Comparing by fit
Two ways of thinking, side by side. There is no winner here — read across each row and choose the one that fits your situation.
Innovation
Understand the person, frame the real problem, build something rough, and learn from their reaction.
By 6days
Innovation
Not all features are equal: some delight, some merely satisfy, and some only hurt when missing.
By 6days
When to use — Design Thinking
Use it on ill-defined problems where the need is genuinely unclear, where the people affected are not you, and where the cost of building the wrong thing is high. It is strongest early, when the framing is still open and cheap to change.
When to use — Kano Model
Use it when a roadmap needs to balance table-stakes against differentiation, when entering an established category where expectations are already set, or when heavy feature investment is somehow producing no measurable satisfaction gain.
When not to use — Design Thinking
Avoid it when the problem is well-specified and the answer is known — it is expensive ceremony for work that needs execution. It struggles with problems whose constraints are technical or regulatory rather than human. And it is the most ritualised framework in common use: workshops, sticky notes and a five-stage poster routinely produce the appearance of the method with none of the substance, because nobody left the building to observe anyone.
When not to use — Kano Model
Avoid it in a genuinely new category, where customers have no expectations to classify against and the survey returns noise. It is survey-based, so it inherits every weakness of stated preference — people are poor predictors of their own delight. It is also expensive to run properly and stale quickly; a three-year-old Kano study is a historical document.
Organisations solve the problem they were handed. A brief arrives already containing its solution — 'build a dashboard' — and a team spends six months building it well, only to find nobody uses it, because the actual difficulty was never a lack of a dashboard. The expensive error was committed before any work began, in accepting a framing nobody tested against a real person.
Teams treat features as a single list ranked by how much customers say they want them. But customer satisfaction does not respond linearly to features. Some things generate no goodwill when present and fury when absent. Some delight now and will be unremarkable in two years. Ranking everything on a single 'wanted' axis guarantees you will over-invest in things that cannot make anyone happy and under-invest in the ones that can.
Design thinking is a loop for problems where the requirement is not yet known: understand the people affected, define the problem from what you learned rather than from the brief, generate many candidate solutions before judging any, build a rough artefact, and put it in front of someone. The sequencing carries the value. Defining after observing prevents you from solving the wrong problem, and prototyping before committing makes being wrong cheap. It is not linear — findings at the test stage routinely send you back to redefine — and treating it as a five-step process to march through is the most common way to get nothing from it.
The Kano model sorts features by how their presence and absence affect satisfaction, producing distinct categories rather than one ranking. Must-be features are invisible when present and damaging when missing — nobody praises an aircraft for landing. Performance features scale: more is better, roughly linearly. Attractive features delight when present but are not missed when absent, because customers never expected them. Indifferent features move nothing. The model's sharpest insight is temporal: today's delighter becomes tomorrow's expectation, so categories decay and must be re-measured.
Watch and talk to the people who live with the problem, where they actually encounter it. Watch what they do rather than trusting what they say; the workarounds they have stopped noticing are where the real problem is visible.
Write a problem statement grounded in what you observed, not in the brief you were handed. If your definition is identical to the original brief, you have almost certainly skipped the observing.
Produce many candidate directions with evaluation explicitly suspended. The first plausible idea is a local optimum and will kill the search if allowed to. Quantity first, judgement second, deliberately separated.
Build the crudest thing that could elicit a real reaction — paper, a clickable sketch, a manual process behind a form. Fidelity is not a virtue here; it is a liability, because polish makes people admire the artefact and makes you reluctant to discard it.
An ordered process with 5 phases.
Observe the people in their situation.
Frame the real problem from what you saw.
Generate many options before judging any.
Worked example — Design Thinking
A hospital is asked to reduce missed outpatient appointments and briefs a team to build an SMS reminder system. Observation first: patients who miss appointments overwhelmingly received the letter and remembered the date. The barriers are transport, unpredictable shift work, and a booking line answered only during working hours — the hours they are at work. The problem is redefined from 'patients forget' to 'patients cannot attend or rearrange within the constraints of their lives.' Prototypes: a text-back rescheduling line, evening slots, a standby list. The reminder system, which was the entire original brief, addresses a cause that barely exists.
Worked example — Kano Model
A hotel books group evaluates features. Hot water and a clean room: must-be — no guest has ever left a five-star review for functioning plumbing, and every guest leaves a one-star review for its absence. Wi-Fi speed: performance, and now the primary driver of business-traveller ratings. A handwritten note from the manager: attractive, delights disproportionately, costs almost nothing, and nobody misses it if it is absent. Same-day laundry: indifferent for this segment. The finding that changes behaviour is that Wi-Fi has migrated from attractive to performance in under a decade and is drifting toward must-be — the investment case for it is not about delight any more, it is about avoiding damage.
The approach draws on design practice and cognitive research going back to the 1960s, with roots in work on the nature of design problems by figures such as Herbert Simon and Horst Rittel. Its current business form was shaped substantially by the firm IDEO and by the Stanford d.school from the 1990s onward. The five-stage articulation is one popular formulation among several, not a canonical definition.
The model was developed by Noriaki Kano and colleagues at the Tokyo University of Science around 1980, within the Japanese quality management tradition that also produced much of modern quality function deployment. Its academic origin gives it an unusually explicit methodology — the paired question format and classification table are part of the original work rather than later additions.
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Put it in front of someone from the affected group and watch them struggle without helping them. Most tests send you back to define rather than forward to build, and that is the loop working rather than failing.
List the features to evaluate in customer-meaningful terms. If a customer cannot tell whether they have it, it cannot be classified — internal work does not belong in this exercise.
For every feature ask two questions: how would you feel if it were present, and how would you feel if it were absent? The pair is the entire mechanism. Asking only the first turns the survey into a wish list, which is the thing you are trying to escape.
Map each respondent's pair to a category. 'Like it if present, expect it if absent' is attractive; 'expect it if present, dislike if absent' is must-be; 'like if present, dislike if absent' is performance. Contradictory answers usually mean the question was ambiguous rather than the customer confused.
Look at the distribution rather than the average, and split by customer type. A feature that is must-be for enterprise buyers and indifferent to individuals will average to 'performance' — a category that describes nobody and misleads everyone.
Cover every must-be adequately before investing anywhere else — they are hygiene and no amount of delight offsets a missing one. Then compete on selected performance features and invest in a small number of attractive ones. Re-run periodically, because the categories will have moved.
Build the crudest thing that can be wrong.
Put it in front of real people and learn.
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