Serving up greater responsiveness and less bias

A global food manufacturer and Implement Consulting Group

29 May 2010

The project

With the desire to improve the foundation for their demand planning process, this global food manufacturer set about creating a stronger, smoother solution that could handle both baseline and promotion demand as well as statistical forecasting.

The new process was built on simple forecasting concepts. A segmentation model helped define how different products should be forecasted and on which product planners should focus their time.

A number of demand planning key figures, both for baseline and promotion demand, were incorporated into the demand planning solution, collectively resulting in a markedly improved consensus forecast.

The number of manually forecasted products was significantly reduced – instead these products were now handled through statistical forecasting.


The impact

  • 50% reduction of forecast bias.
  • 22% fewer forecast errors.
  • Reduction of manually forecasted products from 60% to 25%, creating huge manual task time savings.
  • Significant reduction in manual data loads and data preparation in Excel, equivalent to 3 work days/month in the supply chain planning team.
  • Improved data and process transparency through one set of numbers: shared data model between sales, demand planning and S&OP.

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