Hour 7: Business Intelligence & ERP

1. Hour 7:Business Intelligence & ERP ERP offers opportunity to store vast volumes of data This data can be data mined Customer Relationship Management

2. Data Storage Systems • Data Warehousing • Orderly & accessible repository of known facts & related data • Subject-oriented, integrated, time-variant, non-volatile • Massive data storage • Efficient data retrieval • CRM one data mining application • Can use all of this data • Common ERP add-on

3. Granularity • Definition – level of detail • Most granular – each transaction stored • Averaging & aggregation loses granularity • Data warehouses usually store data at fine levels of granularity • You can’t undo averages & aggregates

4. Data Marts • Different definitions • Small version of data warehouse • Temporary storage of data • possibly from multiple sources • for a specific study

5. On-Line Analytic Processing • OLAP • Multidimensional databases • Display data on selected dimensions • Time • Region • Product • Department • Customer • Etc.

6. Data Quality • Problem causes • Data corrupted or missing • Failure of software transferring data into or out of data warehouse • Failure of data cleansing process

7. Data Integrity • No meaningless, corrupt, or redundant data • Part of data warehousing function to clean data • Data standardization • Remove ambiguity (different ways to abbreviate) • Matching • Associating variables (unique mapping)

8. Database Product Comparison

9. Data Mining • Analysis of large quantities of data by computer • Micromarketing • Versatile • Apply to a wide variety of models • Scalable • Can analyze very large data sets

10. Types of data mining • Hypothesis Testing • Traditional statistics • Knowledge Discovery • No predetermined expectation of relationships

11. Business Data Mining Applications

12. Customer Relationship Management • Determine value of customer • Identify what they want • Package products (services) to keep them • Maximize expected net present value of customer

13. Data Warehouse Use Wal-Mart Fingerhut

14. Wal-Mart Data WarehouseFoote & Krishnamurthi [2001] • Wal-Mart dominates retail market • Heavy user of information technology • Supply chain distribution to 2,900 outlets • A critical success factor • Data warehouse of 101 terabytes • Possibly world’s largest • Investment over $1 billion • Can handle 35,000 queries per week • Benefits over $12,000 per query

15. Wal-Mart • Initial data warehouse • point-of-sale & shipment data • Added data • Inventory • Forecast • Demongraphic • Markdown • Return • Market basket information

16. Wal-Mart Data Warehouse • Process 65 million transactions per week • 65 weeks of data per item • By store • By day • Support decision making • Many users have access • Including 3,500 vendor partners

17. FINGERHUT • Founded 1948 • today sends out 130 different catalogs • to over 65 million customers • 6 terabyte data warehouse • 3000 variables of 12 million most active customers • over 300 predictive models • Focused marketing

18. Fingerhut • Purchased by Federated Department Stores for $1.7 billion in 1999 (for database) • 2002 – more recent developments • Fingerhut had $1.6 to $2 billion business per year, targeted at lower-income households • Can mail 400,000 packages per day • Each product line has its own catalog

19. Fingerhut • Used segmentation, decision tree, regression, neural network tools from SAS and SPSS • Segmentation - combined order & demographic data with product offerings • could target mailings to greatest payoff • customers who recently had moved tripled their purchasing 12 weeks after the move • send furniture, telephone, decoration catalogs

20. Advanced Technology & ERP Bolt-ons Middleware Security

21. Technology & ERPManetti [2001] • Mobile commerce & other IT makes ERP extensions possible, attractive • Broader use of web-enabled systems • Greater AI-driven applications • Greater use of ERP in mid-sized manufacturing • Flexible modular systems • More bolt-ons (3rd party applications) • Creates security issue

22. Conflict: ERP & Open Systems • Original concept of ERP closed • Easy to control access • Openness creates security issues • But there are too many good things to do with open systems • ERP vendors also provide such products

23. Example Bolt-OnsMabert et al. [2000]

24. Middleware • ERP interfaces to external applications difficult to program • Middleware is an enabling engine to allow such external applications eto ERP • Data oriented products - shared data sources • Messaging-oriented - direct data sharing

25. Web ERP • J.D. Edwards OneWorld • SAP mySAP.com • Trends • More web links • More functionality

26. Middleware & Data Acquisition • Bar-code data collection • Radio frequency data collection • Web portals

27. Portals of Major ERP VendorsStein & Davis [1999]; Stein [1999]

28. Other Vendor PortalsStein & Davis [1999]

29. ERP Security Threats

30. Summary • ERP security originally was not problematic • Only few internal users could access • Open systems driven by external applications • Creates security issues • Web access especially problematic • Special ERP Security aspects • Data quality • Control over data access

31. Bolt-On/Middleware Examples Kellogg Company Brown et al. [2001] Dow Corning Teresko [1999]

32. Kellogg Company Bolt-On • Kellogg developed their own ERP • Forecast demand • Take customer orders • Coordinate raw material purchasing • Coordinate production of over 100 food products • Coordinate distribution • Added linear programming Kellogg Planning System (KPS) • Production, inventory, distribution planning • Budgeting & capacity expansion

33. History • Long user of MRP, DRP (distribution resource planning) • 1987 realized product line growth, international expansion led to need for more computer support • Developed KPS in 1989, modified over time • By 1994 strong cost system in place • Saved $4.5 million in 1995

34. Kellogg LP • Minimized total cost • Purchasing, manufacturing, inventory, distribution • Variables: product, package size, case size • 30 week planning horizon • Constraints: • Line, packaging capacities, flow constraints, inventories, safety stocks • 700,000 variables, 100,000 constraints, 4 million non-zero coefficients

35. Kellogg LP • Continuous model took several hours to run • Generated starting solution for managers • Probabilistic features dealt with through safety stock • Example of bolt-on to ERP • Linear programming generated better plans

36. Dow Corning System Integration • 1995 adopted SAP R/3 to integrate global business practices • Also adopted SAP data warehouse • Consolidated information generated internally, externally • Internal: plant-floor data, patent information, benchmarking • Allowed deeper data analysis

37. Dow Corning System • Over 4,000 users had access • Integration & data compatibility problems dealt with by data warehouse • Added automated data collection system • Required middleware • Middleware allowed expansion into supply chain management

38. Summary • Customer Relationship Management very promising • Has not reached all expectations as ERP add-on • Quite expensive to get needed data storage capability • Still an opportunity to use all the data generated by an ERP • Many other useful bolt-ons