Building better
Financial Forecasts
A good forecast is not a prediction—it's a decision tool. Treat it like one.
Start with principles (from research and practice):
- Longer line of sight, frequent refresh. Pair a 12–18-month horizon with monthly updates; this beats one-and-done annual budgets. Harvard Business Review
- Driver-based, not account-based. Tie revenue and cost lines to causal drivers (pipeline, win rate, ramp, utilization). KPMG Assets
- Multiple futures, not one. Always frame Base/Best/Worst and stress tests. Investopedia
A simple build sequence (you can implement this week):
- Define 5–7 drivers. Example: leads → conversion → ASP; seats → churn; hires → ramp → quota. Document each formula. Corporate Finance Institute
- Choose your cadence. Monthly rolling forecast through next 15 months; quarterly beyond. Harvard Business Review
- Calibrate. Back-test last 6–12 months; record forecast error by line item to find weak links. (HBR reminds us forecasts are "wrong but useful"—track error to get useful faster.) Harvard Business Review
- Scenario set. Build Best/Base/Worst with explicit assumptions (price, volume, hiring, FX) and pre-wire cash sensitivity. Investopedia
- Close the loop. After each month, run variance attribution (price vs. volume vs. mix) and update driver coefficients.
Trade-offs to name:
- Rolling vs. static budgets. Rolling improves agility but requires discipline and tooling; static is simpler but goes stale quickly. Finance Alliance
- Fewer vs. more drivers. Fewer drivers = clarity and speed; more drivers = detail but slower cycles. Start lean; add only if error stays high.
Mini-case: A services firm moved from static to rolling forecasts and switched to a utilization-driven model. By linking hiring to backlog and capacity, it reduced overtime by 18% in peak months while holding revenue constant. (Internal observation; your mileage may vary.)
"Most teams still spend ~75–85% of time gathering/administering data—not analyzing it."
— APQC
Alantra bakes these practices in—driver-based modeling, rolling cadence, and scenario packs—so your team can ship a better forecast in days, not quarters.