Potential outcomes
Definition
Potential outcomes is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.
What Potential outcomes captures
Potential outcomes is a statistical or measurement concept used to describe, compare, or interpret engineering data. In practice, the useful question is what the value represents, which observations contribute to it, and what alternative explanations remain. Write down the unit, inclusion rule, and aggregation before comparing results.
An engineering example
A company studies whether a workflow change affects review time. The potential outcomes helps define the causal question or comparison, while the team records assignment, timing, exposure, and the assumptions needed to interpret the contrast.
Limits and interpretation
Causal interpretation requires a credible assignment or comparison design; a named method cannot replace its assumptions. Spillover, selection, measurement error, and changing conditions may change the estimand.
Use the result responsibly
Pair this concept with the underlying observations, sample count, comparison condition, and uncertainty. Preserve the query or calculation version when the result informs a release, staffing, reliability, or AI adoption decision. If the definition changes, mark the boundary so a trend is not confused with a measurement change.
How this relates to Weave
In Weave, potential outcomes can help frame analysis of engineering activity, delivery outcomes, or AI-assisted work in context. Use it to inspect relevant events, cohorts, and time windows rather than reading a summary in isolation. Weave can connect work signals, but it does not by itself establish causality, repair incomplete instrumentation, or guarantee that a metric represents business value.
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