Competitive advantage based purchasing matrix - A portfolio-approach to differentiated purchasing strategy

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1 Competitive advantage based purchasing matrix - A portfolio-approach to differentiated purchasing strategy Jenny Bäckstrand*, Fredrik Tiedemann and Eric Hedén School of Engineering, Jönköping University, PO Box 1026, SE Jönköping, Sweden , jenny.backstrand@jth.hj.se, fredrik.tiedemann@jth.hj.se, eric.heden@fazer.se Summary The aim of this paper is to describe a conceptual alignment between the certainty-customization framework (Bäckstrand, 2012) and Kraljic s purchasing matrix (Kraljic, 1983). This will enable companies that manufactures both standard and customer unique products to develop differentiated purchasing strategies for the constituent based on the products competitive priorities and order winners. Through this distinction, different categories in the Kraljic-matrix needs to be handled differently based on the position in regard to the customer-orderdecoupling-point and its level of customization. Key words: Competitive Advantage based Purchasing matrix, differentiated purchasing, customer order unique Submission category: working paper Background The trend of outsourcing and sourcing globally has led to longer supply chains, as firms increasingly move production offshore or source from more distant locations (Christopher, 2011). A drawback from this might be that the customer order decoupling point 1 (CODP) is transferred from the manufacturer (internal) to the supplier (external) (Bäckstrand, 2012; Wikner and Bäckstrand, 2011). The position of the CODP, in regard to the supply chain, has received much attention by other scholars (e.g. Borgström and Hertz, 2011; Lamming et al., 2000; Mason-Jones and Towill, 1999; Rudberg and Wikner, 2002). Bäckstrand (2012) targets her research on how the supplier interaction should be handled with regard to the position of the CODP. Furthermore, since the CODP might be located outside of the manufacturer, the firms manufacturing strategy must be extended and also include the supplier interaction (Bäckstrand, 2012). This identifies a need for strategic alignment and knowledge transfer between manufacturing and purchasing functions, also highlighted by other scholars (e.g. Rebolledo and Jobin, 2013; Soni and Kodali, 2011). To reduce these problems and provide guidance for manufacturing companies who experience them, Bäckstrand (2012) developed a method for Customer-driven Purchasing (the CDPmethod). The method was developed together with six companies in a research project called KOPeration, and was subsequently implemented at four of them. The aim of the method is to investigate how the customer requirements should impact the supplier interactions and how the requirements can be incorporated in the purchasing strategy. The method contributes to improved interaction with suppliers as well as improved internal communication and 1 The CODP as the separation of the part of the supply chain focused on satisfying the customer and the part of the supply chain based on planning Hoekstra and Romme (1992). This means that the CODP is the point in the flow of goods that separates forecast driven production (speculation) from customer order driven production Giesberts and van der Tang (1992).

2 Efficiency impact integration (Bäckstrand et al., 2013), this is also proved as a competitive advantage by other scholars (e.g. Huo, 2012; Pagell, 2004). Problem background In a Master s thesis, Hedén and Tiedemann (2014) analyzed the CDP-method in order to develop and refine the method. They concluded three areas of improvement: 1. To further define and develop Step 8 - Analyze in the CAP-matrix 2. To strengthen the alignment of strategies by using synchronized KPI s 3. To further develop Step 6 - Analyze in the customization-perspective framework This paper builds on the first area of improvement, the development of step 8 of the CDPmethod, where are analyzed in the CAP-matrix (Competitive Advantage based Purchasing-matrix). The CAP-matrix is based on the Kraljic-matrix (Kraljic, 1983), but where the y-axis reflects order winner impact rather than profit impact (Wikner and Bäckstrand, 2011). Since the general order winners (or competitive priorities) for pre-codp are different from the order winners of post-codp (e.g. Fisher, 1997; Hallgren and Olhager, 2006; Krause et al., 2001; Olhager, 2003) two different CAP-matrixes with efficiency impact and responsiveness impact respectively have been identified (Bäckstrand, 2012), see Figure 1. Efficiency focus CODP Responsiveness focus Figure 1. Two CAP-matrixes, pre- and post-codp. The description from Olsen and Ellram (1997) as well as Gelderman and Semeijn (2006), together with Fisher s (1997) description of an efficient supply chain summarizes the term efficiency focus used within this research while the description from Olsen and Ellram (1997), Kraljic (1983) as well as Gelderman and Semeijn (2006), together with the thoughts from Christopher et al. (2006) regarding an agile and responsive supply chain, and Fisher s (1997) description of an responsive supply chain summarizes the term responsiveness focus. In this paper we will analyze the CAP-matrix while also regarding the level of customization of the purchased item (Lampel and Mintzberg, 1996; Wikner and Bäckstrand, 2012). The levels of customization are according to Bäckstrand (2012) defined as customer-generic (CG), customer-unique (CU), and customer-order-unique (COU). Customer-generic are generic to both products and customers. A customized product might be composed of both standard (generic) and customized. A customized product can either be customer-unique (CU) or customer-order-unique (COU). A CU product is a product that is customized uniquely for a specific customer. The product can thus not be sold to an alternative customer. However, the CU product could basically be a CG product that is made customer-unique at the last manufacturing stage (for example by attaching a customer-unique label). A CU product can be ordered again and again. A COU product is also a product that is unique to a specific customer. It is furthermore unique to this specific order, and a duplicate of the product is not likely to be

3 Customer generic Efficiency impact Customer unique Efficiency impact Customer order unique ordered again. Consequently, the level of customization is also connected to the volume and frequency of orders, assuming that orders with low level of customization (CG) in general have higher volumes and higher frequency than orders with high level of customization (COU) (Mattsson, 1987). When regarding the levels of customization together with the CODP, a certainty-customization framework is developed, see Figure 2. The grey upper left corner indicates that it is not viable to manufacture customer-order unique, or products, based on forecast. The two CAPmatrixes illustrated in Figure 1 equals the CAP-matrixes at the customer generic level in Figure 2. When increasing the level of customization, the appropriate order winners will change, and hence, five different CAP-matrixes are illustrated in Figure 2.? Figure 2. The certainty-customization framework with corresponding CAP-matrixes. The purpose of this paper is thus to develop differentiated purchasing strategies for purchased, based on their competitive priorities and their level of customization. Method Forecast-driven CODP Customer-order-driven Both the doctoral dissertation where the CDP-method was presented (Bäckstrand, 2012) and the Masters thesis where areas of improvements of the CDP-method was identified (Hedén and Tiedemann, 2014) used the concept of developing analytical conceptual models supported by empirical illustrations as described by Wacker (1998, 2008). The empirical illustrations are collected through case studies at: Ericsson AB in Borås (telecommunication), Fagerhult AB in Habo (professional lightning), Parker Hannifin AB in Trollhättan (hydraulic pumps) and Siemens Industrial Turbomachinery AB in Finspång (gas turbines), all in Sweden. The case

4 companies have all participated in two subsequent research projects KOPeration and KOPtimera, conducted and , where also the main author have participated. The collected empirical data has been triangulated, both between different data collection methods and between different companies, i.e. method and source triangulation (Williamson, 2002). Theory All the and material purchased by a company are not the same. Some are more important and critical to the firm s survival than others. Hence different procurement strategies, tactics and resources are to be used for different (Coyle et al., 2013). The quadrant techniques, matrix or portfolio model s in purchasing provides useful inputs for supply management decision makers. There has been much published research on portfolio models within purchasing (e.g. Bensaou, 1999; Nellore and Söderquist, 2000; Olsen and Ellram, 1997; Turnbull, 1990). However, the model by Kraljic (1983) is considered to be the first description of strategic purchasing (Beer, 2006) and a major part of the development of purchasing and supply chain management (Gelderman and van Weele, 2002). In 1983 Kraljic (1983) published a simple but yet effective framework for collecting marketing and corporate data, forecasting future supply scenarios and identifying available purchasing options as well as for developing individual supply chain strategies for critical and materials. This purchasing model aims at minimizing the supply risk and to make the most out of the company s buying power (Kraljic, 1983). According to Kraljic (1983) a company s need for supply chain strategy depends on two factors; Importance of purchasing and complexity of supply market. By using both these factors a matrix can be formed. The aim of this matrix is to identify which suppliers to develop a longterm relation with and which suppliers to keep at arm s length (Beer, 2006). By using these criteria, a company can sort all their purchased into four categories; leverage (LE), strategic (ST), non-critical (NC) and bottleneck (BN), as can be seen in Figure 1. Each of these categories needs a distinct purchasing approach. All these approaches differ regarding decision level as well as information required and main tasks assigned to them (Kraljic, 1983). Olsen and Ellram (1997) as well as Gelderman and Semeijn (2006) has investigated the same type of classification and provides information on how companies should handle the. should be purchased through efficient buying and optimized order volume. For NC Olsen and Ellram (1997) state that the buying company should strive towards supplier relationships that basically handle themselves. Gelderman and Semeijn (2006) has a similar suggestion, namely to implement e-procurement for these types of. Olsen and Ellram (1997) as well as Gelderman and Semeijn (2006) state that the companies should use these examples to reduce administrative costs. should be purchased by optimized order volume, companies should strive to exploit their full purchasing power for these kind of (Kraljic, 1983). The focus, according to Olsen and Ellram (1997) should be to consolidate the volumes over several product families and obtain a good price for these. Gelderman and Semeijn (2006) state that cost savings is perused for this kind of item and that suppliers should be evaluated against this criteria. should be handled with the main focus of securing supply of material, gaining a lower price for these is not the focus in purchasing situations (Gelderman and Semeijn, 2006; Kraljic, 1983). These have low strategic value and are at the same time difficult to manage (Olsen and Ellram, 1997). This is not a favorable situation and should therefore be avoided. An example of how to move from this situation is to work towards standardization (Gelderman and van Weele, 2002; Olsen and Ellram, 1997). should be given higher attention and the aim is to build long-

5 Efficiency impact term relationships with these suppliers (Kraljic, 1983; Olsen and Ellram, 1997). However, Gelderman and Semeijn (2006) mentions that it can be hard to accomplish a strategic partnership with these suppliers given the suppliers often prevailing upper hand in the power balance. Case study illustrations and analysis The improvement of Step 8 presented by Hedén and Tiedemann (2014) focus only on the lowest level of customization, the CG-level, and is used as a starting point for the analysis. supply risk The empirical investigation showed that the case companies worked with responsiveness focus for ST. Siemens initiative to implement a consignment stock to reduce supply lead-time is showing this. Also Parker, Ericsson and Fagerhult had this focus for ST. Fagerhult used a responsiveness focus for BN, due to them striving to reduce supply leadtimes for all with high supply risk, including BN. Ericsson attempt to reduce leadtime for BN if they purchase them with low frequency and if the item also has a high value. However, if the BN item has low value and is purchased with a high frequency, the focus is not to reduce the supply lead-time. In that case, Ericsson instead uses strategic buffers. Also, if the availability of an item is scarce Ericsson would use strategic buffers to ensure supply. The conclusion by Hedén and Tiedemann (2014) was that CG that are positioned upstream of the CODP and have a high supply risk according to the Kraljic-matrix, should be analyzed through a responsiveness focus. This is in contrast to the CDP-method (Bäckstrand, 2012), which suggest efficiency focus for all types of upstream of the CODP. These should be given more attention in a purchasing situation than the current efficiency focus suggests. The blue box to the left and the upper arrow of Figure 3 illustrates this transition towards responsiveness focus for Pre-CODP with high supply risk. CODP Efficiency focus Responsiveness focus Figure 3. Sourcing focus based on the level of certainty. However, considering the empirical findings regarding BN at Ericsson would suggest that value, volume and frequency of BN should determine if these should be purchased with efficiency or responsiveness focus. This is illustrated with the blue-shaded square at BN in Figure 3. Empirical data from Siemens is however somewhat contradictory to this result due to their focus on efficiency for all generic. Their transition to consumption based stock replenishment of this kind of is in line with the meaning of efficiency focus used within this research. On the other hand, there is also an initiative to implement consignment inventory for high value

6 with long supply lead-time. This could be seen as an example of reducing the supply leadtime for ST, which would be in line with this result. Furthermore, for the NC there are initiatives to let the suppliers be in charge for stock replenishment. This is interpreted as striving for a more efficient supply chain rather than a more responsive supply chain. But still, Siemens sees no direct value of purchasing ST and BN based on a customer order rather than forecast, which is contradicting to this result. However, one explanation for Siemens actions might be the specific competences needed to assemble a gas turbine, making the manual capacity rather rigid, whereas the other companies might use temporary workers in order to create a more flexible capacity. With level and rigid capacity, a level pace of assembly is used and the gas turbine assembly is thus conducted based on forecast. supply risk The literature states that one of the aims when purchasing with low supply risk is to reduce the manual intervention in purchasing situations (Gelderman and Semeijn, 2006; Olsen and Ellram, 1997). The supplier relationships should be easy to manage, with reduced administration costs. Furthermore, Kraljic (1983) state that the order volumes should be optimized, both for NC and LE. Parker has reduced the time spent on purchasing NC and LE. This is also done by Ericsson, which uses as little manual work as possible to purchase LE. Furthermore, Ericsson purchases NC with an efficiency focus, e.g. by the Wilson-formula lot-sizing technique. Fagerhult has also started to purchase NC with an efficiency focus rather than responsiveness focus, which is reflected by larger volumes purchased with lower frequency. This notion is also supported by Siemens aim to transfer responsibility for stock replenishment to their suppliers, which is a way for them to reduce the time spent on purchasing NC. Furthermore, letting the supplier be in charge of stock replenishment could be seen as a way to optimize the order volumes as the supplier can optimize their production in combination to distribution. The suggested improvement for CG positioned downstream of the CODP by Hedén and Tiedemann (2014) was that that imply low supply risk, according to the CAP-matrix should be purchased with an efficiency focus instead of a responsiveness focus. This is in contrast to the CDP-method, which suggest responsiveness focus for all types of upstream of the CODP. An example of this can be illustrated by screws and nuts that are needed downstream the CODP, and therefore can be purchased on an actual customer order. Even though this is possible, it would consume too much time, distract too much attention and create an unnecessary amount of work for the purchasing function. The orange box to the right and the lower arrow in Figure 3 illustrate this. However, considering the value, volume and frequency of some leverage, the trade-offs between efficient purchasing and tied up capital in inventory has to be regarded. It might thus be beneficial to keep responsiveness focus for some leverage item, illustrated with the orange-shaded square at LE in Figure 3. Result By analyzing how the case companies actually worked with the CDP-method, an improvement of step 8 in the CDP-method was suggested by Hedén and Tiedemann (2014). The new way of working with this step is a combination of Kraljic s (1983) portfolio analysis and Fisher s (1997) supply chain design strategies. The analysis by Hedén and Tiedemann incorporates the supply risk as defined in the Kraljic-matrix (1983) to a greater extent and show that this factor divides the focus regarding efficiency or responsiveness rather than solely the CODP. This means that companies should aim to use responsiveness focus to cut supply lead-times and push the with high supply risk downstream of the CODP. On the other hand, with low

7 Customer generic Efficiency impact Customer unique Efficiency impact Customer order unique supply risk should instead be purchased with an efficiency focus. This does not automatically move them upstream of the CODP, but it is not seen as problematic if that would be the consequence. Furthermore, this analysis treats LE and NC as functional products as described by Fisher (1997) and standard products according to Christopher et al. (2006). Moreover, ST and BN are treated as innovative products, as described by Fisher (1997) and special products according to Christopher et al. (2006). However, in order to design a differentiated purchasing strategy also the value, volume and frequency of should be considered. The effect of different volumes and frequencies is somewhat included when the level of customization of the purchased are regarded and this dimension also differentiates between the different competitive priorities. Discussion The CAP-matrixes at the lowest level of customization, the customer generic level, in Figure 4 has already been discussed. At the highest level of customization, customer-order-unique, the purchasing strategy for forecast driven is to aggressively decrease lead time in order to make them customer-order-driven. For customer-order-driven the competitive priorities are quality and delivery precision (order qualifiers), product mix flexibility and design (order winners) (Hallgren and Olhager, 2006). Consequently, on item level, it is not likely to find an item that is classified as low supply risk (NC or LE) according to Kraljic, functional according to Fisher or standard according to Christopher in this quadrant of the certainty-customization framework. This in illustrated with a red and a red-shaded square in Figure 4.? Forecast-driven CODP Customer-order-driven Figure 4. CAP-matrixes regarding the level of certainty and level of customization.

8 For the CAP-matrixes at the customer unique level, the competitive priorities are not as unanimous as for the highest and lowest level of customization. This is mainly due to that volume and frequency of a repeated customer order might differ indefinitely. However, in general, if the volume and frequency is high and level, the customer unique could, from a purchasing strategy perspective, be treated as customer generic. Nevertheless, the competitive priorities that makes the item customer unique needs to be regarded e.g. product mix flexibility and/or design flexibility. On the other hand, if the volume is low or the frequency is low or uneven, the should rather be treated as customer-order-unique, thus demanding a purchasing strategy where all are purchased after the CODP. The main competitive priority is hence lead time, but since the item is order unique also product development lead time and design flexibility are regarded as important. Conclusion In this paper we have tried to illustrate the need to differentiate the purchasing strategy, not only based on the portfolio-approach suggested by Kraljic (1983), but also based on the level of certainty of the demand (forecast driven or customer-order driven) and the level of customization of the purchased item, in order to emphasize the competitive priorities that the purchasing strategy needs to support. The conceptual alignment between the certaintycustomization framework (Bäckstrand, 2012) and the Kraljic-matrix (Kraljic, 1983) was thus described. Further research In further research the customer unique level of customization needs to be further analyzed based on volume and frequency of orders. Also, the zone between forecast-driven and customer-order-driven flow, the customer order decoupling zone (Wikner and Rudberg, 2005) might need further investigation. Acknowledgements This research has been performed in collaboration with the four case companies, based on the KOPeration project, covering the alignment of purchasing strategy with operations strategy to pursue customer-driven purchasing, and the project KOPtimera, focusing on customerdifferentiated supply. The projects are funded and supported by the Swedish Knowledge Foundation, Jönköping University, and the participating companies.

9 References Beer, J., To make or to buy - that is (still) the question. Efficient Purchasing 1, Bensaou, M., Portfolios of buyer-supplier relationships. Sloan Management Review 40, Borgström, B., Hertz, S., Supply Chain Strategies: Changes in Customer Order Based Production. Journal of Business Logistics 32, Bäckstrand, J., A Method for Customer-driven Purchasing - Aligning Supplier Interaction and Customer-driven Manufacturing, School of Engineering. Jönköping University, Jönköping, Sweden. Bäckstrand, J., Johansson, E., Wikner, J., Andersson, R., Carlsson, B., Hjertén, A., Kornebäck, F., Kärnborg, B., Malmstedt, A., Ohlson, N.-E., Spaak, B., A method for customer-driven purchasing, 20th International Annual EurOMA Conference, Dublin, Ireland. Christopher, M., Logistics and Supply Chain Management, 4 th ed. Pearson, London, UK. Christopher, M., Peck, H., Towill, D., A taxonomy for selecting global supply chain strategies. International Journal of Logistics Management, The 17, Coyle, J.J., Langley, C.J., Novack, R.A., Gibson, B.J., Managing supply chains : A logistics approach, 9 th ed. Sout -Western, Cengage Learning. Fisher, M.L., What Is the Right Supply Chain for Your Product? Harvard Business Review 75, Gelderman, C.J., Semeijn, J., Managing the global supply base through purchasing portfolio management. Journal of Purchasing & Supply Management 12, Gelderman, C.J., van Weele, A.J., Direction through Purchasing Portfolio Management: A Case Study. The Journal of Supply Chain Management: A Global Review of Purchasing and Supply 38, Giesberts, P.M.J., van der Tang, L., Dynamics of the customer order decoupling point: impact on information systems for production control. Production Planning & Control 3, Hallgren, M., Olhager, J., Differentiating manufacturing focus. International Journal of Production Research 44, Hedén, E., Tiedemann, F., How to improve the inbound flow of a manufacturing company, Jönköping International Business School. Jönköping University. Hoekstra, S., Romme, J., Integrated Logistics Structures: Developing Customer Oriented Goods Flow, 1 st English ed. Industrial Press, New York, NY. Huo, B., The impact of supply chain integration on company performance: an organizational capability perspective. Supply Chain Management: An International Journal 17, Kraljic, P., Purchasing Must Become Supply Management. Harvard Business Review 61, Krause, D.R., Pagell, M., Curkovic, S., Toward a measure of competitive priorities for purchasing. Journal of Operations Management 19, Lamming, R., Johnsen, T., Zheng, J., Harland, C.M., An initial classification of supply networks. International Journal of Operations & Production Management 20,

10 Lampel, J., Mintzberg, H., Customizing Customization. Sloan Management Review Fall, Mason-Jones, R., Towill, D.R., Using the Information Decoupling Point to Improve Supply Chain Performance. The International Journal of Logistics Management 10, Mattsson, S.-A., Metodkoncept för MPS planeringsmiljöns betydelse för val av planeringsmetod. Mekanförbundets Förlag, Stockholm, Sweden. Nellore, R., Söderquist, K., Portfolio approaches to procurement: Analysing the missing link to specifications. Long Range Planning 33, Olhager, J., positioning of the order penetration point. International Journal of Production Economics 85, Olsen, R.F., Ellram, L.M., A portfolio approach to supplier relationships. Industrial Marketing Management 26, Pagell, M., Understanding the factors that enable and inhibit the integration of operations, purchasing and logistics. Journal of Operations Management 22, Rebolledo, C., Jobin, M.H., Manufacturing and supply alignment: Are different manufacturing strategies linked to different purchasing practices? International Journal of Production Economics 146, Rudberg, M., Wikner, J., The customer order decoupling point: definition and application areas, In: Olhager, J., Persson, F., Selldin, E., Wikner, J. (Eds.), 4 th Research and Application Conference on Logistics and Operations Management [PLANs forsknings- och tillämpningskonferens], Linköping, Sweden, pp Soni, G., Kodali, R., A critical analysis of supply chain management content in empirical research. Business Process Management Journal 17, Turnbull, P.W., A Review of Portfolio Planning Models for Industrial Marketing and Purchasing Management. European Journal of Marketing 24, Wacker, J.G., A definition of theory: research guidelines for different theory-building research methods in operations management. Journal of Operations Management 16, Wacker, J.G., A conceptual understanding of requirements for theory-building research: Guidelines for scientific theory building. Journal of Supply Chain Management 44, Wikner, J., Bäckstrand, J., Aligning operations strategy and purchasing strategy, 18 th International Annual EurOMA Conference, Cambridge, UK. Wikner, J., Bäckstrand, J., Decoupling points and product uniqueness impact on supplier relations, 19 th International Annual EurOMA Conference, Amsterdam, The Netherlands. Wikner, J., Rudberg, M., Introducing a customer order decoupling zone in logistics decision-making. International Journal of Logistics: Research and Applications 8, Williamson, K., Research methods for students, academics and professionals: information management and systems, In: Harvey, R., Ferguson, S. (Eds.), Topics in Australasian Library and Information Studies, 2 nd ed. Centre for Information Studies, Charles Sturt University, Wagga Wagga, NSW, Australia.