F100 pharma achieves 1.5X improvement matching supply to peak demand across geographies
In keeping with geographical regulations, the client needed a solution to ensure retailers across the region had enough supply to meet customer demand during peak seasons. Internal experts manually reviewed historical data such as previous sales, including around 4000 purchase entries every month, to flag outliers. This included distributed data in different formats, with no clear record of rules, and no consistent measure to evaluate decisions.
MResult kicked off the first step of automation by harmonizing the data. The MResult AI team then stepped in to build a suggestion engine using Machine Learning to automatically identify and classify purchase outliers. Only outliers below a pre-defined level of confidence were then passed on to the client expert team for manual review.