The problem
A services revenue forecast is usually the delivery schedule summed by month. The schedule assumes every project lands on time and on budget, and the finance team adds a haircut from experience. When projects slip, the forecast learns about it at month end.
Whether a project will slip is predictable from the projects before it: team, client, scope, and phase. That prediction belongs in the forecast.
How it works
For each active project, _predict returns the probability of on-time and of on-budget delivery, each with its $why. The application spreads the project's value over the months it is scheduled for and adjusts each month by the predictions, so the scheduled line and the predicted line sit side by side.
A project whose prediction moves shows up in the gap between the two lines, with the drivers that moved it.
For the full architecture, see the technology overview. For the broader narrative across multiple use cases, read The Predictive Application.
See it live
This use case runs in the 📋 ERP demo today. Click through to the live application and inspect the queries that produce the result.
