Log actual vs. estimated time for every task
Build a personal database of your own estimation errors so you can calibrate future predictions.
Key takeaways
- What it is: Build a personal database of your own estimation errors so you can calibrate future predictions.
- Why it works: The planning fallacy persists partly because its errors are invisible: you finish late, update the calendar, and forget the original estimate. Tracking creates a feedback loop where the cost of optimism is made explicit and memorable. Calibration research shows that people can become better-calibrated forecasters through repeated feedback on their predictions — but the feedback must be systematic, not occasional. A running log of your own ratio (actual / estimated) is a personalized reference class.
- Evidence: Plausible mechanism, limited direct outcome data.
- Avoid: Logging time only for tasks that went over estimate — this gives a biased sample. Logging only surprises skews your correction factor and makes you overcorrect.
Why it works
The planning fallacy persists partly because its errors are invisible: you finish late, update the calendar, and forget the original estimate. Tracking creates a feedback loop where the cost of optimism is made explicit and memorable. Calibration research shows that people can become better-calibrated forecasters through repeated feedback on their predictions — but the feedback must be systematic, not occasional. A running log of your own ratio (actual / estimated) is a personalized reference class.
How to do it
- 1Before starting a task, write down your time estimate.
- 2After finishing, record the actual time taken.
- 3Calculate your personal ratio (actual / estimated) over a month of data.
- 4Multiply your estimates by your average ratio going forward.
- 5Review monthly to see if the ratio improves.
What the evidence says
MechanisticCalibration training research (e.g., Lichtenstein & Fischhoff, 1980) shows that feedback on confidence intervals improves forecasting accuracy over time. Application to personal time estimation is mechanistically plausible but less formally studied.
Honest caveat: Most calibration training research is on probability judgments, not time estimates; transfer to scheduling is reasonable but not directly proved.
- — Lichtenstein & Fischhoff (1980), Training for calibration, Organizational Behavior and Human Performance
Common mistake
Logging time only for tasks that went over estimate — this gives a biased sample. Logging only surprises skews your correction factor and makes you overcorrect.
IX Coach maintains your estimation log automatically, shows you your running accuracy ratio, and pre-adjusts new goal timelines based on your actual history.
Practice this with IX Coach →