Data & Analytics · Consumer Goods
Predictive Analytics & Forecasting
Built demand-forecasting models to reduce stockouts and overstock across a multi-warehouse distribution network.
+22%
Forecast accuracy
-30%
Stockouts
14 weeks
Duration
The Brief
CPG Distributor needed a partner to move quickly on predictive analytics & forecasting without compromising on quality or long-term maintainability. CloudGrips ran the engagement end-to-end, from discovery through production support.
What We Built
- Implemented and integrated Python as part of the delivered solution.
- Implemented and integrated scikit-learn as part of the delivered solution.
- Implemented and integrated Airflow as part of the delivered solution.
Phase-by-Phase
001DISCOVER
Scoping & discovery
Mapped current workflows, stakeholders and constraints to define a phased delivery plan.
002BUILD
Build & iterate
Delivered in short iterations with regular stakeholder demos and course-correction.
003DEPLOY
Deploy & support
Rolled out to production with monitoring in place, followed by a stabilization period.
At a Glance
Sector
Consumer Goods
Capability
Data & Analytics
Tech Stack
Pythonscikit-learnAirflow
Illustrative engagement
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