Measure design and completeness
The assessment tests whether measures cover the intended outcome, define the population and period correctly, and avoid incentives that distort operational behavior.
Performance-measure review
Verify that reported performance means what leadership thinks it means.
Elvaris assesses whether program measures are complete, reliable, decision-useful, and supported by a defensible collection process. Reviews connect reported results to definitions, source evidence, known error, and operational variation.
The assignment
What you receive. What we need.
- Deliverable
- Measure-by-measure findings, a record of the checks performed, limitations and recommended corrections.
- Customer inputs
- Selected measures, definitions, reporting periods, source records, calculations and known exclusions.
- Example acceptance criteria
- Each selected measure has a documented definition, checks of available supporting records, and an explicit conclusion or limitation. Unreproducible values are flagged, not accepted by default.
- Scope boundary
- Not a financial-statement audit, a guarantee of savings or proof that AI caused an observed change. AI value conclusions depend on the agreed baseline, comparison design and supporting records; an illustrative calculation is not a measured result.
- Effort and price
- Quoted after agreeing the material, access, stakeholders, deliverables and deadline.
Reliability and evidence
Source systems, transformations, exclusions, manual steps, and quality controls are traced so reported values can be reproduced and limitations can be stated precisely.
Error and process variation
Measurement error and normal process variation are separated from meaningful performance change, reducing false conclusions and improving management response.
Engagement outputs
Designed for decision, remediation, and audit.
- Clear measure definitions and decision purpose
- Documented data lineage and limitations
- Reliability findings supported by evidence
- More defensible performance reporting
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