Supply Chain Business Intelligence Technologies, Issues and Trends

Topics: Business intelligence, Supply chain management, Supply chain Pages: 32 (9640 words) Published: March 2, 2013
Supply Chain Business Intelligence: Technologies, Issues and Trends Nenad Stefanovic1 and Dusan Stefanovic2
Zastava Automobiles, Information Systems Department, Kragujevac, Serbia nenad@automobili.zastava.net, www.zastava-automobili.com 2 Faculty of Science, University of Kragujevac, Serbia dusans@kg.ac.yu, www.pmf.kg.ac.yu 1

Abstract. Supply chains are complex systems with silos of information that are very difficult to integrate and analyze. The best way to effectively analyze these disparate systems is the use of Business Intelligence (BI). The ability to make and then to process the right decision at the right time in collaboration with the right partners is the definition of the successful use of BI. This chapter discusses the need for Supply Chain Business Intelligence, introduces driving forces for its adoption and describes the supply chain BI architecture. The global supply chain performance measurement system based on the process reference model is described. The main cutting-edge technologies such as service-oriented architecture (SOA), business activity monitoring (BAM), web portals, data mining, and their role in BI systems are also discussed. Finally, key BI trends and technologies that will influence future systems are described.

1

Introduction – Supply Chain

Competing in today’s business environment precipitates the need for successful integration and collaboration strategies among supply chain partners. The global environment is influenced by increased globalization and outsourcing, mergers, new technologies, and e-business. Shorter time-to-market, reduced product lifecycle, built-to-order strategies, pull systems and uncertainty force organizations to adopt new ways of doing business. There was a lot of pressure on companies to increase profit, decrease cycle times, reduce inventories, improve service and adapt to forthcoming changes. Supply chain management (SCM) as a new management philosophy followed. Supply Chain Management was seen as a tool for gaining competitive advantage through real-time collaboration with trading partners, and offered a new way to rapidly plan, organize, manage, measure and deliver new products or services. Many companies are beginning their search for a solution to implementing an electronically oriented supply chain management system that provides connection to customers and to suppliers. This integrated supply chain may be based on new M. Bramer (Ed.): Artificial Intelligence, LNAI 5640, pp. 217 – 245, 2009. © IFIP International Federation for Information Processing 2009

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software solutions or based on enhanced communication capabilities. The ultimate objective is to create a “seamless system interface” that provides the capability to review and analyze varying elements of information. The objectives for analysis of this information are to create a more efficient supply chain characterized by [1]: Increased customer service levels; Decreased transaction costs; More efficient inventory investments; Reduced expenses for manufacturing; Increased responsiveness to customer demands; The ability to fulfill customer requirements more profitably; The ability to deliver high quality products in the shortest time; The ability to deliver products at the lowest cost; The ability to penetrate smaller, fragmented markets cost effectively; Greater linkages with key suppliers; Demand driven logistics; Capacity planning across the supply chain; Sharing of information with key suppliers thus reducing supplier costs. In today’s fast-changing global market organizations need to compete as supply chains, not as single business entities [2]. Additionally, an organization can participate in many supply chains, thus creating a complex supply network of interconnected processes (see Figure 1).

Fig. 1. The Supply Chain

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Pushed by globalization and competitive...

References: 1. Martin, J., Roth, R.: Supply Chain management – Direction Strategy, ECRU Technologies, Inc. (2000) 2. Lambert, M.D., Cooper, C.M., Pagh, D.J.: Supply Chain Management: Implementation Issues and Research Opportunities. The International Journal of Logistics Management 44(2), 1–19 (1998) 3. Gintic, Measuring supply chain performance using a SCOR-based approach, Institute of Manufacturing Technology (March 2002) 4. Lapide, L.: What About Measuring Supply Chain Performance? ASCET 2 (2000) 5. Supply Chain Council, Operations Reference-Model Overview Version 8.0 (2006) 6. Bolstroff, P., Rosenbaum, R.: Supply Chain Excellence: A Handbook for Dramatic Improvement Using the SCOR Model. Amacom, New York (2003) 7. Quinn, K.: Establishing a Culture of Measurement – A Practical Guide to Business Intelligence, Information Builders (2003) 8. Computerworld, Executive Briefings - Get Smart About Business Intelligence (2005) 9. Datamonitor, BI Trends – What to Expect in 2006 (January 2006) 10. Decker, J., Brett, C.: The Joy of SOX: Part 2—The SOX Solution Blueprint, META Group (2003) 11. Betts, M.: The future of business intelligence, Computerworld (2003) 12. Lambert, M.D., Pohlen, L.T.: Supply Chain Metrics. The International Journal of Logistics Management 12(1), 1–19 (2001) 13. Atre, S.: The Top 10 Critical Challenges for Business Intelligence Success, Computerworld, Computerworld (2003) 14. Biere, M.: Business Intelligence for the Enterprise. Pearson Education, New Jersey (2003) 15. Inmon, H.W.: Building the Data Warehouse, 3rd edn. John Wiley & Sons, Chichester (2002) 16. Moeller, A.R.: Distributed Data Warehousing Using Web Technology. Amacom, New York (2001) 17. Stefanovic, N., Radenkovic, B., Stefanovic, D.: Supply Chain Intelligence. In: Pham, D.T., Eldukhri, E.E., Soroka, A.J. (eds.) Intelligent Production Machines and Systems, vol. 3, Whittles Publishing, Dunbeath (2007) 18. Haydock, P.M.: Supply Chain Intelligence. ASCET 5, 15–21 (2003) 19. Shobrys, D.: Supply Chain Management and Business Intelligence, Supply Chain Consultants (2003)
Supply Chain Business Intelligence: Technologies, Issues and Trends
245
20. Curt, H.: Supply Chain Intelligence: Applying Business Intelligence to Enhance Operational Efficiencies, Wipro (2002) 21. Wolfe, M.E., Wadewitz, R.T., Combe, G.C.: E-gistics, Bear, Stearns & Co. Inc. (2000) 22. Srinivasa, P.R., Saurabh, S.: Business Intelligence and Logistics, Wipro (2001) 23. Ferguson, M.: Developing a Service-Oriented Architecture (SOA) for Business Intelligence, BeyeNetwork (2007) 24. White, C.: What Do SOA and ESB Mean in Business Intelligence, BeyeNetwork (2007) 25. Everett, D.: Web Services and Business Intelligence. Hyperion, New York (2003) 26. Berenson, H.: Why Consider a Service-Oriented Database Architecture for Scalability and Availability, Microsoft (2005) 27. Microsoft, What is BAM? (March 2006), http://msdn2.microsoft.com/enus/library/aa560139.aspx 28. Ferguson, M.: Building Intelligent Agents Using Business Activity Monitoring. DMReview Magazine (Dec. 2005) 29. Stefanovic, N., Stefanovic, D.: Methodology for BPM in Supply Networks. In: 5th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering, Ischia, Italy (2006) 30. Hand, D., Mannila, H., Smyth, P.: Principles of Data Mining. MIT Press, Cambridge (2001) 31. Tang, Z.H., MacLennan, J.: Data Mining With SQL Server 2005. Wiley, Indianopolis (2005) 32. Larose, T.D.: Discovering Knowledge in Data. John Wiley & Sons, Chichester (2005) 33. Berry, M.J.A., Linoff, G.S.: Data Mining Techniques for Marketing, Sales, and Customer relationship Management. John Wiley & Sons, Chichester (2004) 34. Beal, B.: Application Vendors to Dig Into Data Mining (Jan. 2005), http://searchcrm.techtarget.com/originalContent/0,289142,sid11_gci10473 47,00.html 35. Bisconti, K.: Integrating BI Tools into the Enterprise Portal. DMReview Magazine (Aug. 2005) 36. Athena IT Solutions, BI as a Smart Investment (2006), http://www.athenasolutions.com/bi-brief/june03-issue3.html 37. McKnight, W., Humphrey, S.: Building Business Intelligence: Rafting Into the Business Intelligence Future. DMReview Magazine (Oct. 2004) 38. OMG, Common Warehouse Metamodel, CWM (2007), http://www.omg.org/ technology/documents/formal/cwm.htm 39. Computerworld, The Future of Business Intelligence (June 2004) 40. Linthicum, D.: Gartner Sees $19.3 Billion SaaS Market by 2011 (August 2007), http://www.intelligententerprise.com/blog/archives/2007/08 /gartner_sees_19.html 41. Flex News Desk, Business Intelligence in the world of Rich Internet Applications (2007), http://java.sys-con.com/read/280900.htm 42. Ames, B.: Web 2.0 tools inspire data-sharing software (2007), http://www.info world.com/article/07/04/18/HNweb2datasharingtools_1.html 43. Michalewicz, Z., Schmidt, M., Michalewicz, M., Chiriac, C.: Adaptive Business Intelligence. Springer, Heidelberg (2006) 44. Stefanovic, D., Stefanovic, N.: Methodology for modeling and analysis of supply networks. Journal of Intelligent Manufacturing 19(4), 485–503 (2008)
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