JTBD ODI: Outcome-Driven Innovation and the Opportunity Score

What is Outcome-Driven Innovation?

Outcome-Driven Innovation is the Jobs-to-be-Done variant that prioritizes improvements by calculation. Anthony Ulwick developed the approach in the early 2000s. It breaks down the job customers get done with a product into individual desired outcomes and collects two values for each outcome:

1. Importance: How important is this outcome to you?
2. Satisfaction: How satisfied are you with it today?

Together they produce the opportunity score. It shows where an outcome is important and at the same time poorly served — and therefore where an improvement has the greatest effect.

When does ODI fit — and when does it not?

ODI fits when it is settled that you will improve something, but not what comes first. Typical occasions are the next product generation, the roadmap of a portal, or choosing from a sales team's wish list.

ODI does not fit when

• you do not yet know which outcomes are relevant — then JTBD Story is the right place to start,
• you want to understand why someone bought, abandoned or switched — that is what JTBD Switch is built for,
• the question is the usability of an interface — that is the job of SUS and UEQ+.

How do you phrase desired outcomes?

As an outcome someone wants to achieve, without presupposing a solution. This is the hardest and most important part of the method.

Not like this (solution)	But like this (outcome)
Larger dust container	Empty the container without stirring up dust
Longer battery life	Finish without recharging
Quick-release filter	Clean the filter without taking the device apart

Three rules help:

• One outcome per statement. “Vacuum quickly and quietly” is two outcomes.
• From the user's point of view. Not what the product does, but what the person has achieved afterward.
• Solution-neutral. An outcome must be achievable in more than one way. If you write the solution into the question, you only measure agreement with that solution.

How is the opportunity score calculated?

Importance plus the gap between importance and satisfaction, with a negative gap counted as zero.

Opportunity score = importance + max(importance − satisfaction, 0)

Importance and satisfaction are both on a scale from 0 to 10. In Ulwick's approach, this is the share of respondents who choose the top two levels on a five-point scale, divided by ten. The score therefore ranges from 0 to 20.

Outcome	Importance	Satisfaction	Gap	Opportunity score
A	9.2	2.5	6.7	15.9
B	8.0	5.0	3.0	11.0
C	8.0	8.5	0 (instead of −0.5)	8.0

Outcome A is important and poorly solved — that is where the opportunity lies. Outcome C is just as important as B but already very well served: further investment there achieves little.

As a rule of thumb, scores above 15 count as severely underserved and scores below 10 as already well served. If satisfaction is higher than importance, an outcome is overserved.

Example: The loudest idea internally ends up in sixth place

In the Handheld vacuum case study (in German), there are nine improvement ideas for the next device generation, and the budget covers three. 412 buyers rate nine outcomes:

Rank	Outcome	Opportunity score	Assessment
1	Empty the container without stirring up dust	18.4	severely underserved
2	Clean the filter without taking the device apart	16.1	severely underserved
3	Vacuum under furniture without moving things	14.7	underserved
6	Finish without recharging (battery life)	8.9	already well solved

Longer battery life was the idea championed most loudly internally. Respondents consider it important — but are already satisfied. The bigger battery is put on hold, and with it about a third of the change budget. Dust-free emptying, ranked seventh of nine internally, becomes the first measure.

A second example from a B2B setting is the B2B customer portal case study (in German): 22 requests from sales, budget for four.

What are the limits of ODI?

• The list of outcomes decides everything. If an important outcome is missing, it does not appear in any ranking. If the list is guesswork, the score only looks more precise than it is.
• No causes. ODI shows where the gap is, not why. That takes an open question or a follow-up study.
• No switching behavior. ODI does not answer why someone buys or drops off.
• Effort per outcome. Each outcome costs two ratings. Long lists lengthen the questionnaire and reduce the care that goes into the responses.

How does JTBD ODI work in usabiq?

JTBD ODI is included in every plan, including Free Discovery, the free plan.

• Scored without a language model. The opportunity score is calculated according to the method, and underserved needs are flagged.
• Transparent intermediate values. Importance and satisfaction can be viewed individually for each outcome and — from Research Core — exported, not just the final result.
• Additional open questions are analyzed separately. For ODI, AI theme detection does not run on the outcomes; it runs only for JTBD Switch, JTBD Story and the free-form questionnaire.
• Segment comparison from Decision Pro: for example, the importance of an outcome by household type, with statistical confidence instead of colorful bars.
• Decision Engine from Decision Pro: the ranking becomes a prioritized list of problems, opportunities and quick wins.