By Roger Knocker
June 29 2026
Driver Based Forecasting: Why the Hockey Stick Never Came
Roger Knocker • June 29, 2026
Driver Based Forecasting
vs. Optimistic Predictions
Why the hockey stick never came and how driver based forecasting
helps finance teams see the truth early.
Gary had a strong track record in software sales, so when he wanted to join our small start-up, I was surprised. But he was confident.
Three months passed.
Over Easter weekend I finally sat down to check the numbers.
Zero.
Not a single sale from Gary.
The only work we did win came from old colleagues referring leads to me directly.
Whenever we asked about his pipeline, he gave the same answer:
Month four.
Month five.
Gary blamed the slow market. Apparently Easter had caught everyone off guard that year.
Then came his big promise.
The Hockey Stick
We stopped waiting and built our own simple driver based pipeline instead:
- Customer name
- Quantity × Price
- Deal probability %
- Expected landing date
The hockey stick vanished instantly.
There was never a spike coming and Gary moved on soon after.
I see the same pattern in finance teams.
Revenue forecasts based on optimism rather than drivers.
Budget plans that assume everything will “pick up in Q3.”
Pipeline reports that are really just wish lists with percentages attached.
Driver based forecasting removes the guesswork.
When you break down your forecast into actual business drivers, headcount changes, price adjustments, volume shifts, and conversion rates, you get a number you can stand behind in a board meeting.
The truth shows up early, whilst you still have time to adjust the plan rather than explain the miss.
The sooner you understand what is really driving performance, the sooner you can make better decisions.
Learn how AI can help finance teams document a revenue planning process, define dimensions and KPIs, and create a stronger foundation for model design.
Learn how AI can turn meetings, documents and manual input into structured revenue planning process documentation, creating a stronger foundation for model design and implementation.
