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How to preserve institutional knowledge in your experimentation programme
When someone leaves, the programme shouldn’t. Here’s how to keep research, decisions, and learnings in the system.
Institutional knowledge in experimentation is: what you tested, why, what you decided, what you learned, and what you did next. When that lives in spreadsheets, Slack, and people’s heads, it leaves with them. You retest. You repeat mistakes. You can’t answer “what has this programme delivered?” Here’s how to fix it.
1. Make iteration chains first-class
Link experiments: what you tried, what you learned, and what you did next. When that’s in the product (not in a deck or a tab), it stays. New joiners see the lineage. When someone suggests a test, you can see if it’s already in the chain. How we do it in Experiment OS.
2. Keep a research library and link it
Surveys, heatmaps, interviews in one place, with links to the hypotheses they support. Evidence URLs, not “see the July deck.” When someone asks why you ran a test, the research is attached. When they leave, it’s still there.
3. Document decisions, not just results
Ship, iterate, stop, or investigate, and write why. Rationale and learnings live with the experiment. Future you and new joiners get the “why,” not just the outcome. That’s what turns a log into institutional knowledge.
4. One system, not five
The more scattered the workflow (research here, hypotheses there, decisions in Slack), the more is lost. One place for the lifecycle (research, hypotheses, experiments, and decisions) makes it possible to search, link, and retain. How Experiment OS structures it.
Preserve your programme
Iteration chains, research library, decision docs. See the solution.
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