).
6.1 Operational hybridity
Operational hybridity is the short term variation of CODP point caused by the characteristics of the customer orders and incidental factors. In this type four different causes for a dynamic CODP are distinguished. These causes are customer order flow, size of the customer order, level of the stock and general incidental factors.
Companies can decide to go with a dynamic CODP on the basis of the customer order flow. They can decide to either shift the CODP forward or backward. Usually the CODP will be shifted backward in times of little demand and will be shifted backwards in times of high demand. The main reason is that in times of little demand (intermediate) products can be produced and thereby the resources can be put to use (Sun, Jib, Suna, & Wanga, 2007). An example can be found in the aircraft industry: in times of low demand they resort to the production of “white” aircrafts, which can be made customer specific when the demand picks up. In times of high demand the CODP is shifted forwards, decreasing the risk and cost of speculative production. This type of dynamic CODP positioning is also fairly common in companies subject to seasonal demand having different CODP position in the high and low seasons.
The second category of operational hybridity is on the basis of size of the customer order. In case of an uncommon size order the CODP can be shifted forward or backward. Usually the CODP will be shifted forward in case of a relative large order and shifted backward in case of a relative small order (Giesberts & Van der Tang, 1992). The main reason is that either way the production efficiency can be increased. But also for large orders can be handled in a purchase-to-order matter to capitalize on purchase quantity advantages.
The third category is hybrid CODP positioning based on the stock level. Depending on the stock level the CODP can be shifted forwards or backwards. Usually when stock levels are high the CODP is shifted forwards and if the stock levels are low the CODP is shifted backwards (Soman, van Donk, & Gaalman, 2004). The benefit of incorporating the stock level in the
22 decision of the CODP is that smaller safety stock can be held while achieving equal service levels. For instance if a product is not in stock it can be made-to-order while if there is a high stock level products can be taken from stock. Even it can be preferable to use products made for other customers.
The final category having to do with short term operational dynamic CODP positioning are changes due to incidental factors (Giesberts & Van der Tang, 1992). Examples are dealing with cancellations of partly made products, changes due to quality issues of finished products or raw materials.
6.2 Long term hybridity
Besides the operational short term hybridity there is long term hybridity. Long term hybridity has to do with the evolution through a product lifecycle. During the different phases in the product life cycle the CODP can be shifted either forwards or backwards (A.L & Geunes, 2006). The most common pattern is that the product starts with CODP early in the process, than the CODP is shifted backwards and at the end of the product lifecycle the CODP is shifted forwards again.
This pattern has a strong relation to the risk profile of the product. In the beginning of the lifecycle the risk is relatively high, advocating an early CODP placement. In the maturity phase of a products lifecycle the risk is generally decreases making a later CODP position more interesting. In the decline phase of a product lifecycle the risk of speculation increases again advocating backwards shifting.
Typical examples can be found in the manufacturing of machinery. Here it is quite common to develop a product in close relation with the initial customer (engineer-to-order). Later the machine can be either developed in a standard product that is (partly) made based on speculation (make-to-stock or assemble-to-order). While in the later phase the product is not considered a standard product anymore the CODP can be shifted forwards by a make-to-order strategy.
6.3 Assortment hybridity
The last category is permanent hybridity based on the assortment of the products. This concerns processes where the products produced in the process cannot be characterized with a single CODP strategy. This type of hybridity occurs in two forms, that a process produces standard products as well as customer specific products and that a company has hybrid strategies for the production of one finished product (Van Donk, 2001). The first instance represents many companies usually which mainly make standard products. They will make
23 customer specific products if the customer is willing to pay a premium. Examples can be given for heating systems companies and agricultural equipment. The second type, where within a specific product structure dynamical CODP positioning can take place. Typically these companies pre produce or pre purchase long lead time items while the general CODP strategy can be engineer-to-order.
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7. CODP in mass customization and leagile production
In the field of manufacturing operations two paradigms have gained increasing interest after the turn of the millennium, mass customization and leagile production (Voss, 2005). These paradigms are sometimes referred to as next generation or IT enabled strategies. In both these paradigms the point of entry of the customer order play a vital role and therefore they have a relation to the CODP. In this chapter the relation between these paradigms and the CODP will be examined. In section 7.1 mass customization will be introduced. In section 7.2 and 7.3 the relation and differences between mass customization and the CODP will be addressed. Leagile production will be explained in section 7.4 and the relation between leagile production and the CODP will be presented in section 7.5.
7.1 Mass customization
Davis introduced the term mass customization in 1987 and today it is used as a way of offering high variability at a reasonable price by mass production (Rudberg & Wikner, 2004). It is a term most often used in commercial perspective. The rise of interest in mass customization is often associated with the rise of modern information technology as an enabling factor (Voss, 2005). However form a production point of view the conflict of mass production and high variability is easy to see. The perception is that the position of the CODP is key to the degree and type of customization that can be provided (Duray, Ward, Milligan, & Berry, 2000).
7.2 CODP and mass customization typology
Mass customization can occur at various points along the process, ranging from relative simple adaptation of delivered products to customization in design, production and delivery. The customization point and the CODP therefore can have a correlation based on the point in the process. The correlation of the typology used in literature of mass customization and the CODP typology is presented in table 7-1. From this overview the mass customization typology can be translated in terms of the CODP position. However, not in all literature all CODP points are labeled.
25
Lampel and Mintzberg
(1996) Gilmore and Pine (1997) Da Silveira (2001) Duray (2000)
ETO Pure customisation Collaborative Design
MTO Fabrication Fabricatiors
ATO Tailored customisation Adaptive Assembly Assemblers
Customized standardisation
MTS Pure standardisation Standardisation
Non related Segmented standardisation Cosmetic Additional custom work Involvers Transparant Package and distribution Modulizers
Usage
Mass customization typology CODP typology
Table 7-1 Mass customisation typology in relation to the CODP typology
7.3 The “mass” of mass customization
Although the typology of mass customization can be translated in the CODP typology, their goals are profoundly different (Rudberg & Wikner, 2004). Mass customization focusses on the production scale versus variability trade-off, which is only one characteristics couple of the CODP. Mass production is the term used to combine efficient, large scale production with high product variability. In production oriented literature this is usually combined with the product process matrix (Da Silveira, Borenstein, & Fogliatto, 2001). Traditionally, it has been argued that companies are positioned along the diagonal of the matrix. But for mass customization processes the aim is to divert from this diagonal. This has been illustrated in figure 7-1. In this literature review only the correlation with the CODP is addressed. The means of achieving mass customizations are very divers and would pose a separate literature review.
Pr
od
uc
t
va
rie
ty
Production volume
H ig h Lo w Low High Proje ct Batch prod uctio n Mass prod uctio n Cont inuou s prod uctio n Mass customization26
7.4 Leagile production
Leagile is a merge of the “lean” and “agile” paradigms introduced by Naylor (1997). Combining agility and leanness in one process divided by the CODP has been termed leagile production (Mason-Jones, Naylor, & Towill, Engineering the leagile supply chain, 2000). The lean and agile paradigms are distinctively different and therefore have different characteristics (Christopher & Towill, 2000). Lean focusses on the elimination of waste in the process. One of the key success factors for lean manufacturing is the ability to enable a level schedule (Naylor & Naim, 1997). On the other hand, agile focusses on flexible and efficient response to unique customer demand and capitalize on opportunities in a volatile market place (Naylor & Naim, 1997). An agile system is built around flexibility, emphasizing on flexible production sizes and changeovers. These focusses can be translated into respectively cost based and flexibility based requirements. An illustration in terms of the Delft System approach (Veeke, Ottjes, & Lodewijks, 2008) is depicted in figure 7-2.
Lean process
Output
Input
Cost based
requirements
performance
Cost based
Agile process
Output
Input
Flexibility based
requirements
Flexibility based
performance
Figure 7-2 Lean and agile processes portrayed in terms of the delft systems approach
7.5 Leagile production and the CODP
Figure 7-3 depicts a leagile production process. Leagile production is the production process divided in two parts, a lean and an agile part.. Thereby the cost effective lean process is first and is followed by the responsive agile process. The CODP is the division of these processes. Forming a speculative lean process and a customer driven agile process. Thereby the lean process is “protected” from the demand fluctuation and the agile process can be even more responsive since the length of the process performed under customer demand is reduced. Roughly the same conclusions are presented by Olhager and Ostlund (1990) arguing that a
27 push strategy is applicable for pre-CODP processes and a pull strategy is applicable for post-CODP processes.
Lean process
Agile process
Input
CODP
Output
Flexibility based
requirements Flexibility basedperformance Cost based
requirements performanceCost based
Figure 7-3 A leagile process portrayed in terms of the delft systems approach
The main criticism of leagile production is that the lean process is performed in a “push” matter where one of the fundaments of lean is that the production should be performed under a “pull” matter. The proposed defense is that process could be seen as a “pull” process from an internal customer. This internal customer accepts longer lead times since he has a stock which only periodically should be replenished (Christopher & Towill, 2000).
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8. Concluding Remarks
Although there is a general consensus on the phenomena and the characteristics associated with the CODP, the methods for placing the CODP differ in literature. The general perception is that CODP is, strategically positioned static point in the process. However in practice a dynamical CODP is often used. Although no winning CODP blueprint can be comprised, strategically positioning of the CODP is an powerful tool in an operations engineer toolbox. This literature review has provides an insight of the possibilities offered of this tool.
Throughout the literature review arguments are given on where the CODP should be positioned. Although these arguments are useful the they should be put in perspective by the central question: “does it create more value overall?”. Whether more value is created depends on the specific cost-buildup of production and the specific revenue-buildup of sales.
In practice most value can be created when both aspects are mediated. An illustrative figure that depicts this value creation is show in figure 8-1. From this viewpoint the CODP discussion can be generalized in a tension field between cost and revenue perspective. Positioning back- or forwards shifting should therefore always be motivated in terms of value creation. This reduces the argument of CODP positioning to two possible arguments. The cost reduction by CODP shifting is larger than the reduction in revenue or the revenue increase is larger than the cost increase.
Cost minimalisation focus M on et ar y eq ui va le nt Asymptote of maximum revenue Asymptote of minimal cost Revenue maximisation focus
Section of value creation
29 The cost- and revenue-buildup are unique for every company. Therefore the proper placement method of the CODP is also unique for every process. For every company different arguments will hold. This makes the variety of business case examples found in literature just as - or maybe more - interesting than the theory found. A variety of case examples can be found on printed packages boxes (Olhager & Ostlund, 1990), trucks (Van der Vlist, Hoppenbrouwers, & Hegge, 1997), pulp and paper (Lehtonen, 1999), chemicals (D’Alessandro & Baveja, 2000), food processing (Van Donk, 2001) and dental implants (Olhager, 2003).
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