# Quality Standards

**Purpose**: Define minimum acceptable quality for cycle outputs.

Quality standards exist to help teams move faster with less rework. They are not there to make the process heavier. They are there to stop weak work from quietly creating downstream confusion.

## Assumption quality

* Specific, not vague.
* Directly tied to value, behavior, or feasibility.
* Prioritized by risk and impact.

Good assumption quality means the team can point to one meaningful uncertainty and explain why it matters now.

## Hypothesis quality

* Testable in a finite period.
* Contains measurable expected outcome.
* Linked to one core assumption.

A strong hypothesis makes it obvious what the team expects to observe if the assumption appears true.

## Experiment quality

* Clear method and success criteria.
* Feasible within team constraints.
* Produces interpretable evidence.

An experiment is high quality when it helps the team decide something. If it only produces interesting information without affecting confidence or action, it is probably weaker than it looks.

## Learning quality

* Derived from evidence, not interpretation alone.
* Includes confidence and uncertainty.
* Clearly states what changed in team understanding.

Good learnings are humble and useful. They do not overclaim. They help the team understand what shifted, how strongly, and what still remains unclear.

## Insight quality

* Synthesizes multiple learnings where relevant.
* Includes decision implications.
* Supports a specific next action.

A strong insight helps the team move from “Here is what happened” to “Here is what this means.”

## Why these quality bars matter

Low-quality work often feels fine in the moment. The problem shows up later:

* vague assumptions create messy tests,
* messy tests create weak learnings,
* weak learnings create hesitant decisions,
* hesitant decisions slow the whole system down.

That is why quality should be checked early, not just at the end.

## Weak vs strong pattern

| Stage      | Weak pattern            | Strong pattern                         |
| ---------- | ----------------------- | -------------------------------------- |
| Assumption | Broad and hard to test  | Specific, risky, and worth testing now |
| Hypothesis | Hard to measure         | Measurable and time-bounded            |
| Experiment | Busy but unclear        | Explicitly tied to a decision          |
| Learning   | Sounds like an opinion  | Evidence-backed and confidence-tagged  |
| Insight    | Interesting but passive | Makes the next move clearer            |

## Practical use

Use these standards during the cycle, not after it. The best time to improve quality is before weak work compounds into a slower decision cycle.

## Next step

Read [Common Failure Patterns](https://playbook.swiftracks.com/fundamentals/common-failure-patterns).