Complete firstBounded subject
The scope and purpose of Lean Startup are stated as a concrete question.
Without scope, validated learning loop becomes arbitrary.
Method guideInnovation
Lean Startup
A practical method guide: clarify prerequisites and materials, understand the complete process, and look up outputs, pitfalls, and stop criteria.
ComplexityMedium
TimeWochen bis Monate je Lernzyklus
Participants2-8
FormatWorkshop + async
MaturityCanonical
01
Prerequisite
What needs to be finished first
Complete firstAccess to relevant perspectives
Vision and assumptions, target customer segment, innovation accounting metrics and domain decision makers are available.
Without these perspectives, central claims in validated learning loop remain unsupported.
02
Preparation
What needs to be ready before start
Materials
Vision and assumptions, target customer segment, innovation accounting metrics, shared workspace, source links, and decision log.
People / roles
Founder/Product · Research · Engineering · Analytics
Pre-read
Collect Vision and assumptions, target customer segment, innovation accounting metrics in advance and mark open assumptions.
Time needed
1–4 weeks per loop
Setup
Prepare Build-Measure-Learn loop with MVP, actionable metrics, and pivot/persevere decision visibly and calibrate assessment terms before starting.
03
Core question
The one question this method answers
What smallest experiment creates decision-ready learning about the riskiest assumption?
04
Flow
Phases with goal, actions, output and pitfall
Lean Startup states leap-of-faith assumptions, builds the smallest learning-capable MVP, measures behaviour against a baseline, and decides persevere, pivot, or stop.
validated learning loop
Fictional worked example
Build-Measure-Learn loop with MVP, actionable metrics, and pivot/persevere decision as a precise working structure with a fictional example.
Hypothesis
Hypothesis information to record
Teams zahlen 180 €/Monat für Auditexport.
MVP
MVP information to record
Concierge MVP mit fünf Teams.
Metric/threshold
Metric/threshold information to record
≥3/5 LOIs nach zwei Reviews; Ergebnis 1/5.
Pivot/persevere
Pivot/persevere information to record
Segmentproblem pivotieren.
The example demonstrates the domain logic of Lean Startup; worksheets remain blank.
- 1
Hypothesis
Hypothesis
Goal
Produce leap-of-faith assumption so the core question “What smallest experiment creates decision-ready learning about the riskiest assumption?” can be answered with stronger support.
Inputs for this step
- Vision and assumptions
- target customer segment
- innovation accounting metrics
Actions
- Name the value or growth hypothesis and riskiest assumption.
- Record source, rationale, and open uncertainty directly in leap-of-faith assumption.
Output
leap-of-faith assumption
leap-of-faith assumption · source · uncertainty · next decision
Quality check
Is the assumption observable?
Pitfall
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria. Set assumption, behaviour, threshold, and pivot option before building.
Timing: 10–20 minutes
- 2
Minimum viable product
Minimum viable product
Goal
Produce MVP so the core question “What smallest experiment creates decision-ready learning about the riskiest assumption?” can be answered with stronger support.
Inputs for this step
- leap-of-faith assumption
- target customer segment
- innovation accounting metrics
Actions
- Build the smallest offer that elicits real behaviour.
- Record source, rationale, and open uncertainty directly in MVP.
Output
MVP
MVP · source · uncertainty · next decision
Quality check
Does the MVP test the assumption directly?
Pitfall
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria. Set assumption, behaviour, threshold, and pivot option before building.
Timing: 10–20 minutes
- 3
Measure
Measure
Goal
Produce innovation accounting so the core question “What smallest experiment creates decision-ready learning about the riskiest assumption?” can be answered with stronger support.
Inputs for this step
- MVP
- target customer segment
- innovation accounting metrics
Actions
- Analyse baseline, cohort, and actionable metric.
- Record source, rationale, and open uncertainty directly in innovation accounting.
Output
innovation accounting
innovation accounting · source · uncertainty · next decision
Quality check
Was the threshold preset?
Pitfall
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria. Set assumption, behaviour, threshold, and pivot option before building.
Timing: 10–20 minutes
- 4
Decide
Decide
Goal
Produce learning decision so the core question “What smallest experiment creates decision-ready learning about the riskiest assumption?” can be answered with stronger support.
Inputs for this step
- innovation accounting
- target customer segment
- innovation accounting metrics
Actions
- Decide persevere, pivot, or stop with rationale.
- Record source, rationale, and open uncertainty directly in learning decision.
Output
learning decision
learning decision · source · uncertainty · next decision
Quality check
Does the decision follow behaviour?
Pitfall
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria. Set assumption, behaviour, threshold, and pivot option before building.
Timing: 10–20 minutes
05
Artifact
What comes out at the end
Sketch: what the artifact looks like
Form
Versioned validated learning loop with date, sources, owners, and next review.
Versioning / ownership
Retain date, source, assumption state, and decision for every version of validated learning loop.
Tool alternatives
- validated learning loop as board or document
- Source and evidence register
- Decision and action log
lean-startup-working-template.md
Plan Lean Startup around its domain steps and the concrete decision question.
Lean Startup: Worksheet
Question
To be confirmed
Desired outcome
To be confirmed
Scope
Full initiative Time: 1–4 weeks per loop
Complete this worksheet on paper or in your own document during the work.
Preparation for this scope
Method setup
- Materials: Vision and assumptions, target customer segment, innovation accounting metrics, shared workspace, source links, and decision log.
- Roles: Founder/Product · Research · Engineering · Analytics
- Advance information: Collect Vision and assumptions, target customer segment, innovation accounting metrics in advance and mark open assumptions.
- Overall time needed: 1–4 weeks per loop
- Setup: Prepare Build-Measure-Learn loop with MVP, actionable metrics, and pivot/persevere decision visibly and calibrate assessment terms before starting.
Prepare for the work steps
Hypothesis: Hypothesis
- Vision and assumptions
- target customer segment
- innovation accounting metrics
Minimum viable product: Minimum viable product
- leap-of-faith assumption
- target customer segment
- innovation accounting metrics
Measure: Measure
- MVP
- target customer segment
- innovation accounting metrics
Decide: Decide
- innovation accounting
- target customer segment
- innovation accounting metrics
validated learning loop
Hypothesis
Hypothesis information to record
...
MVP
MVP information to record
...
Metric/threshold
Metric/threshold information to record
...
Pivot/persevere
Pivot/persevere information to record
...
Enter only real input, sources, and decisions.
Hypothesis: Hypothesis
Expected artifact: leap-of-faith assumption
leap-of-faith assumption · source · uncertainty · next decision
Entry:
...
- Is the assumption observable?
Minimum viable product: Minimum viable product
Expected artifact: MVP
MVP · source · uncertainty · next decision
Entry:
...
- Does the MVP test the assumption directly?
Measure: Measure
Expected artifact: innovation accounting
innovation accounting · source · uncertainty · next decision
Entry:
...
- Was the threshold preset?
Decide: Decide
Expected artifact: learning decision
learning decision · source · uncertainty · next decision
Entry:
...
- Does the decision follow behaviour?
Open questions and next steps
...
Method guide: https://methodatlas.meierhoff-systems.de/en/methods/lean-startup/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.
lean-startup-beispiel.md
Concrete filled scenario, fictional example
Value hypothesis: regulated teams pay €180/month for audit export. Concierge MVP with five teams; preset success: at least three signed letters of intent after two real reviews. Result 1/5, so pivot the problem segment rather than expand features.
07
Pitfalls
Recognize symptoms and steer against them
Quick overview, the full text is in the matching phase in the flow
- HypothesisAn unfinished product counts as an MVP or vanity metrics replace preset learning criteria.View in phase
- Minimum viable productAn unfinished product counts as an MVP or vanity metrics replace preset learning criteria.View in phase
- MeasureAn unfinished product counts as an MVP or vanity metrics replace preset learning criteria.View in phase
- DecideAn unfinished product counts as an MVP or vanity metrics replace preset learning criteria.View in phase
Trap
Hypothesis
Symptom
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria.
What to do
Set assumption, behaviour, threshold, and pivot option before building.
Trap
Minimum viable product
Symptom
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria.
What to do
Set assumption, behaviour, threshold, and pivot option before building.
Trap
Measure
Symptom
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria.
What to do
Set assumption, behaviour, threshold, and pivot option before building.
Trap
Decide
Symptom
An unfinished product counts as an MVP or vanity metrics replace preset learning criteria.
What to do
Set assumption, behaviour, threshold, and pivot option before building.
08
Stop criteria
When to pause, resolve prerequisites, or choose another approach
validated learning loop answers the core question with traceable evidence or explicitly marked uncertainty.
Owners, next actions, and review dates are named for open points.
Finished the method guide?
Go to the profile for purpose, similar methods, and sources or continue to the next method in the catalog.