This paper shows one methodology of using predictive modeling in planning and scheduling decisions in supply chain management. It is important to remember that the variables will be different depending on the industry and client-specific requirements.
The latest development in data mining, predictive modeling, marketing analytics, artificial intelligence, analytics, intelligent agents, semiconductors, distributing computing, and network security. SAS, Fair Isaac, Microsoft Analysis Services, SPSS, Cognos, Hyperion, Business Objects, Oracle, KXEN,or R. Healthcare, Pharmaceutical,Retail, CPG, Travel, Financial, Banking, Telecommunications, or Insurance. Unleashing the Power of the Mind©™
Wednesday, September 12, 2007
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Blog Archive
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2007
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September
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- Mobile Business Intelligence - the Next Big Step
- Duke Plots Course Beyond the Smart Grid
- VP, Decision Support Systems
- Market Forecasting and Modeling for the Power Syst...
- Predictive Planning for Supply Chain Management
- F.B.I. Data Mining Reached Beyond Initial Targets
- Frequent Doesn’t Mean Loyal: Using Segmentation Ma...
- Data Mining Analysis and Modeling for Marketing Ba...
- SUPERVISORY [BANK] RISK ASSESSMENT AND EARLY WARNI...
- Data Mining Applications in Higher Education
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- Integrating Customer Value Considerations into Pre...
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September
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About Me
- alberto
- See my resume at: https://docs.google.com/document/d/1-IonTpDtAgZyp3Pz5GqTJ5NjY0PhvCfJsYAfL1rX8KU/edit?hl=en_USid=1gr_s5GAMafHRjwGbDG_sTWpsl3zybGrvu12il5lRaEw
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