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Estimation Workshop Guide

Table output Has example

Estimate effort honestly with a team.

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Plan an estimation session. Work items to estimate: [WORK_ITEMS]. Team members and experience: [TEAM_EXPERIENCE]. Past data on similar work: [PAST_DATA].

Choose and explain three methods: three-point estimation (optimistic O, most likely M, pessimistic P; expected = (O + 4M + P) / 6; standard deviation = (P - O) / 6), relative sizing, and reference-class comparison with past projects.

Output format:
1. A worksheet applying three-point estimation to my items: Item | O | M | P | Expected | SD, with the arithmetic shown for two items.
2. Totals, and a range at roughly 80 percent confidence = expected total + 1.28 x square root of the sum of squared standard deviations.
3. A 60-minute agenda with timings.
4. Anti-anchoring rules (write estimates silently, then reveal) and a list of what to include (testing, review, meetings, waiting time).
5. Common errors: the planning fallacy, forgetting integration.
6. A calibration step comparing past estimates with actuals.
7. A message of about 100 words to the sponsor presenting the estimate as a range with assumptions.

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Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.

See an example result (fictional data)
Task: migrate 4,000 customer records.
Optimistic 16 h, most likely 30 h, pessimistic 62 h.
Expected = (16 + 4 x 30 + 62) / 6 = 198 / 6 = 33 hours.
Standard deviation = (62 - 16) / 6 = 7.7 hours.
Second task: configure reports, O 10, M 14, P 30. Expected = (10 + 56 + 30) / 6 = 16 hours; SD = 3.3.
Total expected = 49 hours. Combined SD = square root of (7.7 squared + 3.3 squared) = square root of 70.2 = 8.4.
About 80 percent confidence: 49 + 1.28 x 8.4 = 59.8, so quote 49 to 60 hours.
Tell the sponsor the range and the assumptions behind it.

Illustrative only, made-up data. Your results will differ and must be reviewed.

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