APPROACH
The approach to address the client’s challenge included:
· Analyze Store-SKU behavior and estimate phantom inventory
· Calculate corrected inventory at the store to estimate reorder point
· Generate OOS and zero scan alerts based on inventory levels and sales patterns at the store
· Use advanced ML algorithms to forecast Store-SKU level sales and compare with actual sales to identify anomaly due to shelf mismanagement
· Prioritize alerts based on business rules and $ opportunity
KEY BENEFITS
· ML-driven model to evaluate the impact of trade promotion spends
· Scalable platform to understand the trade spend effectiveness across brands and regions
· Visualization platform cum scenario planner was embedded to help category managers optimize trade spends
RESULTS
· Acting on 3% OOS results in an overall revenue boost of 4%
· Nudging merchandising teams to achieve higher alert reach resulted in an additional 1.5% revenue