Task:
Improve process and reduce manual time spent deciding how much product should be distributed to each store

Overview:
- It took 3 days per week to pull data, update sheets and analyse before determining the next week’s distribution
- Created automated data pipelines to enable combined hourly stock and sales data to create modelled store distribution grades using mathematical models to account for socio-economic factors

Impact:
- Enabled timelier response to stock distribution needs, freeing up resource for more value add activities
- Democratised stock availability data across business to ensure more data-informed decisions especially in Buying & Merchandising


Key Statistics:
4.2 FTE resource saved
~ 5% Stock Availability Increase
+£40m Modelled Gross Sales Impact