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driver-based forecast

Also called: driver-based forecasting, driver-based planning

A forecast built from the operational numbers that cause the financial ones (learners, lessons per learner, price, payout) instead of last year's totals plus a percentage.

A driver-based forecast builds the financial numbers from the operational ones that cause them. Instead of "last year plus 10%", it forecasts the drivers (customers, usage per customer, price, unit costs, exchange rates, hiring) and lets the money follow by formula. Money is the output of the sheet, not its input.

For a subscription or lessons business one month is a chain: customers × usage = units; units × price = sales; units × (price after fees − variable costs per unit) = contribution; contribution − fixed costs = operating profit. Fixed costs come from drivers too: support staff that follow customer numbers in steps, salaries that follow a hiring plan.

The point is not a nicer number but one people can argue with. Each driver has an owner and a reason, so the team can see which assumptions make the year, and when actuals come in, which driver missed. It also sets up the next tools: sensitivity analysis, scenarios, budgets built from drivers and variance analysis all work on the same sheet.

Example

Klasna's forecast drivers for next year: average price 650 UAH per lesson, tutor payout 415, video and AI 0.75 USD at 42, a 2.5% payment fee. One lesson leaves 0.975 × 650 − 415 − 31.50 = 187.25 UAH.

October: 1,010 learners × 6.5 lessons = 6,565 lessons; 6,565 × 187.25 = 1,229,296.25 of contribution. Fixed costs: three coordinators (114,000), team 600,000, office and tools 88,000, marketing 260,000 = 1,062,000. Operating profit: 167,296.25 UAH.

The same recipe for all twelve months gives 80,128 lessons and 2,251,968 UAH of operating profit, against 818,592.19 from "last year + 10%". The difference comes from two drivers, the price rising from about 620 to 650 and the payout from about 400 to 415, so those are the assumptions the board should watch.

Common mistakes

  • Growing totals instead of causes. "Plus 10%" can't say whether more customers, more usage or higher prices are behind it, and each costs differently.
  • Hard-coding fixed costs. Staff that follow volume in steps belong in the model as drivers.
  • Drivers without owners. Every driver needs someone who stands behind it and reports when it moves.
  • Too many drivers. Model the handful that move the result; detail beyond that is false precision.
  • Forgetting currency. Costs billed in dollars need their own rate driver.

Learn it in the course

  • Driver-based forecasting · Driver-based forecasting: revenue and profit from learners, lessons, price and payout instead of last year plus ten percent.