Company

Building Better Financial Forecasts

A
Alantra Team
September 15, 2024

Building better

Financial Forecasts

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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):

  1. Define 5–7 drivers. Example: leads → conversion → ASP; seats → churn; hires → ramp → quota. Document each formula. Corporate Finance Institute
  2. Choose your cadence. Monthly rolling forecast through next 15 months; quarterly beyond. Harvard Business Review
  3. 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
  4. Scenario set. Build Best/Base/Worst with explicit assumptions (price, volume, hiring, FX) and pre-wire cash sensitivity. Investopedia
  5. 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.