methodatlas
RunsheetProduct Discovery

Product Kata

ComplexityMedium
Time1-2 Wochen je Loop
Participants3-10
FormatWorkshop + async
MaturityEstablished
01

Prerequisite

What needs to be finished first

Complete firstNorth Star Metric

A North Star Metric or comparable outcome metric with established measurement is set, and Current and Target Condition orient to it.

Without: Without a measurement anchor, kata targets become wish values, and learning loops cannot be checked objectively.
02

Preparation

What needs to be ready before start

Materials

Kata board with four fields (Direction, Current Condition, Target Condition, Next Step); live measurement dashboard with outcome metric; experiment log; storyboard per iteration; coach or mentor (optional but recommended).

People / roles

One Product Lead or PM as owner; cross-functional team (PM, designer, engineer); one coach with kata experience; sponsor for direction setting and obstacle escalation.

Pre-read

Direction (vision or strategic goal); current measurement data; previous kata loops with learning effects; obstacle list; available experiment methods (interview, prototype, pretotype, data analysis).

Time needed

1-2 weeks per kata loop, ongoing

Setup

Kata board visible in team room or digital. Cadence: loop start Monday, mid-week sync, loop review Friday. Measurement dashboard visible. Experiment log continuous.

03

Core question

The one question this method answers

Which Target Condition does the team want to reach in 1-2 weeks, and which smallest next step moves us there or lets us see where the obstacle is?

04

Flow

Marker: Phase

StepDurationActionHint
1Phase 1: Clarify direction
Initial 1-2 h, then every quarterDirection in one sentence: where do we want to be in 6-12 months? Link to vision or product goal. Clarify what success in this direction looks like.Direction is not vision alone, but an operationalized line of flight. If direction becomes arbitrary, the kata loop swings between topics week by week.
2Phase 2: Measure Current Condition
30-45 minWhere are we today, measured? Outcome metrics plus relevant leading indicators. Data in numbers or observations. Do not guess; measure or name missing measurement as obstacle.Anyone filling Current Condition with gut feeling will guess Target Condition. Better write "we do not know" and plan measurement setup as Next Step.
3Phase 3: Target Condition for the loop
30-45 minWhich measurable change in Current Condition do we want to see in 1-2 weeks? Concrete number, clear behavior, not "better". Target Condition is a learning goal, not a delivery goal.Target Condition too large: loop fails, no learning. Too small: loop is useless. Rule of thumb: ambitious enough that current knowledge is not sufficient.
4Phase 4: Plan and execute Next Step
Plan 30 min, execution days to 1 weekSmallest experiment that creates learning: interview, spike, prototype, data analysis, A/B test. Before start: what do we expect, what would surprise us, how would we recognize obstacles.Anyone starting Next Step without an expectation statement will not know afterward whether they learned. Writing expectation is mandatory.
5Phase 5: Reflection and next loop
1 h at loop endWhat did we learn? Was Target Condition reached? Which obstacle became visible? Derive new Current Condition and new Target Condition from it. Next loop starts.Reflection without addressing the obstacle is bookkeeping. The obstacle must become visible, named and addressed in the next loop, otherwise the team learns nothing.
05

Artifact

What comes out at the end

Form

Kata board with current Direction, Current Condition, Target Condition, Next Step and expectation; experiment log with hypothesis, result, obstacle; loop history as chronological list for coaching.

Versioning / ownership

One entry per loop with date, loop number, kata-board snapshot and reflection. Loops archived chronologically. Quarterly learning synthesis.

Tool alternatives
  • Whiteboard with four quadrants plus photo export
  • Miro or FigJam with kata template
  • Notion page with reusable template per loop
  • Linear or Jira with custom issue type Kata Loop

product-kata-working-template.md

Compact working template for Product Kata with context, input, output artifacts, and next step.

Product Kata Working Template

Goal

Iterative learning cycle from Direction, Current Condition, Target Condition, and Next Step.

Context

When and for what do we use this method?

Input

Which data, observations, decisions, or materials are available?

Execution

Short notes along the runsheet.

Output artifacts

  • Direction:
  • Current Metric:
  • Target Metric:
  • Experiment note:
  • Learning report:

Assumptions and open questions

  • ...

Decision / next step

Owner, date, and success signal.

06

Example output

Concrete filled scenario, fictional example

product-kata-beispiel.md

Concrete filled scenario, fictional example

Product Kata Loop #14 - Activation Team (2026-05-12 to 2026-05-23)

Direction: By Q4 2026, 50% of first installers reach the aha moment in week 1.

Current Condition (2026-05-12):

  • Activation rate week 1 = 27%.
  • Step-3 drop-off in onboarding at 41%.
  • User quotes: "I do not know what to enter here." (n=6 in tests).

Target Condition (target 2026-05-23):

  • Activation rate week 1 >= 32%.
  • Step-3 drop-off <= 25%.

Next Step (experiment): Wizard layout for step 3 as A/B test with 50% traffic from 2026-05-14.

Expectation: 50% reduction in step-3 drop-off, +4 points activation rate. It would surprise us if drop-off increases in the wizard variant.

Reflection (2026-05-23):

  • Step-3 drop-off = 22% in wizard variant (expectation exceeded).
  • Activation rate week 1 = 31% (slightly below target, but +4pp).
  • Obstacle visible: step 5 (DATEV connection) now has 18% drop-off, previously 9%. Wizard shifts the problem backward.

Next Current Condition (Loop 15):

  • Activation rate week 1 = 31%.
  • Step-5 drop-off = 18% (new main problem).

Next Target Condition: Step-5 drop-off < 10%. Next Step: interviews with users who drop at step 5.

07

Pitfalls

Recognize symptoms and steer against them

Trap

Direction changes every loop

Symptom

Loop 1 targets activation, Loop 2 retention, Loop 3 pricing. No continuous learning thread.

What to do

Set and protect direction quarterly. Within the quarter, only sub-targets change; direction remains. Anyone changing mid-quarter learns nothing cumulatively.

Trap

Current Condition estimated

Symptom

Current values are assumptions, not data. Target becomes arbitrary.

What to do

Use measurement setup as first kata loop if data is missing. Until then, honestly label the loop as measurement setup, not as outcome loop.

Trap

Target too large

Symptom

Target demands a doubling in one week, team fails and is demotivated.

What to do

Target at the edge of reachability, not beyond. Rule of thumb: existing knowledge is just not enough. Coach can help calibrate.

Trap

Next Step is delivery sprint

Symptom

Next Step is "build feature X", takes 3 weeks, no learning along the way.

What to do

Next Step is experiment, not implementation. Maximum duration 1 week. If longer, find a smaller experiment that gives insight faster.

Trap

Reflection without obstacle addressing

Symptom

Loop reflection summarizes what happened, but next Current Condition is identical.

What to do

Obstacle must flow into next Target Condition or Next Step. If obstacle is not addressed, what are the next 1-2 weeks for?

Trap

Coach missing

Symptom

Team runs loops, quality remains low, targets become feature lists.

What to do

Plan coach (internal or external) for first 10-20 loops. Coach checks questions, not answers. Without coaching, kata quickly becomes a standup variant.

08

Stop criteria

Done signals checkable in under a minute

No direction can be set stably for at least one quarter.
No measurable outcome metric is established; Current and Target cannot be quantified.
Team is output-driven (fixed feature list), hypothesis work is not allowed.
Loops cannot be completed in 1-2 weeks (delivery cycles too long).
Coach unavailable and no team member has kata experience.
Sponsor expects fixed roadmap instead of learning loops.

Finished the runsheet?

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