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A free worksheet that tests whether a demand or commercial forecast has a defined decision purpose, credible drivers, usable history and active ownership, before the business plans around its numbers. It produces no forecast values: readiness is the question.
Readiness by domain: the decision purpose and horizon are clear; historical data covers the horizon but changes definition partway through the series; pipeline evidence is strong; retention assumptions are unvalidated; and no reforecast trigger exists. The forecast would not be revisited until it had already failed.
Recommended method category: range-based planning now, with a data-preparation path towards a driver-based forecast. The result lists the assumptions needing validation first and the next-step questions to settle before any model is built, and deliberately produces no forecast numbers itself.
The worksheet examines each readiness domain against fixed criteria: is the decision defined, is the history usable, are the drivers credible, are the assumptions explicit, is anyone accountable for reforecasting. Each domain gets a readiness status, and missing or unstable inputs are flagged rather than smoothed over.
From that pattern the worksheet classifies the situation (ready for a driver-based forecast, needing data preparation first, or better served by a range-based planning approach) and builds a preparation plan. It never produces forecast values: a checklist that generated numbers would be exactly the kind of forecast it warns about.
Results are rule-based guidance generated from self-reported answers. They are directional, not accounting, legal or other professional advice, and a professional review working from evidence may reach different conclusions.
The worksheet is designed to run inside Web Lifter Studio. Each worksheet is linked to a named forecast, planning horizon and management decision, and saved in your own workspace with its assumptions and review dates, so Studio can prompt you to update it when actuals arrive and track which assumptions changed. Responses are used to generate your result and to make recommended next steps more relevant; they are not published. If you join the waitlist before launch, your details are used only to tell you when the tool opens.
The most common forecasting failure isn't a bad model: it's a model the inputs never justified. The worksheet distinguishes three honest positions: ready for a driver-based forecast, where history and drivers hold up; data preparation first, where the inputs are the constraint; and range-based planning, where committing to a single number would be false precision. Naming which position you are in is worth more than any forecast built while pretending otherwise.
A forecast is a set of assumptions with a shelf life. The worksheet records each assumption explicitly, with a review date and an owner, and is designed so Studio prompts an update when actuals become available, tracking which assumptions moved and whether reforecast ownership is actually active. Over repeated cycles that record becomes the audit trail of how the business's forward view is formed, not just the number it landed on.
When the result points at a constraint that needs professional depth, these engagements pick it up.
Registration is free, no card required, and your results save to your workspace so the working stays in one place.