1. The evidence framework
Before a direction can be chosen, the evidence has to be sorted into five rows and rated honestly: problem validation, market timing, solution fit, team capability, resource match. Each row gets a color, the signals that earned it, and the signal that would change it. The framework does not decide. It makes the decision an argument about rows instead of about who is most confident.
- How do you evaluate the results of product discovery?
- What is an evidence framework for startup decision-making?
- How do you know if your startup idea is validated?
§The question: what does the actually say, row by row, before anyone says what to do about it?
§The from the sprint told you which assumptions held. It did not tell you whether the company should proceed, because that is a judgment across several kinds of evidence at once, and judgments across several things at once are where confident people win arguments they should lose. The framework in this chapter separates the judgment into five rows so that each can be argued on its own.
§ 1.1Five rows#
§Problem validation. Is the problem real, frequent, costly and felt by a segment you can name? The evidence is the problem definition document and the quotes behind it.
§Market timing. Is the world ready? Are the enabling technologies mature, is awareness growing, is competition still thin, is regulation a tailwind or a wall? The evidence is desk research and the experts.
§Solution fit. Did strangers understand it, want it, and commit to something? Is it clearly different from what exists? The evidence is the prototype sessions and the commitments.
§Team capability. Can the people you have build and sell this? Where is the gap: technical, domain, distribution? The evidence is uncomfortable and internal.
§Resource match. Does the first version fit the money, time and people available? Does the timeline fit the runway? The evidence is arithmetic.
§Marty Cagan's four risks, value, usability, and viability, sit inside these rows: the first three rows carry value and usability, the last two carry feasibility and viability. The rows are wider because a startup has two risks a product team inside a company does not: whether the timing is right and whether these particular people can do it.
§ 1.2Three colors, honestly#
§Each row gets one of three ratings. Strong positive: clear evidence supporting success. Mixed: unclear or conflicting evidence. Strong negative: clear evidence of a wall.
§The word that matters is honestly. Teams rate the rows they like green and the rows they fear yellow, and the framework only works if the reverse discipline is applied: rate the row you like least first, and require a quote or a number for every green.
| Row | Weak rating | Strong rating |
|---|---|---|
| Problem validation | "Everyone we talked to agreed it's a problem." | "Eight of ten described a specific recent event with a cost; two could not." |
| Market timing | "AI is hot right now." | "The model capability we need crossed the usable threshold in the last year; two funded competitors emerged in the last six months; no regulation applies." |
| Solution fit | "People loved the prototype." | "Five of six completed the core task unaided; three asked for a pilot; six of six failed the check-in." |
| Team capability | "We're a strong team." | "Strong technical and domain skills; nobody has sold to this buyer before." |
| Resource match | "We can make it work." | "First version needs roughly twice the current budget; timeline exceeds runway by a quarter." |
§The weak column is not wrong. It is unfalsifiable, and unfalsifiable ratings cannot be argued with, which is why teams prefer them.
§ 1.3The signals that move each row#
§For each row, write two lists before you rate it: what would make this strongly positive, and what would make it strongly negative.
§For problem validation, positive signals are consistent unprompted mentions, a clear financial or emotional cost, inadequate current solutions, and shown rather than stated. Negative signals are "nice to have," inconsistent descriptions of the problem across the segment, many existing solutions, low urgency.
§For market timing, positive signals are growing awareness, ready enablers, regulatory tailwinds, limited competition. Negative signals are a market that needs educating, technical barriers still standing, regulatory uncertainty, saturation.
§For solution fit, positive signals are enthusiastic behavior rather than words, clear differentiation, feasibility with the resources at hand, a value proposition that lands in thirty seconds. Negative signals are lukewarm response, a "me too" solution, resource gaps, advantages nobody can name.
§For team capability and resource match, the signals are plainer and harder to write down, because they are about you. Write them anyway. Rita McGrath's discovery-driven planning made the case thirty years ago: the assumption most likely to kill the plan is the one to state and test first, and for most small teams it sits in one of these two rows.
§ 1.4What the framework is for#
§It does not decide. A grid with three greens, one yellow and one red does not tell you whether to proceed; it tells you where the argument is. That is the whole value. Kahneman, Sibony and Sunstein's work on noise in judgment points to exactly this mechanism: break a complex judgment into independent components, assess each on its own evidence, and only then combine. The framework is decision hygiene for a team small enough that one loud opinion can otherwise carry the room.
§ 1.5What comes out#
§One page. Five rows, each with a color, the signals that earned it, and the signal that would change it. Written before the direction is discussed, by someone who was in the field, and read aloud at the start of the conversation that decides. The next chapter is that conversation.
Five rows, three colors, and the signal that would change each one. Rate the row you like least first.
- Marty Cagan, The Four Big Risks (2017). www.svpg.com/four-big-risks
- Rita McGrath and Ian MacMillan, Discovery-Driven Planning, Harvard Business Review (1995). hbr.org/1995/07/discovery-driven-planning
- Daniel Kahneman, Olivier Sibony and Cass Sunstein, Noise (2021), on structured judgment. www.penguinrandomhouse.com/books/626277/noise-by-daniel-kahneman-olivier-sibony-and-cass-r-sunstein