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Automated Statistical Analysis

Drives Inventory Management

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Automated statistical analysis drives inventory management
By Thomas R. Willemain, Ph.D.

 

Inventory managers struggle with the conflicting priorities of customer satisfaction vs. cost control.  Learn how to harness customer demand data to craft optimal inventory policies:

 

  • Measure current inventory policy performance – including service levels, fill rates, inventory turns, and ordering costs.
  • Identify improvement goals: Assess tradeoffs between inventory investment and the risk of running out. Where are you over- and under-stocked, and how can you do better?
  • Find your optimal balance point, setting reorder points and order quantities that will achieve the results you require.
  • Then make it so.

 

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    Pursuing best practices in demand planning, forecasting and inventory optimization

    Do your statistical forecasts suffer from the wiggle effect?

    Do your statistical forecasts suffer from the wiggle effect?

    What is the wiggle effect? It’s when your statistical forecast incorrectly predicts the ups and downs observed in your demand history when there really isn’t a pattern. It’s important to make sure your forecasts don’t wiggle unless there is a real pattern. Here is a transcript from a recent customer where this issue was discussed:

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