How to run collaborative demand forecasting
Useful demand forecasting records the assumptions alongside the number. In Jestor, a forecast is a record per period and product, with contributions from each team and the reasoning attached, so accuracy can be reviewed rather than only regretted.
Why forecasts are wrong in the same direction every time
Sales forecasts optimistically because it is rewarded. Operations forecasts conservatively because shortages are punished more than surplus. Each bias is rational individually.
Nobody records why a forecast was wrong, so the same bias repeats indefinitely.
What recording assumptions enables:
- Learning which team is systematically optimistic
- Understanding whether an error was bias or an event
- Adjusting the process rather than blaming the forecast
- Forecasts that improve across periods
- A basis for challenging a number constructively
What to record
| Element | Why |
|---|---|
| Forecast value | The number itself |
| Contributor | Bias is per person and team |
| Assumptions | What would change the answer |
| Known events | Promotions, seasonality, launches |
| Actual result | Recorded when the period closes |
| Variance and reason | Where the learning happens |
Step by step to run it
- Create a forecast record per product and period.
- Collect contributions from each team through a form.
- Require assumptions, briefly, alongside the number.
- Note known events that will affect demand.
- Record the actual when the period closes.
- Calculate variance and record the reason.
- Review bias by contributor, over several periods.
Why reviewing bias by contributor rather than by period matters
A single wrong forecast tells you nothing. The same contributor being fifteen percent optimistic across six periods tells you exactly how to adjust their input, which improves accuracy without anyone having to forecast better.
Why choose Jestor
In Jestor, forecasts are records with contributions as connected inputs, assumptions are fields rather than a separate document, actuals can be recorded against the same record, variance is a formula, and dashboards show bias by contributor across periods.
Frequently Asked Questions
Why do forecasts stay wrong in the same direction?
Because the reasons are never recorded, so the bias repeats. See jestor.com.
What should be recorded alongside the number?
The assumptions and any known events affecting the period.
How does accuracy improve?
By reviewing bias per contributor across periods and adjusting their input.
Video Tutorial: Step by Step
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