After years of post-mortems, the root cause of “we’re late” is usually bad estimates. You don’t need heavy math to do better—just ranges and discipline.
Use three-point estimates
For any task or work package, ask for:
- Optimistic (O): if everything goes right (no blockers).
- Most likely (M): the realistic middle.
- Pessimistic (P): if common blockers hit.
Then compute an expected effort: (O + 4M + P) / 6. It anchors optimism bias.
Build buffers openly
- Add a risk reserve tied to identified risks (not a secret 20% pad).
- Add a management reserve for unknowns at the project level.
- Keep reserves visible in your plan so sponsors see where contingency lives.
Model uncertainty lightly
- Group related tasks and assign ranges by affinity (integration, data, vendor).
- Roll up the expected value for a high-level view; keep P95 for executive asks.
- If you have time, run a quick Monte Carlo in a spreadsheet (100–500 trials is enough) to show probability of hitting key dates.
Calibrate with history
- Compare planned vs. actuals from similar efforts; adjust your O/M/P based on what actually happened.
- Ask SMEs for “percent confident” on their ranges—then test that over time.
Communicate the story
- Show the date as a range with confidence (e.g., “We’re 80% confident in landing between May 10–24”).
- Tie reserve usage to risks: when a risk materializes, draw from its reserve.
- Re-forecast monthly; publish deltas and drivers.
Good estimation is a habit. Use ranges, show your math, and revisit often. You’ll build trust and catch schedule risk while you can still act.