Sixteenth Annual Conference of POMS, Chicago, IL, April 29 May 2, 2005 Abstract Number 003-0307 A BUSINESS LOGISTICS APPROACH TO DESIGN PERFORMANCE EVALUATION SYSTEMS Álvaro Gehlen de Leão gehleao@orion.ufrgs.br Pontifícia Universidade Católica do Rio Grande do Sul Departamento de Engenharia de Produção Av. Ipiranga, 6681 Prédio 30 Faculdade de Engenharia 90619-900 Porto Alegre RS Brazil Phone: +55 51 3320.3648 Fax: +55 51 3320.3625 Since the early 1990s, various authors have been enlarged their considerations about logistics and supply chain management. What can be observed in the existing literature although its widespread theory about performance measurement and cost management is a lack of a structured method to proceed a practical implementation of performance evaluation systems using a business logistics approach. This paper intends to present results of a doctoral research developed to design a logistics performance evaluation system, which was built using processes-
based management concepts to synchronize logistics measures with corporate strategy, focusing on key performance measures. As a research project outcome, different tools like network modelling, balanced scorecard and activity-based costing were integrated in a system designed for decision-making on logistical management. 1 INTRODUCTION Nowadays, enterprises are facing an environment of high competitive level. Globalization of business relations increase the importance and complexity of logistical challenges faced by companies. Thus, management of logistic networks become a vital factor of competitiveness and, consequently, different approaches to improve enterprise performance are required, including quantitative evaluation of its logistical processes. According to Christopher (1998), Dornier et al. (1998), Keebler et al. (1999), Schönsleben (2000), Simchi-Levi et al. (2000) and Shapiro (2001), supply chain management and performance measurement have becoming mandatory disciplines to maintain high service level and low costs on logistics, because logistical activities are related to products, orders and information that flow through factories, wholesalers, retailers and carriers around the world. Various enterprises are measuring cost of independent activities, but are not paying sufficient attention to measure performance on the whole integrated logistical process. Some reasons are given (Keebler et al., 1999): there are too many measures being collected and these measures are set independently by functional managers and not connected to logistical processes; measures to
evaluate performance are often not completely synchronized to corporate strategy; and implementation of a successful processes-based measurement program is a complex work. 2 RESEARCH IN BUSINESS PERFORMANCE EVALUATION During the last years, academicians have significantly enlarged their investigation on business performance evaluation (Rolstadas, 1995; Lebas, 1995; Shapiro, 1999; Lapide, 2001; Epstein and Manzoni, 2002; Slagmulder, 2002). Andersson et al. (1989) underlined that there was a lack of connection between physical and economical measurements. According to Kaplan and Norton (1992), performance need to be measured by an integration of four perspectives financial, customer, internal processes, and learning and growth to provide a better linkage between operational processes and strategic planning. McCormack et al. (2003) emphasize that, although historical logistics measurement have maintained a functional perspective, a processes-oriented approach is more appropriate in today s competitive environment. Bowersox and Closs (1996) outline internal cost, customer service, productivity measures, asset measurement, quality, and external customer perception measurement, best practice benchmarking performance measurements. Orientation about comprehensive supply chain
management is given and characteristics of an ideal measurement system are discussed. Finally, levels of measurement and performance report structures are suggested. Shapiro (2001), Chopra and Meindl (2001) use a quantitative perspective and present an approach based on operations research. An overview of supply chain models and modelling systems is given, describing fundamentals of optimisation models. Applications on strategic, tactical and operational supply chain planning are also presented through numerous examples of performance evaluation. Also Monahan (2000) and Ragsdale (2001) provide a spreadsheet approach for modelling and analysis of managerial problems, using deterministic and probabilistic models which are suitable to solve logistical problems (Bertrand and Fransoo, 2002). What can be observed in the existing literature is a lack of an integrated model to carry on a practical implementation of performance evaluation systems using a business logistics approach. 3 DESIGNING LOGISTICS PERFORMANCE EVALUATION SYSTEMS In our research project we developed a business logistics performance evaluation system see figure 1, which was designed using processes-based management concepts taking into account the following recommendations (Keebler et al., 1999): synchronize logistics measures with corporate strategy; identify and understand customer needs and evaluate costs of logistics services; adopt a processes-based management, focusing on key performance measures.
Business Logistics Performance Evaluation System Balanced Scorecard and Strategy Maps Mapping of Logistical Processes Business Logistics Performance Indicators System Plan Source Make Cost Quality Delivery Deliver Return Responsiveness Flexibility Business Logistics Performance Evaluation Business Logistics Improvement Figure 1 Business Logistics Performance Evaluation System In this section, it will be detailed the integrated model to design logistics performance evaluation systems. This model, inspired on the SCOR Model, developed by the Supply-Chain Council (SCC, 2002; Meyr et al., 2002; Bolstorff and Rosenbaum, 2003), was built based on past
experiences achieved in research projects developed in several companies that manufacture intercity and urban buses, computer equipments for bank automation and industrial control, and shoes and leather products. 3.1 Strategic Analysis using Balanced Scorecard and Strategy Maps The balanced scorecard strategy map (Kaplan and Norton, 2000) is a useful tool to clarify strategies, identify the key internal processes that drive strategic success and align investments to improve logistics performance. According to Kaplan and Norton (2004), a strategy map see figure 2 provides a framework to link intangible assets to value creating processes on financial, customer, internal process and learning and growth perspectives. Financial perspective describes the tangible outcomes in traditional financial terms and customer perspective defines the value proposition, which provides the context to create value for customers. To achieve desired outcomes, both in financial and customer perspectives, it is necessary to create value through internal processes, which are performed by human resources, information and organisational structures. Therefore, learning and growth perspective helps to identify the intangible assets that must be aligned to the critical internal processes.
Financial Perspective Productivity Strategy Growth Strategy Customer Perspective Price Conformity Availability Selection Internal Processes Perspective Integrated Planning Procurement Purchasing Incoming Inspection Storage and Handling Suppliers' Development Production Dispatching Distribution Disposal Learning and Growth Perspective Human Resources Information Organisational Structure Figure 2 A Strategy Map to Design Logistics Performance Evaluation Systems
3.2 SCOR Model Approach and Mapping of Logistical Processes The SCOR Model approach is based on five management processes plan, source, make, deliver and return (SCC, 2002). Plan processes are responsible to accomplish market demand, developing a course of action which meets sourcing, production and delivery requirements. Source processes are in charge to procure materials to be transformed into finished products by make processes. Deliver processes includes order management and distribution management to satisfy customer demand and return processes are associated with returning or post-delivery customer support. The logistical processes that were depicted in the strategy map are then classified according to SCOR Model. In using a workflow tool for mapping of processes (Sharp and McDermott, 2001; Aalst and van Hee, 2002) see figure 3 logistical processes can be connected by physical and information flows (Hines et al., 2000; Handfield and Nichols, 2002).
Market Demand Plan Integrated Planning Source Materials Procurement Purchasing Make Storage and Handling Incoming Inspection Suppliers' Development Production Dispatching Distribution Disposal Return Deliver Products Available to Customers Discarded Materials and Products Figure 3 SCOR Model and Mapping of Logistical Processes
3.3 Competitive Priorities and Logistics Performance Metrics According to Krajewski and Ritzman (2002), competitive priorities are the operating advantages that internal processes of a firm need to outperform its competitors. To achieve the desired outcomes, it is necessary to select competitive priorities which are linked to productivity and growth strategies in a financial perspective, and that have impact on price, conformity, availability and selection in a customer perspective, as shown on figure 4. Financial Perspective Customer Perspective Price Conformity Availability Selection Cost Quality Delivery Responsiveness Flexibility Internal Processes Perspective Learning and Growth Perspective Figure 4 Internal Processes Perspective Impact on Customer Perspective
Five competitive priorities were selected cost, quality, delivery, responsiveness and flexibility. These competitive priorities are connected to the internal processes and define logistics performance metrics, as shown on table 1. Table 1 Competitive Priorities and Logistics Performance Metrics Competitive Priorities Logistics Performance Metrics Targets Plan Flexibility Percentage of Developed Products over Total Demand 75% (min.) Delivery Time to Create a Production Order 3 days (max.) Source Quality Percentage of Materials Subject to Incoming Inspection 15% (max.) Percentage of Materials Rejected in Incoming Inspection Percentage of Approved Suppliers 2% (max.) 60% (min.) Delivery Time to Complete a Purchasing Order 5 days (max.) Responsiveness Percentage of Accomplished Purchasing Orders 90% (min.) Make Cost Production Cost of Packages $ 0,15 per kg Quality Percentage of Rejected Packages 0,7% (max.) Deliver Cost Distribution Cost: Packages to Supermarkets $ 45 per ton Distribution Cost: Bottles to Stores $ 4,80 per lot Delivery Distribution Time: Packages to Supermarkets 24 h (max.) Quality Physical Losses to Distribute Bottles to Stores 0,5% (max.) Return Delivery Time to Discard Materials and Products 5 days (max.)
These logistics performance metrics can be evaluated by means of performance indicators. Table 2 presents, as an example, some logistics performance indicators for the distribution process which is mapped on figure 5. Packages Factory Bottles Factory D1 D2 Transportation DA DB Transportation DC Warehousing (Delivery)! NO YES DD Direct Sales Shipping DE SUPERMARKETS! (Destination) Final Consumers STORES Delivery DF D3 DG Delivery Supermarkets D4 Stores Figure 5 Mapping of Distribution Process
Table 2 Logistics Performance Indicators for the Distribution Process Process Logistics Performance Indicators Distribution Distribution Cost: Packages to Supermarkets Cost (DA + DC + DE + DF) Distribution Cost: Bottles to Stores Distribution Time: Packages to Supermarkets Cost (DB + DC + DE + DG) Instant D3 Instant D1 Physical Losses to Distribute Bottles to Stores Quantities ((D2 D4) / D2) The map of distribution process see figure 5 presents initial events, like available packages and bottles in the factory, activities performed transportation DA and DB, warehousing DC, direct sales DD, shipping DE, delivery DF and DG, monitoring points D1, D2, D3 and D4, and final events, related to products distributed to supermarkets, stores and final consumers. 4 FINAL REMARKS In this article we have presented results achieved in a doctoral research which was concluded by the end of March 2004. In our research project we have proposed an integrated model to design performance evaluation systems, which was built using processes-based management concepts to synchronize logistics measures with corporate strategy, focusing on key performance measures. The integrated model uses strategy maps from Balanced Scorecard, defining financial targets, customer needs and logistical processes. In a second step, the model suggests a workflow tool to map logistical processes, using the SCOR Model approach.
Finally, to evaluate logistics performance, this integrated model recommends logistics performance metrics derived from the competitive priorities selected to accomplish strategic objectives. REFERENCES AALST, W. van der; van HEE, K. Workflow Management: Models, Methods, and Systems. Cambridge: The MIT Press, 2002. ANDERSSON, P.; ARONSSON, H.; STORHAGEN, N. G. Measuring Logistics Performance. In: Engineering Costs and Production Economics, n. 17, p. 253-262. Amsterdam: Elsevier, 1989. BERTRAND, J. W. M.; FRANSOO, J. C. Operations Management Research Methodologies using Quantitative Modeling. In: International Journal of Operations and Production Management, v. 22, n. 2, p. 241-264. London: Emerald, 2002. BOLSTORFF, P; ROSENBAUM, R. Supply Chain Excellence: A Handbook for Dramatic Improvement Using SCOR Model. New York: Amacom, 2003. BOWERSOX, D. J.; CLOSS, D. J. Logistical Management: The Integrated Supply Chain Process. New York: McGraw-Hill, 1996. CHOPRA, S.; MEINDL, P. Supply Chain Management: Strategy, Planning, and Operation. New Jersey: Prentice-Hall, 2001. CHRISTOPHER, M. Logistics and Supply Chain Management: Strategies for Reducing Cost and Improving Service. London: Prentice-Hall, 1998.
DORNIER, P.; ERNST, R.; FENDER, M.; KOUVELIS, P. Global Operations and Logistics: Text and Cases. New York: John Wiley, 1998. EPSTEIN, M. J.; MANZONI. J. F. (Eds.) Performance Measurement and Management Control: A Compendium of Research. Oxford: Elsevier, 2002. HANDFIELD, R. B.; NICHOLS, E. L. Supply Chain Redesign: Transforming Supply Chains into Integrated Value Systems. New Jersey: Prentice Hall, 2002. HINES, P.; LAMMING, R.; JONES, D.; COUSINS, P.; RICH, N. Value Stream Management. Edinburgh: Pearson Education, 2000. KAPLAN, R. S.; NORTON, D. P. The Balanced Scorecard Measures that Drive Performance. In: Harvard Business Review, Jan. Feb. 1992 p. 71-79. Boston: HBR, 1992. KAPLAN, R. S.; NORTON, D. P. Having Problem with your Strategy? Then Map It. In: Harvard Business Review, Sep. Oct. 2000 p. 3-11. Boston: HBR, 2000. KAPLAN, R. S.; NORTON, D. P. Strategy Maps: Converting Intangible Assets into Tangible Outcomes. Boston: Harvard Business School Press, 2004. KEEBLER, J. S.; MANRODT, K. B.; DURTSCHE, D. A.; LEDYARD, D. M. Keeping Score: Measuring the Business Value of Logistics in the Supply Chain. Oak Brook: Council of Logistics Management, 1999. KRAJEWSKI, L. J.; RITZMAN, L. P. Operations Management: Strategy and Analysis. Upper Saddle River: Prentice Hall, 2002. LAPIDE, L. What about Measuring Supply Chain Performance. In: The Supply Chain Yearbook, 2001 Edition, p. 373-393. New York: McGraw Hill, 2001. LEBAS, M. J. Performance Measurement and Performance Management. In: International Journal of Production Economics, n. 41, p. 23-35. Amsterdam: Elsevier, 1995.
McCORMACK, K. P.; JOHNSON, W. C.; WALKER, W. T. Supply Chain Networks and Business Process Orientation: Advanced Strategies and Best Practices. Boca Raton: St. Lucie Press, 2003. MEYR, H.; ROHDE, J.; STADTLER, H. Basics for Modelling. In: Stadtler, H.; Kilger, C. (eds.) Supply Chain Management and Advanced Planning: Concepts, Models, Software and Case Studies, p. 45-70. Berlin: Springer-Verlag, 2002. MONAHAN, G. E. Management Decision Making: Spreadsheet Modeling, Analysis, and Application. Cambridge: University Press, 2000. RAGSDALE, C. T. Spreadsheet Modeling and Decision Analysis. Mason: South-Western, 2001. ROLSTADAS, A. Performance Management: A Business Process Benchmarking Approach. London: Chapman and Hall, 1995. SCC (Supply Chain Council) Supply Chain Operations Reference Model: Overview of SCOR Version 5.0. Pittsburgh: Supply Chain Council, 2002. SCHÖNSLEBEN, P. Integral Logistics Management: Planning and Control of Comprehensive Business Processes. Boca Raton: St. Lucie Press, 2000. SHAPIRO, J. F. On the Connections among Activity-Based Costing, Mathematical Programming Models for Analyzing Strategic Decisions, and the Resource-based View of the Firm. In: European Journal of Operational Research, n. 118, p. 295-314. Amsterdam: Elsevier, 1999. SHAPIRO, J. F. Modeling the Supply Chain. Pacific Grove: Duxbury, 2001. SHARP, A.; McDERMOTT, P. Workflow Modeling: Tools for Process Improvement and Application Development. Norwood: Artech House, 2001. SIMCHI-LEVI, D.; KAMINSKY, P.; SIMCHI-LEVI, E. Designing and Managing the Supply Chain: Concepts, Strategies and Case Studies. New York: McGraw Hill, 2000.
SLAGMULDER, R. Managing Costs across the Supply Chain. In: Seuring, S.; Goldbach, M. (eds.) Cost Management in Supply Chains, p. 75-88. Heidelberg: Physica-Verlag, 2002.