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Next-Generation Supply Chain Predictive Analytics: A Cornerstone to Demand-Driven Value Networks
11 March 2011
 
Noha Tohamy   John Hagerty  

Predictive analytics enable demand-driven value networks through segmentation, demand sensing and shaping, and profitable demand response.





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Table of Contents

Contents
  • Analysis
    • What Is Predictive Analytics?
    • Making Sense of the Terms
    • Predictive Analytics in the Supply Chain
    • Predictive Analytics: A Cornerstone to DDVNs
    • Are You Currently Using Predictive Analytics in Your Supply Chain?
    • Examples of Predictive Analytics in DDVNs
      • No. 1: Shaping and Responding to Demand for a New Product
      • No. 2: Shaping Demand for Excess Inventory
      • No. 3: Managing Supplier Risk for More Supply Chain Resiliency
      • No. 4: Managing Aftermarket Inventory for Better Customer Service
    • The State of the Supply Chain Predictive Analytics Solution Market
    • For Success, Overcome Significant Hurdles First
Tables
Table 1.
Different Analytical Techniques Answer Different Questions
Table 2.
Phases of Data Mining and Predictive Analytics
Table 3.
Traditional Supply Chain Solutions Offer Basic Predictive Analytics Capabilities
Table 4.
Characteristics of Advanced Supply Chain Predictive Analytics
Figures
Figure 1.
Discovering Patterns and Relationships
Figure 2.
Classification and Predictions
Figure 3.
Predictive Analytics in DDVNs




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Resource Id: 1585414