methodatlas
RunsheetProduct Strategy

DIBB

ComplexityLow
Time1-2 h
Participants2-8
FormatWorkshop + async
MaturityEstablished
01

Prerequisite

What needs to be finished first

The decision is clearly defined, with alternatives and stakeholders, and data access is available.

Without: Without a clean decision frame, DIBB becomes a mixed collection of preferences; Beliefs and Bets lose their connection.
02

Preparation

What needs to be ready before start

Materials

DIBB template with four sections (Data, Insight, Belief, Bet); source directory for data; stakeholder review plan; versioning system (Git or Notion); success measurement setup.

People / roles

One owner (strategy lead, PM, or departmental head) as author; one to three reviewers from neighboring areas; sponsor with decision mandate; data owner for fact check.

Pre-read

Decision question in one sentence; available data and sources; known assumptions from previous decisions; Bet time horizon; success metric for the Bet (what shows success at 6, 12, or 24 months).

Time needed

1-2 hours for first draft, plus reviews

Setup

Create the DIBB template. Prepare source section for data. Schedule review slot in calendar. Activate versioning tool. Definition of done: sponsor signs Bet.

03

Core question

The one question this method answers

On what basis, and with which Beliefs and Insights from which data, does the team take which Bet (decision)?

04

Flow

Marker: Sektion

StepDurationActionHint
1Section 1: Data
30-45 minCollect hard data, facts, and observations. For each data point define source (dashboard, study, interview quote, market report). Add collection date and context. No interpretation in this section.Interpreting in Data mixes layers. Data should be numbers, quotes, facts. Interpretation belongs in Insight. If merged, it is unclear later what is evidence and what is interpretation.
2Section 2: Insight
30-45 minDerive key findings from data. Insight links multiple data points into one picture. Keep to 3-5 insights; more dilutes the result. Reference underlying data for each insight.An insight tied to only one data point is often just a restatement. Real insight combines at least two data points into a statement.
3Section 3: Belief
30-45 minBelief is a derived conviction from Insights. A Belief is a position: "We believe that ...", often with implicit assumptions. Make assumptions explicit. Reference Insights for each Belief.Beliefs without explicit assumptions become untestable later. If "the market keeps growing" is hidden as an assumption, that belief cannot be updated when the trend changes.
4Section 4: Bet
30-45 minDefine what we do, what we do not do, what we invest in, and over which time horizon. Define Bet success measurement (which metric and when shows success). Name explicit exclusion options.A Bet without success measurement is hope. Each Bet needs at least one metric and one horizon. A Bet without non-action options is wishful thinking.
5Section 5: Review and signature
30-60 minRun reviewer round with written comments. Owner revises where needed. Sponsor signs Bet in writing. Record date, version, and review date (for example 6 months).Reviews often reveal where data is weak or Beliefs are vague. Substantive critique triggers revisions, not polish. Sponsor signature creates commitment, not ceremony.
6Section 6: Learning and updates
Quarterly, 1 hQuarterly review: which Beliefs are challenged by new data? For each Belief set status: confirmed, weak, disproven. If disproven, adapt or reconfirm Bet with new rationale.Teams that never review Beliefs keep Bets alive artificially. Visible update of Beliefs protects against sunk-cost bias.
05

Artifact

What comes out at the end

Form

DIBB document with four sections, data source directory, assumptions list per Belief, Bet with success metrics and horizon, reviewer comments, sponsor signature, and versioning. Quarterly update log.

Versioning / ownership

Use SemVer per DIBB document. Major version for Bet changes, minor for Belief updates, patch for data refresh. Archive prior versions with diff view. New Bet reversal creates a new DIBB with a reference.

Tool alternatives
  • Notion or Confluence page in Strategy space
  • Google Docs in Suggesting mode for reviews
  • Markdown in repo under docs/decisions/dibb/
  • Coda doc linked to data sources

dibb-working-template.md

Compact working template for DIBB with context, input, output artifacts, and next step.

DIBB Working Template

Goal

Spotify framework: Data, Insight, Belief, Bet, to structure decisions in a traceable way.

Context

When and for what do we use this method?

Input

Which data, observations, decisions, or materials are available?

Execution

Short notes along the runsheet.

Output artifacts

  • DIBB document:
  • Beliefs list:
  • Bets list:
  • Learning report:

Assumptions and open questions

  • ...

Decision / next step

Owner, date, and success signal.

06

Example output

Concrete filled scenario, fictional example

dibb-beispiel.md

Concrete filled scenario, fictional example

DIBB — Austria market entry for Clarity-App (v0.4, 18.05.2026)

Data

  • 380k solo entrepreneurs in Austria (Statistics Austria 2024).
  • 18 of 22 solo entrepreneurs in Austria already pay for tools like DATEV-Anwender (own interviews, 03-04/2026).
  • Competitor "BalanceBuch" has 12% market share among solo entrepreneurs in Austria (market report Stockl 2025).
  • Customer Acquisition Cost in Germany: 14 EUR (own data Q1-2026).
  • LinkedIn ad test in Austria (300 EUR budget): 28% conversion versus 30% in Germany.

Insight

  • I1: Austrian market is large enough (380k solo entrepreneurs) and is paying materially (18/22 interviews). Competitive landscape is less consolidated than in Germany.
  • I2: Channels respond similarly to Germany (conversion -2 pp). CAC should be comparable.
  • I3: BalanceBuch is present in SMB segment, but underrepresented in solo segment (only 12%).

Belief

  • B1: We can acquire 2k paying solo customers in Austria within 18 months if we execute local adaptations (FinanceOnline integration, tax rates, German UI with Austrian specifics).
  • B2: Market entry adds LTV without material CAC increase because marketing channels and learning are transferable.
  • Assumptions: (a) FinanceOnline API integration is feasible in 3 months. (b) Language and tax logic are the main adaptations; no full rebrand needed. (c) Austrian competition remains stable for 18 months.

Bet

We invest 180k EUR over 6 months for Austrian market entry: local UI adaptation, FinanceOnline integration, performance marketing in Austria.

  • Trade-off: Austrian launch delays Swiss launch to 2027.
  • Success measurement: 500 paying Austrian customers by 30.11.2026, 2k by 30.11.2027. AT CAC comparable (14-18 EUR).
  • Sponsor: @julia (CEO), signed on 18.05.2026.
  • Review: Q3 2026 on 30.09.2026.

Belief status Q3 (future): Test B1 against customer acquisition rate and B2 against CAC comparison.

07

Pitfalls

Recognize symptoms and steer against them

Trap

Data and Insights mixed

Symptom

Data section contains interpretations, Insight section adds new data points.

What to do

Keep sections strictly separate. Data is only facts and sources. Insight combines multiple data points. Reviewers validate separation.

Trap

Beliefs without assumptions

Symptom

Belief reads as a closed statement, assumptions are not explicit and are later disconfirmed.

What to do

List assumptions explicitly under each Belief. Review quarterly. A belief without assumptions is not review-ready.

Trap

Bet without trade-off

Symptom

Everything is done, no trade-offs are visible, resource clarity is missing.

What to do

Name explicitly what is not done for each Bet (market, feature, initiative). Trade-offs force clarity.

Trap

Missing success measure

Symptom

Bet is clear but no one can state what success is measured against.

What to do

Metric and horizon are mandatory. If no metric can be found, the Bet is not thought through. Use leading indicators if necessary.

Trap

No reviews

Symptom

DIBB document is created once and never reviewed; Beliefs stay unchanged for six quarters.

What to do

Make quarterly review mandatory in calendar. Set explicit Belief status (confirmed/weak/disproven). Update Bet when a belief is disproved.

Trap

Smoothing reviews

Symptom

Reviewer comments are only cosmetically applied, and substantive criticism is not addressed.

What to do

Add a written response for each reviewer comment: accepted, rejected with reason, or parked. Smoothing is method misuse.

08

Stop criteria

Done signals checkable in under a minute

No data available, DIBB would start from pure Beliefs.
Sponsor refuses to place a Bet or does not accept quarterly review.
Decision is operational and does not need versioned rationale.
Less than 1 hour is available; all sections cannot be filled.
Beliefs are not testable (no metric, no horizon), learning loop is impossible.
Bet is already made; DIBB would be post-hoc justification rather than a decision tool.

Finished the runsheet?

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