methodatlas
Method guideDecision Making

Three-Point Estimation

A practical method guide: clarify prerequisites and materials, understand the complete process, and look up outputs, pitfalls, and stop criteria.

ComplexityMedium
Time10-30 min je Item
Participants1-8
FormatWorkshop + async
MaturityCanonical
Plan Three-Point Estimation
01

Prerequisite

What needs to be finished first

Complete firstComparable subject

Close work package, unit, Done criterion, and dependencies; define O, M, and P as scenarios rather than target values.

Without a common frame, values are not comparable.
Complete firstEvidence access

Clear scope, historical analogies, O/M/P scenario sheet, calculation sheet, and assumption log

Missing data remains visible as uncertainty.
02

Preparation

What needs to be ready before start

Materials

Clear scope, historical analogies, O/M/P scenario sheet, calculation sheet, and assumption log

People / roles

Work owner · delivery experts · data/risk expert · facilitator

Pre-read

Close work package, unit, Done criterion, and dependencies; define O, M, and P as scenarios rather than target values.

Time needed

30–60 minutes per work-package group; evidence collection extra.

Setup

Prepare a workspace with Scope · Scenarios · Calculate · Drivers · Use; separate example from live data.

03

Core question

The one question this method answers

What range and triangular expected value follow from a plausible optimistic, most likely, and pessimistic scenario?

04

Flow

Phases with goal, actions, output and pitfall

Three different views of the same work are combined instead of asserting a mean without context. Uncertainty becomes a planning range and expectation. The approach is useful when buffers and risk need a clear rationale.

Three-Point Estimation · working structure

Fictional example

Fictional values show the actual method fields.

Three-Point Estimation · working structure
Work packageO · optimisticM · most likelyP · pessimisticCalculationRangeDriverReview
Provider tokenAdd evidence and rationale.4 days · API fits7 days · normal adaptation16 days · migration + certification rework(4+7+16)/3 = 9 days4–16 daysMigration/certificationAfter trial import
  1. 1. O · optimistic

    Provider token
    4 days · API fits
  2. 2. M · most likely

    Provider token
    7 days · normal adaptation
  3. 3. P · pessimistic

    Provider token
    16 days · migration + certification rework
  4. 4. Calculation

    Provider token
    (4+7+16)/3 = 9 days
  5. 5. Range

    Provider token
    4–16 days
  6. 6. Driver

    Provider token
    Migration/certification
  7. 7. Review

    Provider token
    After trial import

All values are fictional.

Reference · original teaching example

  1. 1

    Scope

    Estimate frame

    Goal

    Estimate frame: Define work, unit, Done, and included risks unambiguously.

    Inputs for this step

    • Close work package, unit, Done criterion, and dependencies; define O, M, and P as scenarios rather than target values.
    • Clear scope, historical analogies, O/M/P scenario sheet, calculation sheet, and assumption log

    Actions

    • Define work, unit, Done, and included risks unambiguously.

    Output

    Estimate frame

    Define work, unit, Done, and included risks unambiguously.

    Quality check

    Do all three values describe the same completed work?

    Pitfall

    Optimistic estimates less scope than pessimistic. Close scope once and vary only conditions between scenarios.

    Timing: 5–10 minutes

  2. 2

    Scenarios

    Three values

    Goal

    Three values: Derive O, M, and P from concrete conditions and analogies; verify O ≤ M ≤ P.

    Inputs for this step

    • Estimate frame

    Actions

    • Derive O, M, and P from concrete conditions and analogies; verify O ≤ M ≤ P.

    Output

    Three values

    Derive O, M, and P from concrete conditions and analogies; verify O ≤ M ≤ P.

    Quality check

    Are extremes plausibly reachable rather than perfect/worst imaginable?

    Pitfall

    P is doubled without naming a scenario. Record conditions, evidence, and trigger for each value.

    Timing: 10–20 minutes

  3. 3

    Calculate

    Expected value

    Goal

    Expected value: Compute triangular expected value E=(O+M+P)/3 and preserve the range separately.

    Inputs for this step

    • Three values

    Actions

    • Compute triangular expected value E=(O+M+P)/3 and preserve the range separately.

    Output

    Expected value

    Compute triangular expected value E=(O+M+P)/3 and preserve the range separately.

    Quality check

    Is the formula visible and calculated in one unit?

    Pitfall

    Expected value 9 is treated as a certain commitment. Report the value with O–P range and assumptions.

    Timing: 5–10 minutes

  4. 4

    Drivers

    Uncertainty view

    Goal

    Uncertainty view: Inspect M→P and O→M gaps for dominant uncertainty and controllable actions.

    Inputs for this step

    • Expected value

    Actions

    • Inspect M→P and O→M gaps for dominant uncertainty and controllable actions.

    Output

    Uncertainty view

    Inspect M→P and O→M gaps for dominant uncertainty and controllable actions.

    Quality check

    Is the broad interval linked to a concrete driver?

    Pitfall

    The range remains without a learning step. Prioritise the costly uncertainty driver and assign evidence work.

    Timing: 5–10 minutes

  5. 5

    Use

    Planning range

    Goal

    Planning range: Use the estimate for a named decision and schedule review after scope or evidence changes.

    Inputs for this step

    • Uncertainty view

    Actions

    • Use the estimate for a named decision and schedule review after scope or evidence changes.

    Output

    Planning range

    Use the estimate for a named decision and schedule review after scope or evidence changes.

    Quality check

    Is it clear how value/range will be used and when to re-estimate?

    Pitfall

    E is added to a date without dependencies. Model calendar forecast separately with dependencies, capacity, and risk.

    Timing: 5–10 minutes

05

Artifact

What comes out at the end

Sketch: what the artifact looks like

Three-Point Estimation · O / M / POptimistischen, wahrscheinlichsten und pessimistischen Wert sichtbar machen, um Aufwand als Range statt Einzelzahl zu verstehen
Three-Point EstimationDas Visual zeigt optimistische, wahrscheinlichste und pessimistische Schätzung als Bandbreite mit Risk Range und Planungsannahme.Unsicherheit als Bandbreite statt als Einzelzahl schätzenOptimistisch, wahrscheinlich und pessimistisch machen Risiko sichtbar und liefern eine bessere Planungsannahme.SchätzobjektAufwand, Dauer oder Kosten klarabgrenzenrealistische BandbreiteO4 dOptimistischgünstig, aber plausibelM8 dMost Likelyhöchste WahrscheinlichkeitP16 dPessimistischungünstig, aber plausibelnicht als Zusage lesenExtremwerte erklärenRisk RangeBreite zeigt Unsicherheit und GesprächsbedarfPlanungsannahmeRange, Erwartungswert und Risikendokumentieren
Form

Three-point estimate with O/M/P scenarios, triangular expected value (O+M+P)/3, range, drivers, and review trigger.

Versioning / ownership

Record date, team, data state, and review date; preserve prior versions.

Tool alternatives
  • O/M/P scenario sheet
  • Historical analogies
  • Calculation and assumption log

three-point-estimation-working-template.md

Set subject, data, roles, flow, and review.

Three-Point Estimation: Worksheet

Question

To be confirmed

Desired outcome

To be confirmed

Scope

Complete run Time: 30–60 minutes per work-package group; evidence collection extra.

Complete this worksheet on paper or in your own document during the work.

Preparation for this scope

Method setup

  • Materials: Clear scope, historical analogies, O/M/P scenario sheet, calculation sheet, and assumption log
  • Roles: Work owner · delivery experts · data/risk expert · facilitator
  • Advance information: Close work package, unit, Done criterion, and dependencies; define O, M, and P as scenarios rather than target values.
  • Overall time needed: 30–60 minutes per work-package group; evidence collection extra.
  • Setup: Prepare a workspace with Scope · Scenarios · Calculate · Drivers · Use; separate example from live data.

Prepare for the work steps

Scope: Estimate frame

  • Close work package, unit, Done criterion, and dependencies; define O, M, and P as scenarios rather than target values.
  • Clear scope, historical analogies, O/M/P scenario sheet, calculation sheet, and assumption log

Scenarios: Three values

  • Estimate frame

Calculate: Expected value

  • Three values

Drivers: Uncertainty view

  • Expected value

Use: Planning range

  • Uncertainty view

Three-Point Estimation · working structure

Work packageO · optimisticM · most likelyP · pessimisticCalculationRangeDriverReview
Provider token
  • Provider token: Add evidence and rationale.

The blank worksheet contains prompts only.

Reference · original teaching example

Scope: Estimate frame

Expected artifact: Estimate frame

Define work, unit, Done, and included risks unambiguously.

Entry:

...

  • Do all three values describe the same completed work?

Scenarios: Three values

Expected artifact: Three values

Derive O, M, and P from concrete conditions and analogies; verify O ≤ M ≤ P.

Entry:

...

  • Are extremes plausibly reachable rather than perfect/worst imaginable?

Calculate: Expected value

Expected artifact: Expected value

Compute triangular expected value E=(O+M+P)/3 and preserve the range separately.

Entry:

...

  • Is the formula visible and calculated in one unit?

Drivers: Uncertainty view

Expected artifact: Uncertainty view

Inspect M→P and O→M gaps for dominant uncertainty and controllable actions.

Entry:

...

  • Is the broad interval linked to a concrete driver?

Use: Planning range

Expected artifact: Planning range

Use the estimate for a named decision and schedule review after scope or evidence changes.

Entry:

...

  • Is it clear how value/range will be used and when to re-estimate?

Open questions and next steps

...

Method guide: https://methodatlas.meierhoff-systems.de/en/methods/three-point-estimation/run-sheet

06

Example output

Concrete filled scenario, fictional example

Fictional example for orientation. Counts and timings describe this case and are not universal requirements.

three-point-estimation-beispiel.md

Concrete filled scenario, fictional example

Fictional teaching example: Three-Point Estimation · working structure

Work packageO · optimisticM · most likelyP · pessimisticCalculationRangeDriverReview
Provider token4 days · API fits7 days · normal adaptation16 days · migration + certification rework(4+7+16)/3 = 9 days4–16 daysMigration/certificationAfter trial import
07

Pitfalls

Recognize symptoms and steer against them

Quick overview, the full text is in the matching phase in the flow

  1. Estimate frameOptimistic estimates less scope than pessimistic.View in phase
  2. Three valuesP is doubled without naming a scenario.View in phase
  3. Expected valueExpected value 9 is treated as a certain commitment.View in phase
  4. Uncertainty viewThe range remains without a learning step.View in phase
  5. Planning rangeE is added to a date without dependencies.View in phase
08

Stop criteria

When to pause, resolve prerequisites, or choose another approach

Stop Scope: Do all three values describe the same completed work?
Stop Scenarios: Are extremes plausibly reachable rather than perfect/worst imaginable?
Stop Calculate: Is the formula visible and calculated in one unit?
Stop Drivers: Is the broad interval linked to a concrete driver?
Stop Use: Is it clear how value/range will be used and when to re-estimate?

Method after Praxisgemeinschaft. The method emerged as a widespread practice and is not clearly attributed to a single originator or organization. Curated with 1 sources.

Sources: Three-Point Estimation

Flow, timeboxes, and pitfalls are editorially curated practice recommendations based on the listed sources.

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