Change and contribution analysis: Implementation and data quality

Specifies storage, interfaces, validation, access, freshness, monitoring, and failure behavior for change and contribution analysis, so adopters can decompose an observed metric change into authorized segments and distinguish contribution evidence from unsu...

Package status: reference context ready for human review. The contract and test scenarios are complete, but no claim is made that an adopting implementation has passed them.

Decision

For Change and contribution analysis, implement the semantic contract through owned, typed boundaries so adopters can decompose an observed metric change into authorized segments and distinguish contribution evidence from unsupported causal explanation. The method attributes arithmetic contribution within declared dimensions; it does not establish real-world causation without a separate causal design. This is a reference contract: database products, numeric budgets, jurisdictions, retention, organizational defaults, and accountable owners remain explicit adoption choices.

Scope

• The Change and contribution analysis actors, inputs, outputs, states, versions, and externally visible outcomes needed to decompose an observed metric change into authorized segments and distinguish contribution evidence from unsupported causal explanation.
• The role-specific focus of this block: implement the semantic contract through owned, typed boundaries, including primary, cached, asynchronous, export, support, and recovery paths where applicable.
• Adoption-specific configuration, ownership, rollout, evidence retention, and review responsibilities needed to use the contract safely.

Outside this block

• The method attributes arithmetic contribution within declared dimensions; it does not establish real-world causation without a separate causal design.
• Choosing a universal database, model, renderer, vendor, numeric threshold, retention period, timezone, jurisdiction, or service-level objective.
• Claiming that packaged scenarios ran against a downstream implementation or that this reference grants security, privacy, accessibility, analytical, or legal approval.

Contract

• The implemented Change and contribution analysis boundary enforces this rule: Contribution analysis begins with one validated total delta and decomposes only dimensions approved by the metric catalog and caller authorization.
• The implemented Change and contribution analysis boundary enforces this rule: Segment contributions use a documented additive, rate, mix, or other decomposition method whose components reconcile to the total or expose a residual.
• The implemented Change and contribution analysis boundary enforces this rule: Rankings state whether contribution is absolute, relative, positive, negative, or share-based and retain units throughout the calculation.
• The implemented Change and contribution analysis boundary enforces this rule: Small populations, restricted dimensions, high-cardinality values, and differencing risks are suppressed or grouped before results reach the agent.
• The implemented Change and contribution analysis boundary enforces this rule: The analysis distinguishes a segment contributing to arithmetic change from that segment causing the underlying behavior.
• The implemented Change and contribution analysis boundary enforces this rule: Interactions, overlapping dimensions, metric-definition changes, missing values, and access-trimmed segments produce visible limitations rather than false reconciliation.
• The implemented Change and contribution analysis boundary enforces this rule: The narrative names the largest material contributors, the remaining residual, and a bounded next question instead of listing every segment.
• The implemented Change and contribution analysis boundary enforces this rule: Repeated drill-down calls preserve the original total, periods, metric version, and policy scope through an explicit analysis handle.

Implementation guidance

• Store the versioned semantic object separately from database-specific compiled artifacts and presentation-specific documents.
• Validate at ingestion, registry, query, result, and rendering boundaries and keep one normalized representation through downstream steps.
• Roll out additively, compare old and new evidence over frozen fixtures, and keep a reversible migration until consumers adopt the new version.
• Instrument success, rejection, staleness, partial results, version conflicts, and repair without recording sensitive payloads.

Failure handling and safeguards

• For Change and contribution analysis, If contributions cannot reconcile within the declared tolerance, the decomposition is marked incomplete and no cause-like summary is generated.
• For Change and contribution analysis, If a requested dimension is unauthorized or unsafe, the server denies it before aggregation and does not reveal whether hidden segments exist.
• For Change and contribution analysis, A metric or source discontinuity inside the comparison period blocks contribution ranking unless the user selects a comparable interval.

Verification and operations

• For the implementation evidence of Change and contribution analysis, reconcile additive, rate, and mix fixtures to known totals, including residual, overlap, suppressed segments, and missing data.
• For the implementation evidence of Change and contribution analysis, review generated language for causal overstatement and require explicit distinction between contribution, association, experiment, and causal evidence.
• For the implementation evidence of Change and contribution analysis, test drill-down under different roles and confirm that totals, ranks, minimum populations, and hidden-dimension behavior remain policy-correct.

Adoption assumptions

• The adopting product has authenticated identity, a versioned authorization policy, owned metric definitions, bounded telemetry, and a controlled path for change.
• Names and values in the example are fictional adoption fixtures, not universal defaults, production credentials, performance promises, or business targets.
• Referenced specifications constrain protocol, security, accessibility, or vendor behavior; the adopting team must confirm current applicability before promotion.

The executable-looking examples in this package are fixtures and acceptance contracts. Run the collection validator to check structure and metadata, then translate and execute the scenarios in the target repository before recording implementation evidence.

References

• NIST AI 600-1, Generative AI Profile (applies as of 2026-09-12)