Predictive forecasting
An illustrative look at how we turn scattered retail data into demand forecasts a team can plan against, with a clear view of cash runway and balances.
An illustrative example of the kind of work we do, not based on a specific client engagement.
The pain point
Planning ran on gut feel and last year's spreadsheet. The result was the classic retail bind: too much cash tied up in the wrong stock, and stockouts on the items that actually sold.
Without a trustworthy forecast, every buying decision carried avoidable risk, and finance couldn't see the cash runway clearly.
Our approach
We start with a hard look at the data (what exists, what's usable, and what's quietly missing), then build demand-prediction models on top of it, plus a clear view of cash runway and balances.
The models are built to be retrained and monitored, not handed over as a one-off.
What we built
The kind of system we build for this:
- Data audit: mapped and cleaned the inputs the forecast depends on.
- Forecasting models: demand prediction with a measurable lift over the old baseline.
- Cash-flow dashboards: runway and cash-balance views finance can act on.
- Retraining loop: models stay honest as the business changes.
The outcome
Done well, buying decisions start from a forecast the team trusts: less cash stuck in the wrong stock, fewer empty shelves, and a clear view of the runway ahead.
Have a problem like this?
Let's talk about what it would take to ship.