Opportunity Scoring

Discovery

Prioritization

Strategy

Identify poorly met customer needs with a simple formula. Anthony Ulwick's method to prioritize by the gap between importance and satisfaction.

Description

Opportunity Scoring is a quantitative prioritization method created by Anthony Ulwick (Strategyn, 2002) within the Outcome-Driven Innovation (ODI) framework, which identifies the most promising product opportunities by measuring the gap between how important a need is to the customer and their current level of satisfaction. Its purpose: to replace intuition with a measurable customer signal to decide where to invest. The formula is straightforward: Score = Importance + max(Importance - Satisfaction, 0). Each customer need is rated on two scales from 1 to 10. A need rated 9 in importance and 3 in satisfaction produces a score of 15 (9 + 6). A need rated 9 in importance and 9 in satisfaction produces a score of 9 (9 + 0). The first is a gold mine; the second is already well served. Ulwick put it this way in What Customers Want (2005): "Opportunities exist where important outcomes are underserved." Opportunity Scoring works like a metal detector on a beach: it does not tell you what is buried, but it signals precisely where to dig. A score above 15 indicates a major opportunity, between 12 and 15 a solid opportunity, between 10 and 12 a neutral zone, and below 10 a need that is already satisfied or not very important. This method differs from the Kano model (which classifies needs by type) and from RICE scoring (which evaluates internal initiatives): Opportunity Scoring starts exclusively from the voice of the customer, not from the team's opinion. Bosch applied it to its circular saw range by identifying 14 customer outcomes, which led to a product that captured over 30% of the market at launch.

Objectives

Explore opportunities
Understand users
Foster innovation

Used by

-Bosch (applied Opportunity Scoring to its circular saw range, identifying 14 key customer outcomes that led to a product capturing over 30% market share)

Advantages

Prioritization anchored in the voice of the customer, not internal opinion. Roadmap debates shift from "I think that" to "the data shows that".
Simple and reproducible formula. A junior PM can calculate scores in an hour with a spreadsheet, without specialized tools.
Identifies invisible opportunities. Important but poorly satisfied needs don't show up in support tickets, they hide in the silence of customers who leave.
Compatible with any downstream prioritization framework. Opportunity scores naturally feed into a RICE, MoSCoW or OKR roadmap.

Limitations

Requires a sufficient customer sample. With fewer than 50 respondents, averages are unstable and conclusions fragile.
Outcome quality determines result quality. Poorly formulated outcomes (too vague, too technical) produce unusable scores.
Does not capture latent needs. Opportunity Scoring measures what customers can express, not what they don't yet know they want. For breakthrough innovation, complement with the Kano model.
Non-negligible research cost. Data collection and analysis require time and sometimes an external panel budget.

How to apply Opportunity Scoring

1
Identify customer outcomes (job outcomes)
List the results your customers seek to achieve when using your product or a competing solution. Formulate them as "verb + object + context": "Reduce initial configuration time," "Minimize data entry errors during import." Aim for 10 to 20 outcomes per segment. Output: list of outcomes formulated in ODI format.
2
Build the importance/satisfaction questionnaire
For each outcome, prepare two questions: "How important is [outcome] to you?" and "How satisfied are you with [outcome] using the current solution?". Use a scale of 1 to 10. Keep the questionnaire under 25 outcomes to avoid respondent fatigue. Output: questionnaire ready to send.
3
Collect data from a representative sample
Target 50 to 200 respondents per customer segment. Favor a diverse panel (large clients, small clients, long-standing, new). If you do not have the budget for an external panel, use your existing customer base with a simple incentive. Output: raw importance/satisfaction data per outcome.
4
Calculate the opportunity score for each outcome
Apply the formula: Score = Importance + max(Importance - Satisfaction, 0). Calculate the average for each outcome across all respondents. Sort by descending score. Output: ranked table of opportunity scores.
5
Map the results on an importance vs. satisfaction chart
Place each outcome on a chart with importance on the x-axis and satisfaction on the y-axis. Draw the diagonal: outcomes above the diagonal are over-served (over-investment), those below are under-served (opportunities). Output: visual map of opportunities.
6
Segment opportunities by score threshold
Classify outcomes into four zones. Above 15: major opportunities, priority investment. Between 12 and 15: solid opportunities, to be planned. Between 10 and 12: neutral zone, to monitor. Below 10: satisfied needs, no action required. Output: outcome segmentation by priority.
7
Validate opportunities with qualitative data
A high score is not enough. Conduct 5 to 10 customer interviews on the top-scored outcomes to understand the context, current workarounds, and willingness-to-pay. An outcome may be underserved because no solution exists, or because existing solutions are mediocre. The nuance changes the strategy. Output: qualitative insights per priority opportunity.
8
Feed the product roadmap with priority outcomes
Transform the 3 to 5 top-scored outcomes into concrete product initiatives. Each initiative must target a specific outcome with a measurable KR tied to customer satisfaction. Revisit scores every 6 to 12 months to detect changes. Output: product initiatives linked to quantified customer outcomes.