Complete firstJTBD
At least one documented Job statement for target users exists, from which outcomes can be derived.
Without: Without a JTBD foundation, the team assesses features instead of outcomes and Opportunity Scores become meaningless.
RunsheetProduct Discovery
Opportunity Scoring
ComplexityMedium
Time60-120 min
Participants3-6
FormatWorkshop + async
MaturityEstablished
01
Prerequisite
What needs to be finished first
Complete firstUser Interviews
At least 15 structured interviews or survey responses from target users are available for analysis.
Without: Without user data, importance and satisfaction values come from the team and reflect only internal assumptions.
02
Preparation
What needs to be ready before start
Materials
Outcome list in Minimize/Maximize format; survey tool or table with 1-5 scales for importance and satisfaction; Excel or Sheet template with Opportunity Score formula; notes on segmentation.
People / roles
One research lead owning outcome statements; one data analyst for score calculation and segmentation; 2-3 domain experts validating outcomes; sample of 30-100 target users for the survey.
Pre-read
JTBD statement; list of raw outcomes from interviews; existing roadmap for reflection; segments and relative size; familiarity with score calculation.
Time needed
60-120 min workshop, plus several days for data collection
Setup
Bring outcome statements in Minimize/Maximize format in advance, with one importance item and one satisfaction item per outcome (5-point scale). Define survey distribution channels and minimum sample per segment. Add Opportunity formula Importance + max(Importance minus Satisfaction, 0) in the sheet.
03
Core question
The one question this method answers
Which outcomes are important to target users and currently poorly satisfied, and where does genuine innovation potential exist?
04
Flow
Marker: Phase
| Step | Duration | Action | Hint |
|---|---|---|---|
1Phase 1: Clarify outcomes | 30 min | Check each outcome for format Minimize/Maximize + object + context. For example: Minimize time to review an invoice before sending. Remove duplicates or solution-coded outcomes. | If an outcome contains a solution (for example, use OCR), rephrase it. OCR is a solution, not an outcome. |
2Phase 2: Launch survey | 20 min setup, then 1-2 weeks field period | For each outcome two items: importance (1-5) and current satisfaction (1-5). Add demographics and a segment question. Aim for at least 30 responses per relevant segment. | Fewer than 30 responses per segment makes statistical interpretation weak. Reduce segment size instead of continuing with too small a sample. |
3Phase 3: Calculate scores | 30 min | Per outcome, score = Importance + max(Importance minus Satisfaction, 0). Score above 10 marks Innovation Opportunity, 12+ is overserved. | Aggregated scores across all segments often hide the core signal. Split by at least 2-3 segments. |
4Phase 4: Interpret and act | 40 min | List top outcomes per segment, prioritize underservedd ones (high score), mark overserved ones as removal candidates. Define concrete discovery action for each top opportunity. | Opportunity Score tells what, not how. Solution comes only in the next loop, otherwise categories blur. |
05
Artifact
What comes out at the end
Form
Opportunity landscape per segment with ranked outcomes, score, importance, satisfaction, and sample size. Plus an action list with discovery owner for top-3 outcomes per segment and a removal list for overserved outcomes.
Versioning / ownership
One dataset per collection cycle with date and sample size. Outcomes may be added, existing ones should not be reformulated silently. Keep score history visible so shifts over time are evident.
Tool alternatives
- Google Sheet with pivot tables by segment
- Typeform or Qualtrics for collection, plus Sheet for evaluation
- Strategyn tools for ODI workflow
- Notion or Airtable database with calculation column
opportunity-scoring-working-template.md
Compact working template for Opportunity Scoring with context, input, output artifacts, and next step.
Opportunity Scoring Working Matrix
| Element | Description | Rating | Evidence | Owner | Next step |
|---|---|---|---|---|---|
| 1 | |||||
| 2 | |||||
| 3 |
Output artifacts
- Opportunity score table:
- Top outcomes:
Decision or recommendation
What consequence follows from the matrix?
06
Example output
Concrete filled scenario, fictional example
opportunity-scoring-beispiel.md
Concrete filled scenario, fictional example
Opportunity Landscape — SMB Accounting Segment, n=84
| Outcome | Importance | Satisfaction | Score | Status |
|---|---|---|---|---|
| Minimize time to assign accounting documents | 4.7 | 2.1 | 7.3 | Underserved |
| Minimize error rate for VAT IDs | 4.5 | 2.4 | 6.6 | Underserved |
| Maximize visibility of open client requests | 4.2 | 3.2 | 5.2 | Medium |
| Minimize effort to prepare monthly close | 4.4 | 4.0 | 4.8 | Medium |
| Minimize clicks at login | 2.8 | 4.5 | 2.8 | Overserved |
Discovery actions: Outcome 1 → Anna runs five additional observation sessions by 28.05. Outcome 2 → Ben extends error audit in live data by 02.06. Removal list: remove click-reduction login outcome from roadmap.
07
Pitfalls
Recognize symptoms and steer against them
Trap
Outcome includes solution
Symptom
Items are scored that already include solutions such as OCR or mobile app usage.
What to do
Check each item for solution hints before scoring. Rewrite as Minimize/Maximize outcome without tool references.
Trap
Too small sample
Symptom
Segments have under 20 responses and score ordering changes with each new answer.
What to do
Aggregate segments into larger clusters or extend collection. Publish score only after minimum sample is reached.
Trap
Aggregate hides segments
Symptom
Averaging across all users makes outcomes appear medium for everyone and no clear opportunity stands out.
What to do
Split by segment, at least by persona or use-case type. Heterogeneous markets average themselves into noise.
Trap
Jump to solutions immediately
Symptom
Team discusses features instead of outcomes during the workshop.
What to do
Push solution discussion to a follow-up workshop. In the Opportunity session focus on what, not how.
Trap
Scale inflation
Symptom
Importance is above 4 in nearly all outcomes, limiting differentiation.
What to do
Use forced ranking or MaxDiff instead of Likert. Alternatively ask importance as pairwise choice.
Trap
Roadmap ignores overserved outcomes
Symptom
Team continues building outcomes with score < 10 because there was already investment.
What to do
Apply sunk-cost discipline: present overserved list explicitly in roadmap review and set prune or maintenance status.
08
Stop criteria
Done signals checkable in under a minute
No documented JTBD statement exists, outcomes cannot be derived.
No access to target users for the survey and scores would come only from the team.
Sample below 20 responses per segment, ordering is statistically unstable.
Outcomes are mostly solutions or feature statements, turning the method into feature prioritization.
Strategic roadmap decision is due next week and data collection time is insufficient.
Market is very new with no active users, so satisfaction cannot be assessed.
Finished the runsheet?
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