Demand forecasting — Pharma distribution
Probabilistic forecasts at SKU and store level, feeding replenishment. Delivered for a pharma distribution client in Junagadh.
- Location
- Junagadh
- Year
- 2023
- Duration
- 18 weeks
- Team
- 4 engineers
- −30%
- forecast error
- −47%
- stock-outs
- 26k
- SKUs modelled
The challenge
Data existed but lived in spreadsheets and legacy systems, so decisions were made on instinct rather than evidence.
What we built
We ran a two-week discovery sprint, then built and fielded the system end to end on LightGBM, Prophet and PostgreSQL, with operator training and an SLA.
Delivery timeline
Phase 1
Discovery sprint and site survey
Phase 2
Prototype built and tested in the Motera lab
Phase 3
Pilot on site with before/after measurement
Phase 4
Scale-out, training and handover
Highlights
- Safety case reviewed with the client's EHS team
- Documentation, drawings and source handed over at close
- Remote monitoring and over-the-air updates included
- Operator training delivered in Gujarati, Hindi and English
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