Skills Data Science Compare Process Cohorts

Compare Process Cohorts

v20261008
compare-cohorts
This skill enables comparing process cohorts, departments, or time periods using matched definitions. It involves fixing outcome definitions, metrics, and aggregations while freezing baselines. Users should use specific API calls to retrieve metrics and statistics for matched pairs, ensuring reproducibility and avoiding data leakage between exploratory and baseline filters. It supports analyzing before-and-after results with strict time window controls.
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Overview

Matched cohort comparisons

Use the shared contract and
filters/units.
Fix the outcome definition/provenance, metric, aggregation, units, timezone and one selector S.
Freeze the user's agreed baseline F, separately from current exploratory filters.
Reuse metadata versions and exact typed cohort values. Use the
investigation method for findings/status.

Ordered trace

  1. Copy baseline F twice. For attribute cohorts append

{attributeName:A,dataType:T,attributeValues:[X],isInclusive:true} to
attributeValueFilters for A's cohort value, and the same shape with Y for B.
Preserve other agreed baseline conditions; retain rework restrictions only if part of that
baseline. Do not leak an exploratory/outcome-only subset into a full-population comparison.
Change only the intended cohort condition. If values are unknown, request
get_attribute_values_v2 {S,attributeName:A,itemsPerPage:20,itemsToSkip:0,filterOptions:F};
it returns values, not frequencies.

  1. get_process_overall_metrics_v2 {S,filterOptions:F_A} ->

get_process_overall_metrics_v2 {S,filterOptions:F_B}.
No metrics, groupBy or aggregation parameter exists. Use the same returned metric definitions;
native CaseDuration/CaseWaitingTime are means.

  1. Only if a grouped explanation is needed and statistics is advertised, make a matched pair:

get_attribute_statistics {S,attributeName:A,filterOptions:F_A,itemsPerPage:5,itemsToSkip:0,metricToSortBy:"TotalDuration",sortOrder:"Descending"},
then exactly the same call with F_B. Do not treat independent top-five pages as a complete aligned population.

Continue relevant value/group pages or matched follow-ups when needed, without fixed call quotas.
Stop at sufficient evidence, no new information or a capability/error boundary; no blind sweeps.
Do not create views or use two inclusive timeframes in one query as an A/B comparison.

Time and reproducibility

For periods, change only one explicit timeframeFilters start/end pair in each copied F.
Case windows mean Contained, not cases Started/Completed/Intersecting or all events during the period.
If completed-only membership including earlier starts is essential, stop/reframe or route
to derive-metric/a user-confirmed existing matching view. Never invent a date-mode field
or promise unknown end-boundary behavior.

If refresh is reported or reproducibility is at risk, recheck details.
Changed PV/PMV invalidates the pair: mark inconclusive, stop or deliberately rerun both,
not just the second.
Process selection resolves latest; no direct version selector or atomic comparison snapshot exists.
Views pin version context but their configuration is mutable/cached.

Report A/B counts, mean metrics, absolute delta and relative change only for a nonzero baseline.
Empty cohorts mean insufficient evidence, not zero duration/infinite improvement.
State scope/version and unmatched-group coverage; at most five headline rows.
Recorded means do not establish closure, equal maturity or complete lifecycles. Report those
as unknown unless supported; qualify the comparison, not an assumed causal improvement.
Retain baseline/cohort filters, evidence references, status and alternatives. Overlapping groups
cannot be added as unique-case totals.
Object-centric comparisons belong in analyze-objects, not case-filter fallbacks.

Info
Category Data Science
Name compare-cohorts
Version v20261008
Size 3.6KB
Updated At 2026-10-09
Language