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Database Mining in Enterprise Resource Planning. UCI Freshman Seminar May 10th, 2004 Patrick Nguyen Huu. Introduction To ERP.
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Database Mining in Enterprise Resource Planning UCI Freshman Seminar May 10th, 2004 Patrick Nguyen Huu
Introduction To ERP • Enterprise Resource Planning is a software architecture that facilitates the flow of information among the different functions or processes of an enterprise (manufacturing, logistics, HR, supply-chain management, etc) • ERP provides the backbone for an enterprise-wide information system • A database, in turn, is the backbone of an ERP system
The ERP Software Industry • Until recently, “JBOPS“ were market leaders (J.D. Edwards, Baan, Oracle, PeopleSoft, SAP) • “JBOPS“ -> “SOPMS“ (PeopleSoft acquired J.D. Edwards, Oracel has a hostile bid for PeopleSoft, Baan->Invensys->SSA Global Tech) • There is a number of specialized providers (Siebel Systems for customer relationship management, i2 for supply-chain mgmt) • D-Base companies provide the backbone (Oracle, MS(SQL), Sybase, IBM)
The Business Intelligence Imperative • Forces on the supply side: • The Internet reduces barriers of entry in many markets • Interactive customer channels and increased bandwidth • Explosion of power and data storage capabilities Forces on demand side: Increasingly informed and empowered customers Lower search costs Higher customer acquisition costs => As a result, the leverage of corporate data resources is becoming essential for business success
Clustering: Partitioning a d-base so that records within each group are sufficiently alike Profiling: Obtaining a generalized classification model from a database sample Factor Seeking: Finding interdependencies in the data based on associations between groups of attributes Database Marketing: Translates customer purchase and demographic information into an individual purchase probability, by means of a response model based on purchase history, demographic variables, and product attributes Tools For Responsive Marketing
Calyx&Corolla – Marketer of floral arrangements: Analyzes customer d-base to determine which customers to target with different flower catalogs to balance prospecting costs against the lifetime value of the customer Franklin Mint – direct marketer of quality collectibles and products: Sends catalogs to only those customers with the highest propensity to purchase the offered product; this increases the response rate, lowers costs and increases profits Capital One – leading credit card issuer: Uses customer profitability analysis to deliver the “right product to the right customer, at the right time and at the right price“ Companies Built Around D-Base Marketing
The Harrah‘s Case • Harrah‘s Casino, Las Vegas: • Difference form other casinos: focus on the middle-class, medium-scale gamblers rather than the “high-rollers“ • Had several attempts at customerinitiatives, such as the “Gold Rewards“ => Collected a bulk of customer data via these cards (purchases, points of visits, etc) • Realized that the bulk of their income came from small to medium scale gamblers, utilized their database of customer data to customize service for each individual cardholder
What Made Harrah‘s Success • Harrah‘s is mainly a casino facility with slotmachines and the occassional gambling tables. It lacks the glamorous attractions and shopping centers of comparable casinos in Las Vegas • Unlike other casinos – who draw their main income through the attractions and shops – Harrah‘s focuses on creating its “loyal“ clientele and providing best service, giving them incentive to return • Service for their clientele is personalized, based on the analysis of the data collected from the individual cardholder