The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/0144-3577.htm IJOPM 24,12 Linking SCOR planning practices to supply chain performance An exploratory study Archie Lockamy III Samford University, School of Business, Birmingham, Alabama, USA 1192 Kevin McCormack DRK Research and Consulting LLC, Birmingham, Alabama, USA Keywords Supply chain management, Performance measurement Abstract As supply chains continue to replace individual firms as the economic engine for creating value during the twenty-first century, understanding the relationship between supply-chain management practices and supply chain performance becomes increasingly important. The Supply-Chain Operations Reference (SCOR) model developed by the Supply Chain Council provides a framework for characterizing supply-chain management practices and processes that result in best-in-class performance. However, which of these practices have the most influence on supply chain performance? This exploratory study investigates the relationship between supply-chain management planning practices and supply chain performance based on the four decision areas provided in SCOR Model Version 4.0 (PLAN, SOURCE, MAKE, DELIVER) and nine key supply-chain management planning practices derived from supply-chain management experts and practitioners. The results show that planning processes are important in all SCOR supply chain planning decision areas. Collaboration was found to be most important in the Plan, Source and Make planning decision areas, while teaming was most important in supporting the Plan and Source planning decision areas. Process measures, process credibility, process integration, and information technology were found to be most critical in supporting the Deliver planning decision area. Using these results, the study discusses the implications of the findings and suggests several avenues for future research. International Journal of Operations & Production Management Vol. 24 No. 12, 2004 pp. 1192-1218 q Emerald Group Publishing Limited 0144-3577 DOI 10.1108/01443570410569010 Introduction Increasingly, firms are adopting supply-chain management (SCM) to reduce costs, increase market share and sales, and build solid customer relations (Ferguson, 2000). SCM can be viewed as a philosophy based on the belief that each firm in the supply chain directly and indirectly affects the performance of all the other supply chain members, as well as ultimately, overall supply-chain performance (Cooper et al., 1997). The effective use of this philosophy requires that functional and supply-chain partner activities are aligned with company strategy and harmonized with organizational structure, processes, culture, incentives and people (Abell, 1999). Additionally, the chain-wide deployment of SCM practices consistent with the above-mentioned philosophy is needed to provide maximum benefit to its members. The Supply-Chain Operations Reference (SCOR) model was developed by the Supply-Chain Council (SCC) to assist firms in increasing the effectiveness of their supply chains, and to provide a process-based approach to SCM (Stewart, 1997). The SCOR model provides a common process oriented language for communicating among supply-chain partners in the following decision areas: PLAN, SOURCE, MAKE, and DELIVER. Recently, the details for the decision area of “RETURN” have been added to the SCOR Version 5.0 model. Since the SCOR model is the main framework used in the organization of this study, a short explanation is required. In each decision area there are three levels of process detail. A diagram depicting these levels is provided in Figure 1. Level 1 defines the scope and content of the core management processes for the above-mentioned decision areas. For example, the SCOR Plan process is defined as those processes that balance aggregate demand and supply for developing actions which best meet sourcing, production, and delivery requirements. Level 2 describes the characteristics associated with the following process types deployed within the core processes: planning, execution and enable. For example, supply chain partners require processes for planning the overall supply chain, as well as planning processes for supporting source, make, deliver, and return decisions. A diagram illustrating Level 2 for SCOR Model Version 4.0 is provided in Figure 2. Characteristics associated with effective planning processes include a balance between demand and supply and a consistent planning horizon. The SCOR model also contains Level 2 process categories defined by the relationship between a core management process and process type. Level 3 provides detailed process element information for each Level 2 process category. Inputs, outputs, description and the basic flow of process elements are captured at this level of the SCOR model. Supply chain performance 1193 Figure 1. Supply-Chain Operations Reference Model this level lies outside of its current scope.12 1194 Figure 2. does the degree of influence vary by the decision areas outlined in the SCOR model? The purpose of this exploratory study is to investigate the relationship between supply-chain management . measure and evaluate any supply-chain configuration.IJOPM 24. However. The rationale for its exclusion is that the SCOR model is designed as a tool to describe. firms must implement specific supply-chain management practices based upon their unique set of competitive priorities and business conditions to achieve the desired level of performance. Supply-Chain Operations Reference Model: Level 2 Although the SCOR model acknowledges the need for an implementation level (Level 4) for effective SCM. which practices have the most influence on supply-chain performance? Furthermore. Thus. of the various supply-chain management practices available. 0. Childerhouse and Towill. First. reviewing sourcing and outsourcing options (Ansari et al. Harland et al. supplier relationships. 2001)..0 (PLAN. Ellinger. 2001). 2001). This literature suggests that the effective use of supply chain IT can have a dramatic impact on each of the four decision areas provided in SCOR Model Version 4. long-term time horizons. Boddy et al. an alignment Supply chain performance 1195 . Hauguel and Jackson.. 1999. Narasimhan and Das. strategic supply chain design (Fine. 2001) and the use of ERP systems (Manetti.2001).. advanced planning systems (Cauthen. 2001) This area of research corresponds to P1 in Level 2 of the Supply-Chain Operations Reference Model. a set of research questions is proposed linking supply-chain management planning practices to supply chain performance. 2000. Cox. 1999. mutual information sharing. Korpela et al. 2001a. 2000. D’Amours et al.. Another SCM research area revealed in the literature review is the necessity for supply chain information technology (IT) to foster information sharing (Chandrashekar and Schary. DELIVER) and nine key supply-chain management planning practices derived from supply-chain management experts and practitioners.b. 1999. 2000).c.planning practices and supply chain performance based on the four decision areas provided in SCOR Model Version 4. coordinating the supply chain (Kim.. and Deeter-Schmelz et al. Humphreys et al. one area of SCM research focuses on planning the design and configuration of the supply chain to achieve competitive advantages (Vickery et al. developing strategic alliances (McCutcheon and Stuart. MAKE. The literature review also revealed the importance of partnership planning activities for collaborating among supply chain partners (Corbett et al. 2000. Watson. 2000. Make. shared visions and compatible corporate cultures. This literature also corresponds to each of the four decision areas provided in SCOR Model Version 4. the literature highlights the need for overall strategic supply chain planning to facilitate customer and supplier integration (Frohlich and Westbrook. setting supply chain goals (Wong. Brewton and Kingseed. Waller et al. 2001. SOURCE... and internet technologies (Cross. Finally.0 (Plan. 1999. The SCM research literature provides significant insight on the role of planning in facilitating the effective management of supply chains. and the sharing of risks and rewards. Deliver). Source. Whipple and Frankel. For example. the paper describes the methods and analysis conducted to explore these questions. 2000. 2001). 1999. 2001.. the results of the study along with future research opportunities are offered. 2001) and defining supply chain power relationships among trading partners (Cox. The paper is organized as follows. 2000. 2000). 1999.. Peck and Juttner...1999. 1999). 1999. 2000). Fourth. 2000. 2001. and Rutner et al..b. Second. establishing information-sharing parameters (Lamming et al. 2001a. Review of the supply-chain management planning literature Cooper and Ellram (1993) associate the following characteristics with effective SCM: Channel-wide inventory management. joint planning. 2000). integrating cross-functional processes (Lambert and Cooper. it provides a working definition of SCM and a description of the SCOR model used as a basis for the research. Heriot and Kulkarni. the paper reviews the supply chain planning literature highlighting the need for empirical research linking supply chain planning practices to supply chain performance. 2001). Reutterer and Kotzab. Finally. Stock et al. 2000. channel coordination. Maloni and Benton. 1999. supply chain competitiveness (Narasimhan and Kim. 2000. Kaufman et al. 2000). 2001.. Third.. Cox et al. Raghunathan.. and monitoring. supply chain cost efficiency. 2000). and relationship integration.0. 2001). process ownership. A direct correspondence to P1 in Level 2 of the Supply-Chain Operations Reference Model is observed in this area of the literature. process integration. the planning activities illustrated in Level 2 of the Supply-Chain Operations Reference Model can be used as a framework for directing future supply-chain management planning research. technology and planning integration. process documentation. Construct development The literature review. supplier integration. process measures. One significant study utilized the twenty-first century Logistics framework. nine key supply chain planning practices emerged: planning processes. For collaboration and teaming . although some were implied within the measurement system used. 2001). Their results showed that customer integration. internal integration. First.IJOPM 24.12 1196 between supply chain processes and strategic objectives (Hicks et al. 2000.. documented understanding and agreement of what is to be done within and between processes. 2000). and information technology (IT) support. this exploratory study is an empirical investigation of the relationship between supply-chain management planning practices and supply chain performance based on the four decision areas provided in SCOR Model Version 4. automated functions and event triggers (i. A review of this literature suggests the following conclusions. In this research. along with discussions and interviews with supply chain experts and practitioners was used as the basis for developing the constructs for the study: supply chain planning practices and supply chain performance. It is usually achieved through process design and mapping sessions or review and validation sessions with the process teams.. Third. specific planning practices related to performance were difficult to identify. internal integration and technology and planning performance are the dominant competencies related to performance. to investigate the relationship between logistics integration competence and performance (Stank et al. There have been only a small number of studies attempting to empirically link specific SCM practices to supply chain performance. teaming. Maintenance and change control of this documentation is also a critical component. the importance and necessity of supply-chain management planning is well established in the literature and warrants continued research.0 and nine key supply-chain management planning practices derived from supply-chain management experts and practitioners. Planning processes are required to determine the most efficient and effective way to use the organization’s resources to achieve a specific set of objectives. measurement integration. a list of six critical areas of competence in achieving supply chain logistics integration. Thus. Second. and Ramsay. collaboration. process credibility. The six integration competencies in the framework are: customer integration. 1999. Process integration refers to the tight coupling of two or more processes through shared systems. 2000. because of this correspondence.e. 2001b). and shareholder value via the achievement of competitive advantages (Christopher and Ryals. research published in this area corresponds to the four decision areas provided in SCOR Model Version 4. Through this effort. effective order fulfillment and inventory management (Johnson and Anderson. Tamas. auto replenishment). Finally. there is an absence of empirical research clearly linking specific supply chain planning practices to supply chain performance. Process documentation requires a clear. Viswanathan and Piplani. promise delivery. Discussions then proceeded on how these decision categories relate to the Supply-Chain Operations Reference (SCOR) Model. procurement along with production planning and scheduling decisions tend to span across both internal and supplier SCOR decision Supply chain performance 1197 Figure 3. Process credibility refers to the level of customer confidence in the output of the process and its use in making commitments. procurement. demand management. influence and authority in an SCM organization. cross-functional authority. while decisions on balancing change tend to span internal and external SCOR decision areas across the entire supply chain.to occur. balancing change. This mapping suggests that operations strategy planning and promise delivery decisions tend to be aligned with a firm’s internal SCOR decision areas. This resulted in Figure 3. Early research suggests that there are different types of collaboration based upon the intensity of the information exchanges. Additionally. and the nature of the relationship. The literature review. The formal creation of broad. Finally. and enables multi-dimensional. Supply chain decision categories mapped to the SCOR model . as well as to provide a link to the firm’s reward system. which maps the above-mentioned supply-chain management planning decision categories to the SCOR Model. and distribution management. Process measures are used to identify and assign responsibility for supply chain process outcomes relating to such areas as efficiency. IT support refers to the process owners’ and team members’ perceived usefulness of the IT system in support of SCM processes. cooperative (coordinative) and collaborative (McCormack. discussions and interviews also resulted in the emergence of seven key supply-chain management planning decision categories: operations strategy planning. 2003). A collaborative. production planning and scheduling. cost and quality. cross-functional jobs with real overall supply chain process authority and ownership is a key component of process ownership. team based SCM structure represents the span of involvement. These types are transactional. individuals from the various functions involved in effective SCM must work as a tightly integrated group with shared authority to make decisions and take actions. Survey instrument The literature review. What are the most important supply-chain management planning practices in the MAKE decision area of SCOR Model Version 4. SOURCE. while demand and distribution management decisions span across both internal and customer decision areas. The approach includes specifying the domain of the construct. a practice is defined as a method. What are the most important supply-chain management planning practices in the SOURCE decision area of SCOR Model Version 4. generating a sample of items which capture the domain as specified. along with discussions and interviews with supply chain experts and practitioners was also used as the basis for developing survey questions . and 31 (DELIVER)). or process. The construct is based on perceived performance. and contained a high number of individuals with either a Masters or PhD degree in operations research. A figure depicting the approach is provided in Figure 4. Questions 32 (PLAN). this decision process area performs very well. assessing the construct validity.” The participants were asked to either agree or disagree with the item statement using a five-point Likert scale (1 ¼ strongly disagree. 16 (MAKE). What are the most important supply-chain management planning practices in the PLAN decision area of SCOR Model Version 4. 5 ¼ strongly agree).0 that relate to perceived supply chain performance? RQ2. purifying the measures through coefficient alpha or factor analysis. DELIVER).12 1198 areas. as determined by the survey respondents. What are the most important supply-chain management planning practices in the DELIVER decision area of SCOR Model Version 4. MAKE. and developing norms. Research questions The following research questions were developed to operationalize the above-mentioned constructs: RQ1. The experts and practitioners used in developing and validating the constructs were selected from the Chesapeake Decision Sciences (now AspenTech) user group list. technique. For this study.0 that relate to perceived supply chain performance? RQ4. This list spanned across multiple industries. The planning activities illustrated in Level 2 of the Supply-Chain Operations Reference Model were used to specify the domain of supply-chain management planning practices for the study (PLAN.IJOPM 24. The supply chain performance construct is a self-assessed performance rating for each of the SCOR decision areas. 15 (SOURCE). procedure. The specific item statement on supply chain performance for each of the SCOR decision areas is: “Overall.0 that relate to perceived supply chain performance? Research methodology The research approach for this study follows the process of investigation and measurement developed by Churchill (1979). It is represented as a single item for each decision area (see Appendix 1. assessing reliability with new data.0 that relate to perceived supply chain performance? RQ3. procurement. who does it and how it is done” in their supply chain. promise delivery. production planning and scheduling. and 5 – always or definitely exists. A survey instrument was developed using a 5-item Likert scale measuring the frequency of the practices consisting of: 1 – never or does not exist. 2 – sometimes. The questions focus on decision making in the seven key supply-chain management planning decision categories (operations strategy planning. and distribution management) for each of the four SCOR decision . demand management. improvements in wording and format were made to the instrument. The survey asked respondents to provide their opinion concerning “what is done. The survey questions grouped by SCOR decision area are provided in Appendix A. 3 – frequently. balancing change. Based upon this review. Based upon these tests. Churchill research methodology representing the nine key supply chain planning practices identified in the “Construct development” section. The discussions were structured around SCOR Model Version 4. and several items were eliminated. The Supply Chain Council board of directors also reviewed the survey instrument. how often. The initial survey was tested within a major electronic equipment manufacturer and with several supply chain experts.Supply chain performance 1199 Figure 4. the survey was slightly reorganized to better match the SCOR model.0. 4 – mostly. IJOPM 24. Approximately 43 percent of the respondents work in functions other than the nine categorized in the survey instrument (sales.5 0. information systems. A sample profile is provided in Table I.2 5. while 20 percent considered themselves to be senior managers. The “user” or practitioner portion of the list was used as the final selection since this represented members whose firms supplied a product. planning and scheduling.8 18. Sample The study participants were selected from the membership list of the Supply Chain Council. manufacturing.0 8. Sample profile Respondent position Senior leadership/executive Senior manager Manager Individual contributor Total Number of responses 19 10 17 4 50 Response percentages 38.0 1. Respondent profile by position . this category represented the new Industry description Electronics Transportation Industrial products Food & Beverage/CPG Aerospace & Defense Chemicals Apparel Utilities Pharmaceuticals/Medical Mills Semiconductors Other Total Number of responses 6 2 2 8 2 4 1 10 3 0 1 16 55 Response percentages 10. Upon investigation.12 areas. A profile of the respondents by position and by function is provided in Tables II and III respectively. This list consisted of 523 individuals and 90 firms. finance. distribution. and purchasing). Table III reveals that approximately 18 percent of the respondents work in the purchasing function. while the remaining 8 percent were classified as individual contributors. marketing.0 34.5 3.0 20.6 7.0 100% Table II. The sample represents 11 distinct industry types. We were unable to build a consensus for questions relating process credibility to the SOURCE decision area of SCOR Model.9 3.6 3. rather than a service.8 29. Thirty-four percent of the respondents were classified as managers. Table II reveals that 38 percent of the respondents classified themselves as being either senior leaders or executives.3 1. while approximately 16 percent work in planning and scheduling. Approximately 29 percent of the respondents were classified as “Other” in relation to industry type. engineering.1 100% 1200 Table I.6 14. Therefore the survey instrument does not contain any items corresponding to this area. and were thought to be generally representative of supply chain practitioners rather than consultants. a traditional vacation time in most of the USA and Europe. 28 were returned due inaccurate addresses..1 100% Supply chain performance 1201 Table III. Analysis Factor analysis is used to examine the underlying patterns or relationships for a large number of variables and to determine whether or not the information can be condensed or summarized in a smaller set of factors or components (Hair et al.0 0. Upon investigation. p.Respondent function Sales Information systems Planning and scheduling Marketing Manufacturing Engineering Finance Distribution Purchasing Other Total Number of responses 1 3 8 0 4 0 0 4 9 22 51 Response percentages 2. information systems (approximately 6 percent).0 5. Of the 523 surveys distributed. The number of returned surveys (55) also met the minimum number needed for factor analysis (Hair et al. The remaining respondents work in manufacturing (approximately 8 percent). position or functional bias.7 43. This smaller set of factors was then used in regression analysis to test the hypothesized relationships.5 percent.9 15. Data collection The survey instrument was distributed by mail with a cover letter explaining its purpose and sponsorship by the Supply Chain Council. It was distributed during August.8 0. Recipients were also encouraged to distribute the survey to other practitioners within their firm. distribution (approximately 8 percent). positions and functions and is not heavily weighted toward a few segments.. The sample was also examined for any role. As can be seen from Tables I.0 7. An analysis of non-response bias was made to determine its impact on the data. 239). The purpose of factor analysis in this study was to find a way to condense the variables used to describe the constructs into a smaller set of new composite dimensions or factors with a minimum loss of information. Fifty-five usable surveys were returned for a response rate of 10. Respondent profile by function supply chain oriented jobs such as “Global Supply Chain Manager” or “Supply Chain Team Member”. 1992.0 7. When questioned by phone. The sample size was over 50.7 0. The sample was divided into quartiles based upon the time of submission and means were examined. From this examination it was concluded that no bias was present. 1992).8 17. this low response rate was due to the length of the survey and its timing. The recipients were asked to complete the survey within two weeks and either fax or mail the completed form to a designated address. and sales (approximately 2 percent). the sample appears to represent a cross-section of roles. II and III. which is the minimum . No significant differences were identified. many people stated that they were on vacation during the survey period or did not have time to complete the survey since they were preparing for vacation. p. Factor analysis – PLAN decision area 0.60 0.90 .69 0.61 Factor Demand planning process Scale items P18 – Documented forecasting process P19 – Use historical data in forecast P20 – Use mathematical methods P21 – Process occurs on scheduled basis P22 – Forecast for each product P24 – Owner for DM process P27 – Forecast is credible P28 – Used to make plans/commitments P29 – Forecast accuracy measured P6 – Defined customer priorities P7 – Defined product priorities P13 – Team examines customer profitability P14 – Team examines product profitability P15 – Participates in customer/supplier relationships P17 .77 0.IJOPM 24.62 0.51 0.76 0. Adjustments were made to the measurement model as suggested by this analysis until a final factor matrix emerged for each area.82 0. Coefficient alpha measures the internal consistency of a set of items and were partly used to assess the quality of the instrument.12 1202 criterion for the use of factor analysis. Make and Deliver. 239). Plan analysis Factor analysis on variables relating to the PLAN decision area (see Table IV) resulted in loadings for the following factors: demand management process. and the item significance level for this size of sample was set at a loading of 0. A minimum acceptable criterion of 0. The demand management process factor had nine items representing critical elements of a demand management process.76 0.84 0.Analyze product demand variability P25 – DM uses customer information P9 – Supply Chain performance measures P1 – Operations strategy planning team established P2 – Team has formal meetings P3 – Major functions represented on team P4 – Team process documented P5 – Owner for process SC collaborative planning 0.7 was used for this analysis (Churchill.82 0. and operations strategy planning team.91 0.95 0. supply chain collaborative planning. A low coefficient alpha indicates that the sample of items performs poorly in capturing the construct and a large alpha indicates that the test correlates well with true scores.70 0. This analysis was used to examine whether the number of dimensions conceptualized could be verified empirically. These are items such as process documentation.84 0. 1979).74 0. The initial analysis used a five-factor strategy for each of the SCOR areas of Plan.87 Operations strategy planning team Table IV.87 0.4 using published guidelines (Hair et al.80 0. An exploratory component factor analysis using maximum-likelihood extraction and oblique (varimax) rotation was performed on the data to examine the dimensions underlying the construct.56 0.70 0.94 Factor loadings 0.. Source.71 0. 1992. Coefficient alpha 0.86 0. 67 0. and 0.90 for operations strategy planning team.58 0.75 0.64 0. Coefficient alphas were generated on all factors yielding a value of 0. Supplier transactional collaboration had two items representing the sharing of planning and scheduling information with suppliers and the measurement and feedback of supplier Coefficient alpha 0.7.91 0.87 for supply chain collaborative planning.70 Supply chain performance 1203 Factor Source planning process Scale items S1 – Procurement process documented S2 – IT supports process S3 – Supplier inter-relationships understood/documented S4 – Process owner identified S12 – Procurement process team designated S13 – Team meets on regular basis S14 – Other functions work closely with team S8 – Share plan / schedule with suppliers S11 – Measure and feedback supplier performance S10 – Collaborate with suppliers to develop source plan S5 – Have strategic suppliers for all products/services Procurement planning process team 0.78 – – Table V. The supply chain collaborative planning factor had eight items representing the following specific collaborative planning process elements: supply chain planning team participation in customer and supplier relationships. and information support.72 0. and an owner for the supply chain planning process. Factor analysis – SOURCE decision area . procurement planning process team. conducting formal meetings. etc).86 Factor loadings 0. supplier operational collaboration.94 for demand management process. a documented process for the team. credibility and key practices (mathematical models. operational and strategic. Supplier collaboration had three factors that represent the various types of collaboration: transactional. 0.89 Supplier transactional collaboration Supplier operational collaboration Supplier strategic collaboration 0. conducting formal meetings. understanding and use of customer demand information. Source analysis An analysis of variables relating to the SOURCE decision area (see Table V) resulted in loadings for the following factors: source planning process.60 0. Procurement planning process team had three items representing teaming elements such as: the designation of a procurement planning team with cross functional members. use of historical data. understanding of supplier inter-relationships. a process owner. supplier transactional collaboration.82 0.58 0. and supplier strategic collaboration. Source planning process had four items representing elements of the planning process such as: process documentation. and an owner for the procurement planning process.ownership. These were all deemed acceptable using the criteria of 0. and the understanding and use of customer priorities balance with company priorities. The operations strategy planning team factor had five items representing teaming elements such as: the designation of a planning team with cross functional members.89 0. constraint based methods and information system support.77 for make scheduling process was 0. measurements.70 for make collaborative planning. These were all deemed acceptable using the criteria of 0.86 for source planning process.7.56 0. Deliver process credibility had three items representing customer satisfaction with delivery performance. make scheduling process and make collaborative planning. The values were all deemed acceptable using the criteria of 0. Make analysis Factor analysis on variables relating to the MAKE decision area (see Table VI) resulted in loadings for the following factors: make planning process. 0. cross-functional representation.51 0. Make planning process had six items representing process ownership. and 0. Deliver planning process had seven items representing process documentation.IJOPM 24.12 1204 performance.42 0.67 0.7.45 0. Deliver analysis An analysis of variables relating to the DELIVER decision area (see Table VII) resulted in loadings for the following factors: deliver planning process. deliver process measures and deliver process integration.89 for procurement planning process team.70 . Supplier operational collaboration had one item representing collaborative planning with suppliers. Coefficient alphas for the factors were 0.78 for supplier transactional collaboration. IT support and ownership.54 0. Factor analysis – MAKE decision area Make Collaborative Planning 0. Supplier strategic collaboration had one item representing the designation of strategic suppliers for all products and services. Supplier operational collaboration and supplier strategic collaboration were both single item measures making coefficient alphas non-applicable. process credibility and measurement.77 Table VI. Make scheduling process had three items representing process integration.65 0.IT supports process M6 – Supplier lead times updated monthly M13 – Integrate customer’s plan/schedule M14 – Formal change process Factor loadings 0. and change control. process ownership.84 M2 – Integrated/coordinated across divisions M3 – Process owner designated M4 – Weekly planning cycles M10 – Measure adherence to plan M11– Adequately address needs of business M12 – Sales/Mfg.51 0. cross-functional participation and specific order management practices./Distribution collaborate in process M7 – Using constraint-based planning methods M8 – Shop Floor scheduling integrated M9 . Coefficient alphas for the factors were 0. formal planning cycles.84 for make planning process.66 0. Make collaboration had three items representing the inclusion of supplier lead times. process credibility Coefficient alpha Scale items 0. the inclusion of customer planning and scheduling information.77 and 0.96 0.95 Factor Make planning process Make Scheduling Process 0.76 0. process integration. deliver process credibility. 0. 76 for IT support and ownership. Deliver process measures had three factors representing understanding and documentation of DELIVER network interrelationships (variability and metrics).69 0.90 0. distribution management process measures. and distribution management process ownership. 15 (SOURCE)./planning collaborate D4 – Customers satisfied with deliver performance D5 – Meet short term demands with inventory D9 – Delivery commit credible to customers D14 – IT support of order commit process D18 – IT support distribution management D20 – Distribution management owner D19 – Network inter-relationships understood D29 – Distribution management process measures D30 – Measures used to recognize/reward D27 – Inventory measures and controls D28 – Use auto replenishment in distribution Factor loadings 0.45 0.81 D1 – Order commit process documented D2 – Promise delivery process owner D3 – Track on time customer orders D7 – Measure customer requests v. 0. 0. Deliver process integration had two items representing distribution network inventory measures and controls.69 Supply chain performance 1205 Deliver process credibility 0. and reflects the survey respondent’s view of their performance in a particular SCOR decision area (see Appendix A. distribution management processes. The independent variables are a summation of the scale items within each factor extracted via factor analysis (see Tables IV-VII).53 0.90 0.75 0. and using these measures to recognize and reward participants. IT support and ownership had three items representing IT support for the order commitment.79 0. It is represented as a single item for each decision area.71 0.81 for deliver planning process. 0.71 Table VII.68 0.7. and 31 (DELIVER)).73 0. and the use of automatic replenishment in the network. Factor analysis – DELIVER decision area concerning delivery commitments. Results Descriptive statistics for the supply chain performance variable and SCOR variables derived from factor analysis is provided in Appendix 2. 16 (MAKE). The results of the . and specific finished goods safety stock practices.71 for deliver process integration. 7. These were all deemed acceptable using the criteria of 0. and 0.76 0.65 0.77 for deliver process measures.67 0.85 IT support and ownership Deliver process measures 0. Questions 32 (PLAN). Single variable linear regression analysis was used to test the hypothesized relationships between the identified factors in each SCOR area and the self-assessed performance rating of each area. actual D10 – Promise orders beyond inventory levels D11 – Capability to respond to unplanned orders D13 – Sales/mfg.66 0. Coefficient alphas for the factors were 0.85 for deliver process credibility.Factor Deliver planning process Coefficient alpha Scale items 0. The dependent variable in each case is a self-assessed performance rating for each of the SCOR decision areas./distr.53 0.70 0.77 Deliver process integration 0.54 0.76 0. 02 0. Based on the beta values. 7.33 0.00 0.65 0.IJOPM 24.55 0.46 0.29 0. Single variable regression analysis Notes: dependent variable ¼ supply chain performance.57 0.17 0. the deliver process measures variable has the strongest relationship to supply Adjusted R2 0.12 regression analysis are illustrated in Table VIII.54 0. demand-planning process is the most important PLAN variable relative to supply chain performance. supplier operational collaboration. followed by supply chain collaborative planning and operations strategy planning team. procurement planning process team.72 0.00 0.00 0.71 0.43 0.00 0.00 0.22 1206 Beta values PLAN factors Demand planning process SC collaborative planning Operations strategy planning team SOURCE factors Source planning process Procurement planning process team Supplier transactional collaboration Supplier operational collaboration Supplier strategic collaboration MAKE factors Make planning process Make scheduling process Make collaborative planning DELIVER factors Deliver planning process Deliver process credibility IT support and ownership Deliver process measures Deliver process integration 0.03 0.69 0.00 0. and supplier strategic collaboration in the SOURCE decision area.47 0.00 0.00 Table VIII.55 0. the supplier transactional collaboration variable has the strongest relationship to supply chain performance. Table VIII reveals that the make planning process variable has the strongest relationship to supply chain performance.00 0.43 0.49 Significance level 0. supplier operational collaboration and supplier strategic collaboration.00 0.30 0. followed by supply chain collaborative planning and operations strategy planning team.48 0.31 0. make planning process is the most important MAKE variable relative to supply chain performance. followed by make planning process and make scheduling process. followed by source planning process. followed by make scheduling process and make collaborative planning. these models are equivalent to bivariate correlations. followed by source planning process.20 0. Since each regression model contains only one independent variable.41 0. Finally.74 0.50 0. Based on the beta values.00 0.66 0. In the MAKE decision area. Table VIII shows that the demand planning process variable has the strongest relationship to supply chain performance.29 0.23 0. procurement planning process team.50 0.1 Regression results In the PLAN decision area.49 0. Additionally.00 0.00 0. An examination of the beta values show that supplier transactional collaboration is the most important SOURCE variable relative to supply chain performance. independent variable ¼ SCOR decision area factor .07 0.20 0.09 0.00 0. Conclusions Based upon the aforementioned results. In addition.e. The team should be comprised of representatives from the major supply chain functions (i. followed by IT support and ownership. The creation of an operations strategy team was found to have an impact on supply chain performance. SOURCE conclusions Supplier transactional collaboration activities have a significant impact on supply chain performance within the SOURCE decision area. and have a documented operations strategy process. hold regular meetings. and the management of supplier inter-relationships. deliver process integration.). This also includes the measurement of forecast accuracy along with the establishment of a process owner for the demand process. analyzing customer and demand variability information. marketing.chain performance. an owner for the supply chain planning process is required to ensure its effectiveness. also has a significant impact on supply chain performance in this PRACTICE Planning processes Collaboration Teaming Process measures Process credibility Process integration IT support Process documentation Process ownership PLAN X X X Indirect – – – Indirect Indirect SOURCE X X X Indirect – – – Indirect Indirect MAKE X X – Indirect – – – Indirect Indirect DELIVER X Indirect – X X X X Indirect Indirect Supply chain performance 1207 Table IX. sales. Collaborative planning process activities were also found to have a significant impact on supply chain performance within this decision area. Additionally. An examination of the beta values show that deliver process measures is the most important DELIVER variable relative to supply chain performance. generalized conclusions with respect to the impact of the nine identified key supply chain practices are offered and summarized in Table IX. These activities include: defining product and customer priorities. etc. has a significant impact on supply chain performance. demand planning. These activities include the sharing of planning and scheduling information with suppliers. logistics. and deliver planning process in the DELIVER decision area. establishing customer and supplier relationships. reviewing product and customer profitability information. which includes forecast development activities. and establishing supply chain performance metrics. followed by IT support and ownership. which includes the documentation of procurement processes. deliver process credibility. manufacturing. PLAN conclusions For the PLAN decision area. General conclusions for the nine key supply chain practices . the establishment of information technology that supports theses processes. conclusions regarding the impact of SCOR planning practices on supply chain performance for each SCOR planning decision area are provided below. deliver process integration. The source planning process. deliver process credibility and deliver planning process. This involves: the integration of customer planning and scheduling information into the manufacturing planning process. These metrics should document supply chain inter-relationships in a manner that is understandable by the supply chain trading partners. weekly planning cycles are required to facilitate necessary changes to the plan based on relevant data and information.. These activities include: collaboration tasks among the sales.. and the periodic updating of supplier lead times based on collaborative information.IJOPM 24. These activities include electronic ordering and supplier-managed inventory. To ensure its effectiveness. and be used to reward and recognize the process participants. and distribution organizations. The establishment of a procurement process planning team was found to have an impact on supply chain performance within the SOURCE decision area. delivery process measures have a significant impact on supply chain performance. the development of a formal. MAKE conclusions MAKE planning process activities have a significant impact on supply chain performance within the Make decision area.e. Finally. manufacturing. document. In addition.g. manufacturing. and distribution organizations during the planning and scheduling process. Supplier inter-relationships included in the source planning process include the management of product and delivery variability. Supplier operational collaboration also has a significant impact on supply chain performance in this decision area. the presence of on-site employees of key suppliers facilitates strategic supplier collaboration activities that enhance overall supply chain performance. a joint assessment of the needs of the business among the sales. the designation of a source planning process owner is required to ensure its effectiveness. the process must be integrated and coordinated across functional and organizational boundaries. and the use of information technology to support the make scheduling process (i. Additionally. and work closely with other functional areas such as manufacturing and sales. Make collaborative planning also has a significant impact on supply chain performance in this decision area. The system’s specific support of the order commitment process was found to be critical to effective .12 1208 decision area. Supplier strategic collaboration activities also impact supply chain performance in the Source decision area. along with metrics for monitoring such variability. and the establishment of performance metrics which facilitate the monitoring of “adherence to schedule” requirements. DELIVER conclusions For the DELIVER decision area. This team should meet on a regular basis. The degree to which the information system supports the distribution management process was also found to impact supply chain performance within this decision area. In addition. The make scheduling process also has a significant impact on supply chain performance within the MAKE decision area. and collaborative approval process for schedule changes. MRP and ERP systems). the use of constraint-based planning methodologies (e. Key elements of this process includes: the integration of shop floor scheduling with the overall scheduling process. the use of advanced planning and scheduling software based on the Theory of Constraints). This involves the development of a joint operational plan that is supportive of strategic sourcing activities and outlines how routine transactional activities are to be conducted by the participants. the establishment of a make planning process owner is required to ensure the effectiveness of the process. and measuring variations between customer requests versus actual delivery. However. process metrics was found to only have an indirect impact on supply chain performance in the PLAN. and MAKE areas. SOURCE. tracking the percentage of completed customer orders delivered on time. Process documentation was found to have only an indirect impact on supply chain performance in the four SCOR Model areas included in the study. Delivery planning process activities were also found to have a significant impact on supply chain performance within this decision area. A review of the table reveals that the planning process variables in all four SCOR Model areas have the strongest relationship to supply chain performance. The collaboration results of the study are consistent with the findings of a study conducted by Stank et al. process ownership was found to have an indirect impact on supply chain performance in all four SCOR Model areas. A process credibility. SOURCE. Key integration features include the establishment of inventory control mechanisms and metrics for each node in the distribution network. (2001a).distribution management. although preliminary and exploratory in nature. Delivery process integration along with delivery process credibility were found to have a significant impact on supply chain performance within the DELIVER decision area. manufacturing. These activities include: establishing order commitments based on a collaboration process among the sales. A designated distribution management process owner is required to ensure the effective use of information technology in support of the process. which found that collaboration improves supply chain service performance. Implications This study. Generalized conclusions for the nine key supply chain practices Table IX provides a summary of general conclusions regarding relationships between the nine identified key supply chain planning practices based on a review of the literature and discussions with supply chain experts and practitioners. the deliver planning process should monitor delivery over-commitments and delivery flexibility. and MAKE areas of the SCOR Model. SOURCE. Finally. and information technology support variable was found to have a direct impact on supply chain performance in the DELIVER area. and the SCOR Model areas included in the study (PLAN. Indicators of delivery process credibility include the degree to which customers are satisfied with current on-time delivery performance. MAKE. collaboration was found to have an indirect impact on supply chain performance in the DELIVER decision area. Collaboration variables were found to have a direct impact on SC performance in the PLAN. provides a beginning framework for the comparison and discussion of supply chain planning practices that Supply chain performance 1209 . and distribution organizations. process integration. along with the use of automatic replenishment throughout the network. A designated planning process owner is required to ensure its effectiveness. DELIVER). The table also reveals that teaming variables were found to have a direct impact on supply chain performance in the PLAN and SOURCE areas. a process metrics variable was found to have a direct impact on supply chain performance in the DELIVER area of the SCOR Model. and the customer’s confidence level in projected delivery commitments. Additionally. In addition. In addition. the ability to meet short-term customer demands. (2001b) that reveals a relationship between supply chain integration and performance. The process integration results of the study are consistent with a study conducted by Stank et al. References Abell. Thus. The final implication of this study is that information technology solutions are only part of the answer to improved supply chain performance. Further research on this topic might indicate that some practices are industry or “configuration” specific and do not provide the same results for every supply chain. process measurement. and that IT should serve as an enabler to organization and process change. Finally. and the implementation of the practice. currently lack broad implementation by supply chain partners. and to offer a research framework using the SCOR model to facilitate future studies.12 1210 relate to supply chain performance. “Competing today while preparing for tomorrow”. (1999). Sloan Management Review. This study also suggests is that some of the best practices proposed as mechanisms for improving overall supply chain management performance may not have the degree of impact often presented in the literature.F. D. 40 No. Limitations This study provides an exploratory view of the relationship between supply chain management planning practices and supply chain performance using a limited data set. due the limitations of IT’s impact on supply chain performance revealed in the study. the role of supply chain structure on the degree to which these practices influence performance also warrants future research. 3. collaboration. 73-81. Another research opportunity resulting from this exploratory study is to examine why there appears to be a gap between the recognition of a SCM planning practice as important to supply chain performance. The supply chain planning practices related to process integration. This suggests that integrated supply chain management may be more difficult to operationalize in practice than the popular supply chain press or consultants would have one to believe. firms who have purchased an information technology solution and expect it to drive improvements in supply chain management may be disappointed with the final results. this study has resulted in the development of a valid assessment instrument that is capable of gathering relevant information regarding the supply chain planning decision areas. The purpose of this study is to provide some preliminary insights regarding supply chain management practices and their impact on performance. . pp.IJOPM 24. Thus. The study shows that some best practices help to improve supply chain performance only in specific decision areas. 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S.. 32-46. and purchasing’s contribution to sustainable competitive advantage”. H. and Piplani.. .IJOPM 24.12 Appendix 1. Survey questions with individual correlations 1214 Figure A1. Figure A3.Supply chain performance 1215 Figure A2. . .IJOPM 24.12 1216 Figure A4. 51 3.68 2.17 1.15 1.98 2.00 3.17 1.94 3.72 2.24 1.35 1217 Table AI.37 1.16 1.15 3. SOURCE .34 1.36 1.70 3.22 1.85 3.18 1.33 3.49 PLAN factors P18 P19 P20 P21 P22 P24 P27 P28 P29 P6 P7 P13 P14 P15 P17 P25 P9 P1 P2 P3 P4 P5 Mean 2.21 1.81 3.17 3.08 0.54 Std dev.41 1.39 1.40 1. 1.13 3.35 3.55 1.52 3.00 2.19 1. PLAN SOURCE factors S1 S2 S3 S4 S12 S13 S14 S8 S11 S10 S5 Mean 3.43 1.21 1.33 1.60 3.47 1.15 2.46 3. Descriptive statistics for factor scale items Supply chain performance Std dev.24 1.07 1.39 3.40 2.09 2.07 2.19 1.Appendix 2.52 3.87 2.48 1.65 3.22 1.25 1.57 3.28 2.07 3.38 1. 1.99 Table AII.20 1.38 1.21 2.96 3.44 1. 24 2.18 2. 1.80 2.35 3. . DELIVER MAKE factors M2 M3 M4 M10 M11 M12 M7 M8 M9 M6 M13 M14 Mean 2. 1.28 1.50 1.00 3.36 1218 Table AIII.10 0.43 2.01 1.14 1.40 1.51 2.24 Table AIV.22 1.02 Table AV.28 1.46 3.34 1.86 2.37 1.20 1.68 Std dev.27 1.12 1.16 1.11 1.22 0.87 3.08 1.32 2.IJOPM 24.67 3.22 2.17 1.38 1.96 2.47 3.22 3. 1.40 1.85 2.83 Std dev.12 DELIVER factors D1 D2 D3 D7 D10 D11 D13 D4 D5 D9 D14 D18 D20 D19 D29 D30 D27 D28 Mean 3.24 2.12 2.55 2.11 1.88 1.20 2.20 3.11 1.26 1.70 3.81 2.61 3.18 1.41 3.42 Std dev.62 3.87 3.77 2.12 1.07 2.01 1.80 2.27 1.89 1.13 1.02 1. MAKE Supply chain performance factors P32 S15 M16 D31 Mean 2.