Turning salad sales data into less food waste
Demand forecasting: 25%+ increase in number of days 95% accuracy achieved
Our client was a high turnover/low margin food supply business. How could they improve their demand forecasting to increase profit through reduced waste and optimised warehouse and haulage use?
Predictive models delivered in 3 weeks
Over just three weeks, we worked closely with the client to understand how factors like holidays, events, weather, trends and news affected demand. We then used this data to train a machine-learning model for each product sold. Performance was measured against metrics allowing direct comparison with their current forecasting.
