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Improving Sales Forecasting of Consumer Products

Challenge

A major CPG company was relying heavily on its Field Sales team qualitative information to forecast unit sales. This method resulted in significant inefficiencies and error rates, ranging between 50 to 100% on the SKU/product level, wreaking havoc on supply chain business processes and inventory management.

Actions

  • Worked with SVP Sales, SVP Marketing, SVP Operations to address shortcomings of current forecasting methodology.
  • Compiled a database to collect historical sales data and retail market drivers (e.g., price, distribution, promotion) over the last several years.
  • Created comprehensive data-driven multivariate regression models to more accurately predict sales.
  • Conducted comprehensive research on variables that drove sales.

Results

  • Compiling extensive market-drivers saved the company $200,000 it had planned to commit to a marketing-mix research study.
  • Implemented marketing-mix analytics to determine the variables that drive sales.
  • Demonstrated to Executive Management that in-store trade promotions proved a more effective way to spend marketing dollars.

"Can we hire the analyst from DataKey as a full-time employee? This work is extraordinary!"

- Chief Executive Officer

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