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Sales forecasting process improvement: Case study


This major FMCG manufacturer sells beverages to the major high street retailers as well as to large numbers of wholesale and foodservice outlets.

A sales forecasting procedure had been in place for some time, including the use of a software package.  Although a statistical forecast was routinely produced it was not of a high quality, with the result that members of the sales team were manually entering both baseline and promotional forecasts for every product and customer at a weekly level and over a very long forecast horizon.  Forecast accuracy was poor in some sectors.

A project was established with the twin objectives of improving forecast accuracy and reducing sales force time spent on the forecasting process.  Forecast Solutions was chosen for the project.

Initial investigation suggested that it should be possible to improve the quality of the statistical forecast that was being generated by the forecasting software.  Subject to that being possible it was agreed that the statistical forecast could potentially form the main basis of the baseline forecast.  This should free up sales managers' time, allowing them to concentrate on instances where they could add the greatest value, such as forecasting for new product development and promotions.
 
A number of measures were therefore taken to improve the accuracy of the statistical forecast.  The history of old and obsolete products was linked to that of successor products so that a more reliable forecast could be produced.  Work was carried out to establish the most effective level of detail for carrying out the seasonal analysis and the parameters available within the forecasting software were fine-tuned in order to maximise the accuracy of the statistical forecast.

The statistical forecast then became default baseline at the detailed SKU / customer level unless an exception was entered by the sales team. 

Further enhancements were also made to the process to exploit the benefits of multi-level forecasting and reconcile in the most beneficial way the viewpoints of the demand planning team and the sales teams.

Major improvements in forecast accuracy have been achieved.


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