Signifier

Module 01

The cost of a bad assumption

Identify the riskiest assumption in a brief, and design the cheapest test that could prove it wrong.

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Check yourself · 6 questions · pass at 70%

  1. 01

    Someone in a meeting states confidently that most users are on mobile. No one has checked analytics. What is this?

  2. 02

    Why does the same wrong assumption cost different amounts?

  3. 03

    Which assumptions should you spend your testing budget on?

  4. 04

    You're designing a two-sided marketplace. Which is most likely the riskiest assumption?

  5. 05

    What makes a good test of a risky assumption?

  6. 06

    What's the problem with framing research as 'validation'?

Revision · 8 cards

These come back on a schedule, spaced to catch you just before you’d forget.

Fact vs assumption

A fact is something someone checked. An assumption is something someone said confidently.

What determines the cost of a wrong assumption?

When you find out — not how wrong you were. Conversation → days → the whole build.

The two axes for ranking assumptions

How confident are we, and how bad if we're wrong. Test low-confidence, high-consequence.

Which assumptions do teams test by default?

High confidence, low consequence — comfortable precisely because nothing rests on the answer.

The riskiest assumption

The one holding up all the others. If it's wrong, nothing downstream survives.

The question that does the most work

What is the cheapest thing that could prove this wrong?

Why avoid the word 'validation'?

It sets the goal as being right. Aim for disconfirmation: what would make me abandon this?

Examples of cheap disproof

Five phone calls, a fake door test, or asking the support team — who usually already know.

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