Forecasting that the CFO can trust
Re-architecting pipeline data, stage definitions, and inspection rituals to bring forecast accuracy within 5% three quarters running.
The situation
- Three quarters in a row, the committed forecast missed by 12–18% — sometimes high, sometimes low — destroying boardroom credibility.
- Sales stages had drifted to mean different things in every region, and exit criteria were aspirational rather than enforced.
- The forecast was assembled in spreadsheets each week, with no audit trail of what changed or why.
How we engaged
Assess
Audited two quarters of closed pipeline to quantify slippage, stage-skip patterns, and where deal value was systematically wrong.
Redesign
Rebuilt the sales stage model with mandatory exit criteria, introduced a deal-scoring framework, and defined commit/upside/best-case discipline.
Implement
Reconfigured the CRM, deployed inspection dashboards, and trained every front-line manager on the new deal review cadence.
Optimize
Quarterly forecast retrospectives compared committed vs. actual by manager and segment, feeding model refinement.
What we built and ran
- A 6-stage model with binary, observable exit criteria
- A deal-scoring rubric combining champion strength, economic buyer access, and compelling event
- A weekly forecast call structure with standard artefacts (no slides, one view)
- An auditable forecast change log so movement could be inspected and learned from
What we'd carry forward
- Forecast accuracy is a data discipline problem dressed up as a modelling problem. Fix the inputs first.
- If exit criteria aren't binary and observable, reps will interpret them generously — every time.
- The forecast call is where the system gets enforced. Without a ritual change, the redesign decays in a quarter.
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