Service
Decision Modelling & Predictive Analytics
The gap between "we have the data" and "we know what to do" is a model. We build forecasting, pricing and incentive models that turn your history into better decisions.
What you get
- Sales and stock forecasting — predict demand, optimise inventory, protect cashflow
- Net revenue management — optimal pricing, promotions and portfolio decisions
- Stock decision management — consolidate multivariate data into actions your team can take today
- Commission and incentive scheme modelling, simulated against your real transaction history
- Causal impact measurement — know what an intervention actually changed
- Python
- pandas
- SQL
- Statistical modelling
Forecasting and stock decisions
Past sales, seasonality and market trends carry more signal than most businesses use. We build forecasting models that predict demand at the level you buy at — so you hold less stock, miss fewer sales, and free up cash.
Pricing and net revenue management
Price, promotion and portfolio decisions compound across a product’s lifecycle. We model the trade-offs so you can set prices deliberately, run promotions that pay for themselves, and retire products at the right time.
Incentives that pay for the behaviour you want
Commission schemes drift. We rebuild them from your actual transaction history: simulating candidate schemes against years of real sales data so you can see the cost, the winners and losers, and the behaviour each design rewards — before you commit to it.
Measuring what actually changed
When you open a store, change a price, or launch a channel, the honest question is “what would have happened anyway?” We use causal methods — cohort comparisons and difference-in-differences designs — to separate real impact from noise, so the next decision is made on evidence.