All work
AI
Predictive analyticsDemand Forecasting
Demand forecasting that cut stockouts and waste across a regional network.
Year
2024
Timeline
6 months
Team
5 engineers
Focus
Predictive analytics
Results that matter
- +34%
- better forecast accuracy
- −45%
- fewer stockouts
- −28%
- less waste
The challenge
A logistics operator planned inventory with spreadsheets and intuition , leading to costly stockouts on some lines and overstock on others.
Our approach
We built a forecasting system that blends historical demand, seasonality and external signals, with automated retraining, anomaly alerts, and dashboards the planning team actually uses day to day.
The outcome
Forecast accuracy up 34%, stockouts down 45%, and waste down 28% , with planners spending far less time firefighting.
What we delivered
Multi-signal demand models
Automated retraining pipeline
Planner-friendly dashboards
Real-time anomaly alerts
Tech stack
PythonTensorFlowNumPyPostgreSQLDockerGrafana
“We went from guessing to planning with confidence. The forecasts pay for the project several times over every quarter.”
, VP Supply Chain, Logistics operator
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