Leading UK Retailer
Availability and Profitability of Food Products
Problem
The client encountered challenges with the availability and profitability of food products in certain stores. Inventory planners relied on expert judgment to make forecasts, and there was a need for a more refined approach to enhance forecasting accuracy.
Solution
We implemented an AI-driven system featuring a driver model, designed to identify the key factors influencing forecast errors. Additionally, we developed a Spotfire dashboard to provide insights into forecasting accuracy and monitor performance.
Outcome
The system significantly improved the understanding of forecasting accuracy, offering clearer insights into the factors affecting it. This empowered inventory planners to make well-informed decisions, reducing the need for constant interaction with the forecasting and ordering system.
Transforming Forecast Accuracy with AI-Driven Insights
The client faced challenges with food product availability and profitability across some of their stores, with forecast inventory planners relying on expert judgment rather than data-driven decisions. In response, they approached us to refine their forecast model to enhance accuracy. We implemented a driver model to identify the key factors contributing to forecast errors. Based on the insights from this model, focused initiatives were planned and executed. Additionally, a Spotfire dashboard was designed to provide a dedicated space for reviewing forecast accuracy over past weeks, with a feature to highlight stores and products showing the worst forecasting performance.
The implementation of the above initiatives resulted in significant business improvements, generating an additional £2.2M in profit. The availability of products increased from 92% to 94%, while waste was reduced by 0.5%, from 6.5% to 6%, for the financial year. These efforts empowered more accurate, data-driven decisions, improving both profitability and operational efficiency.
Profit Up, Waste Down!
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