Demand Forecasting
An evidence-based estimate of how much of each product will sell, where, and when.
What it does
Demand forecasting is the practice of using your own sales history — together with what you already know about seasonality, promotions, pricing and outlet mix — to estimate future sales for each product at each location. Instead of one person's judgement applied across hundreds of items, every item gets a forecast produced the same way, on the same evidence, and measured afterwards against what actually sold. The point is not a perfect number. It is a number you can defend, repeat every cycle, and improve as you learn where it goes wrong.
Who it is for
Businesses ordering or producing on experience and spreadsheets, and paying for it at both ends: stockouts on the lines that move, write-offs and tied-up cash on the lines that do not. Typically an FMCG, distribution or retail operation with enough SKUs and outlets that no one can hold the whole picture in their head.
What you receive
- A forecast for every product and location, at the time horizon and granularity your planning cycle actually uses
- Forecast accuracy tracked against real sales each cycle, so the method is accountable rather than assumed
- An exception list flagging the items where the forecast is not yet trustworthy, and why
- A back-test comparing the new forecast against your current method over your own historical data
- Your team trained to read, challenge and override the forecast — not just receive it
A typical engagement
- 1Enablement sessions covering what a forecast is, how accuracy is measured, and what it can and cannot tell you
- 2Assessment of your sales history: coverage, gaps, and the cleaning required before it can be modelled
- 3A baseline forecast produced and back-tested against your existing method over a historical window
- 4Configuration against your product hierarchy, locations and planning calendar
- 5Go-live, followed by an accuracy review in each planning cycle