{ "objectName": "Evidence Checklist", "objectType": "LPM Knowledge Object", "version": "1.0", "owner": "LPM / Lapemo", "lastReviewedDate": "2026-06-24", "lpmLayer": [ "Information Ecology", "Governance Architecture", "Decision Architecture", "AI Amplification" ], "connectedLayers": [ "Ownership Map", "Communication Architecture", "Platform Structure", "Identity & Incentives" ], "purpose": "Define the evidence required before decisions, AI initiatives, controls, recommendations, escalations, and operating-model claims are trusted.", "intendedAudience": [ "Executives", "Transformation leaders", "Product leaders", "Technology leaders", "AI initiative owners", "Risk leaders", "Governance teams", "Data leaders", "Operations leaders", "Platform owners", "Audit and compliance teams" ], "requiredFields": [ { "name": "evidenceId", "type": "string", "required": true }, { "name": "supportedClaim", "type": "text", "required": true }, { "name": "evidenceType", "type": "enum", "values": [ "metric_kpi", "decision_evidence", "control_evidence", "system_evidence", "data_evidence", "people_evidence", "customer_evidence", "ai_evidence", "sme_attestation" ], "required": true }, { "name": "sourceSystemOrLocation", "type": "string", "required": true }, { "name": "evidenceOwner", "type": "role", "required": true }, { "name": "sourceOwner", "type": "role", "required": true }, { "name": "dateCaptured", "type": "date", "required": true }, { "name": "freshnessWindow", "type": "duration", "required": true }, { "name": "confidenceRating", "type": "enum", "values": [ "low", "medium", "high", "verified" ], "required": true }, { "name": "lineageProvenance", "type": "text", "requiredWhen": "materialDecision == true or evidenceType in [data_evidence, control_evidence, ai_evidence]" }, { "name": "dataClassification", "type": "enum", "values": [ "public", "internal", "confidential", "restricted", "regulated", "customer", "employee", "financial", "model", "legal_sensitive" ], "required": true }, { "name": "aiInvolvement", "type": "enum", "values": [ "none", "ai_summarized", "ai_classified", "ai_recommended", "ai_generated", "ai_executed", "autonomous_ai_involved" ], "required": true }, { "name": "humanReviewer", "type": "role", "requiredWhen": "materialDecision == true or aiInvolvement != none" }, { "name": "contradictoryEvidence", "type": "text", "requiredWhen": "knownContradiction == true" }, { "name": "evidenceGap", "type": "text", "requiredWhen": "gapDetected == true" }, { "name": "decisionObjectLink", "type": "string", "requiredWhen": "evidence supports material decision, AI initiative, escalation, control, or governance review" }, { "name": "reviewStatus", "type": "enum", "values": [ "draft", "submitted", "reviewed", "verified", "rejected", "stale", "superseded", "archived" ], "required": true }, { "name": "reviewDate", "type": "date", "required": true }, { "name": "version", "type": "string", "required": true } ], "optionalFields": [ { "name": "evidenceSummary", "type": "text" }, { "name": "sourceUrl", "type": "string" }, { "name": "sourceQuery", "type": "text" }, { "name": "dataQualityScore", "type": "number" }, { "name": "modelOrAgentId", "type": "string" }, { "name": "controlId", "type": "string" }, { "name": "riskTier", "type": "enum", "values": [ "low", "medium", "high", "critical", "regulated" ] }, { "name": "retentionRequirement", "type": "text" }, { "name": "supersededEvidenceId", "type": "string" }, { "name": "operatingModelCorrection", "type": "text" } ], "scoringLogic": { "dimensions": [ "sourceQuality", "ownerClarity", "freshness", "completeness", "lineage", "contradictionHandling", "aiReview", "sensitivityControl", "replayability" ], "scale": [ [ "0", "Evidence is informal, anecdotal, stale, undocumented, or dependent on individual interpretation." ], [ "1", "Evidence exists but source ownership, recency, lineage, confidence, or review status is unclear." ], [ "2", "Evidence is documented but not consistently tied to claims, decisions, AI output, or governance controls." ], [ "3", "Evidence is source-linked, owner-backed, fresh, reviewed, confidence-rated, and connected to the decision or operating object." ], [ "4", "Evidence is governed, lineage-aware, AI-readable, auditable, automatically refreshed or flagged, and connected to live operating-model control." ] ], "formula": "average(sourceQuality, ownerClarity, freshness, completeness, lineage, contradictionHandling, aiReview, sensitivityControl, replayability)", "highRiskFlag": "true when source missing, owner missing, freshness expired, low confidence used for material decision, AI involved without reviewer, sensitive data unclassified, contradictory evidence unresolved, or decision made without evidence link" }, "companyProfiles": { "500_plus": { "designPrinciple": "make evidence explicit without slowing down execution", "minimumModel": "claim, source, owner, date, confidence, gap, decision link, review date", "standards": [ [ "Primary problem", "Evidence lives in people's heads, decks, Slack/Teams threads, spreadsheets, and founder/operator memory", "Create a simple evidence standard before AI pilots and scaling decisions become opinion-driven" ], [ "Minimum evidence pack", "Claim, source, owner, date, confidence, decision link, evidence gap, next review date", "Keep it lightweight and repeatable" ], [ "Owner standard", "Every evidence item has one evidence owner and one source owner", "No ownerless evidence" ], [ "AI standard", "AI output can support analysis but cannot be the only evidence for customer, employee, financial, or control decisions", "Human validation required" ], [ "Review rhythm", "Review before major decisions, AI pilots, funding approvals, operating-model changes, and quarterly planning", "Do not overbuild governance too early" ], [ "Website artifact use", "Download as a workshop checklist and AI readiness self-assessment", "Simple, founder-to-executive friendly" ] ] }, "5000_plus": { "designPrinciple": "standardize evidence across functions, decisions, controls, data, and AI initiatives", "minimumModel": "source system, owner chain, lineage, freshness, confidence, classification, reviewer, contradictions, object link", "standards": [ [ "Primary problem", "Evidence is fragmented across functions, platforms, BI tools, vendors, PMO rituals, risk teams, and transformation programs", "Create cross-functional evidence standards tied to decisions, owners, and governance" ], [ "Minimum evidence pack", "Claim, source system, owner, lineage, freshness, confidence, data classification, AI involvement, reviewer, contradictory evidence, decision/object link", "Make evidence reviewable across functions" ], [ "Owner standard", "Evidence owner, source owner, decision owner, control owner, and AI boundary owner where relevant", "Separate evidence ownership from decision authority" ], [ "AI standard", "AI-summarized or AI-recommended evidence requires provenance, reviewer, source quality score, and review status", "AI cannot hide weak source data" ], [ "Review rhythm", "Review at portfolio, governance, risk, architecture, AI initiative, and value realization checkpoints", "Connect to operating rhythms" ], [ "Website artifact use", "Download as an enterprise operating template and Lapemo onboarding object", "Prepared for structured ingestion" ] ] }, "10000_plus": { "designPrinciple": "federate evidence capture while centralizing standards, lineage, controls, and auditability", "minimumModel": "enterprise evidence object with source, owner chain, lineage, AI trace, control mapping, retention, supersession, and review cadence", "standards": [ [ "Primary problem", "Evidence conflicts across business units, regions, legal entities, systems of record, data domains, governance forums, and AI platforms", "Federate evidence capture while centralizing standards, lineage, controls, and replayability" ], [ "Minimum evidence pack", "Full evidence object with claim, authority source, lineage, owner chain, confidence score, sensitivity, control mapping, AI trace, contradictions, retention, and supersession rules", "Enterprise-grade evidence control" ], [ "Owner standard", "Evidence owner, source owner, data owner, system owner, control owner, legal/entity owner, decision owner, AI boundary owner, and value owner where needed", "Complexity requires formal role separation" ], [ "AI standard", "AI use requires prompt/model trace, evaluation result, human review, automated monitoring where available, and stop-control evidence for autonomous workflows", "AI evidence must be auditable and revocable" ], [ "Review rhythm", "Review through enterprise governance, risk, audit, regulatory, portfolio, model-risk, and operating-model control cadences", "Material evidence must be replayable" ], [ "Website artifact use", "Download as an executive guide and machine-readable control object for large enterprises", "Designed for federation and central control" ] ] } }, "evidenceTypes": [ { "type": "Metric / KPI", "use": "Performance, cycle time, cost, quality, productivity, adoption, value, or risk metric", "commonSource": "Dashboard, BI tool, warehouse, product analytics" }, { "type": "Decision evidence", "use": "Facts used to approve, reject, defer, or supersede a decision", "commonSource": "Decision Log, meeting record, product brief, governance forum" }, { "type": "Control evidence", "use": "Proof that policy, approval, risk review, security, privacy, audit, or compliance control occurred", "commonSource": "GRC, audit tool, risk register, workflow system" }, { "type": "System evidence", "use": "Logs, tickets, changes, access records, workflow state, incident records, or integration events", "commonSource": "Jira, ServiceNow, GitHub, CI/CD, IAM, observability" }, { "type": "Data evidence", "use": "Source data, lineage, quality score, definition, data owner approval, or reconciliation result", "commonSource": "Warehouse, catalog, BI semantic layer, data quality tool" }, { "type": "People evidence", "use": "Role, ownership, staffing, readiness, behavior, adoption, training, or incentive evidence", "commonSource": "Workday, LMS, survey, org system, enablement record" }, { "type": "Customer evidence", "use": "Customer feedback, support trend, churn, NPS, satisfaction, contract issue, or external commitment", "commonSource": "CRM, support platform, research repository" }, { "type": "AI evidence", "use": "Prompt, model output, model card, evaluation result, human review, agent action log, or boundary test", "commonSource": "Model registry, AI platform, eval harness, agent log" }, { "type": "SME attestation", "use": "Named expert judgment when system evidence is incomplete or not yet instrumented", "commonSource": "Attestation record with owner and expiration date" } ], "qualityDimensions": [ { "dimension": "Source quality", "question": "Is the evidence pulled from an authoritative system or from an informal summary?", "passCondition": "Authoritative source identified" }, { "dimension": "Owner quality", "question": "Is there a named evidence owner and source owner?", "passCondition": "Both owners named" }, { "dimension": "Freshness", "question": "Is the evidence recent enough for the decision or risk tier?", "passCondition": "Freshness window active" }, { "dimension": "Completeness", "question": "Does the evidence cover the whole claim, not just the favorable part?", "passCondition": "No material missing fields" }, { "dimension": "Lineage", "question": "Can the evidence path be traced from source to use?", "passCondition": "Provenance documented" }, { "dimension": "Contradiction check", "question": "Has conflicting evidence been surfaced and resolved?", "passCondition": "Known contradictions captured" }, { "dimension": "AI review", "question": "Was AI-generated or AI-summarized evidence reviewed by a human when material?", "passCondition": "Human reviewer named" }, { "dimension": "Sensitivity control", "question": "Is data classification and access handling clear?", "passCondition": "Classification recorded" }, { "dimension": "Replayability", "question": "Can a future reviewer understand what was known and why it was trusted?", "passCondition": "Decision/object link present" } ], "aiInvolvementRules": [ { "level": "Level 0 - No AI", "meaning": "Evidence is human-created or system-generated without AI interpretation", "requiredControl": "Normal evidence owner and source owner required" }, { "level": "Level 1 - AI summarizes evidence", "meaning": "AI compresses source content into a summary", "requiredControl": "Source links, reviewer, and summary limitations required" }, { "level": "Level 2 - AI classifies evidence", "meaning": "AI assigns category, severity, confidence, ownership, or risk tier", "requiredControl": "Classification logic and human spot-check required" }, { "level": "Level 3 - AI recommends from evidence", "meaning": "AI recommends a decision, priority, risk response, or escalation path", "requiredControl": "Decision owner and reviewer required before material action" }, { "level": "Level 4 - AI generates evidence artifact", "meaning": "AI creates a brief, decision pack, control memo, or evidence synthesis", "requiredControl": "All claims must be tied to sources and reviewed" }, { "level": "Level 5 - AI acts on evidence", "meaning": "AI triggers workflow, routes work, changes state, blocks work, or executes an action", "requiredControl": "AI boundary owner, stop path, audit trail, and control owner required" } ], "validationRules": [ { "condition": "No supported claim", "systemResponse": "Block evidence record approval", "reason": "Evidence must support something specific" }, { "condition": "No source system or location", "systemResponse": "Mark low confidence", "reason": "Evidence without source is weak" }, { "condition": "No evidence owner", "systemResponse": "Block material use", "reason": "Evidence needs accountable interpretation" }, { "condition": "No source owner", "systemResponse": "Flag source-governance gap", "reason": "Underlying source must be accountable" }, { "condition": "Date captured missing", "systemResponse": "Require timestamp", "reason": "Freshness cannot be evaluated" }, { "condition": "Freshness window expired", "systemResponse": "Mark stale and require refresh", "reason": "Old evidence may mislead decisions" }, { "condition": "Low confidence used for material decision", "systemResponse": "Require reviewer or alternate evidence", "reason": "Material decisions need stronger evidence" }, { "condition": "AI involved but no human reviewer", "systemResponse": "Block material use", "reason": "AI-assisted evidence needs accountability" }, { "condition": "Restricted data without classification", "systemResponse": "Escalate to control owner", "reason": "Sensitive data must be governed" }, { "condition": "Contradictory evidence unresolved", "systemResponse": "Flag decision risk", "reason": "Conflicting evidence must be resolved or explicitly accepted" }, { "condition": "Decision made but no evidence link", "systemResponse": "Require Decision Log update", "reason": "Decisions must be replayable" }, { "condition": "Repeated evidence gap", "systemResponse": "Create operating-model correction", "reason": "Recurring gaps point to information ecology or ownership failure" } ], "mappingRules": [ { "targetObject": "Ownership Map", "mapping": "Evidence owner, source owner, data owner, system owner, control owner, and AI boundary owner should map to named ownership." }, { "targetObject": "Decision Rights Model", "mapping": "Materiality of evidence determines who can accept weak evidence, approve exceptions, or require more proof." }, { "targetObject": "Decision Rights Matrix", "mapping": "Decision evidence maps to decider, recommender, consulted, informed, implementation owner, and control owner." }, { "targetObject": "Decision Log", "mapping": "Every material decision should link to the evidence that supported it and identify what evidence was missing." }, { "targetObject": "Escalation Map", "mapping": "Stale, missing, contradictory, ownerless, or AI-risk evidence can trigger escalation." }, { "targetObject": "AI Initiative Owner Register", "mapping": "AI initiatives must define evidence for value, risk, model behavior, control readiness, and human review." }, { "targetObject": "Incentive Alignment Checklist", "mapping": "Evidence gaps often reveal teams are rewarded for activity, output, or optics instead of verified outcomes." }, { "targetObject": "Information Ecology", "mapping": "Evidence quality is a direct signal of information health, lineage, trust, and source discipline." }, { "targetObject": "Platform Structure", "mapping": "Evidence should trace to systems, workflows, repositories, observability, and BI/control platforms." }, { "targetObject": "Governance Architecture", "mapping": "Control evidence, audit evidence, privacy evidence, security evidence, and model-risk evidence map to governance owners." } ], "aiPrompts": [ "Assess whether this evidence is sufficient to support the stated decision, risk, control, AI recommendation, or operating-model claim.", "Classify the evidence by source quality, freshness, owner clarity, lineage, sensitivity, confidence, AI involvement, and review status.", "Identify missing evidence, stale evidence, contradictory evidence, weak-source evidence, and ownerless evidence.", "Generate an executive-ready evidence summary with claim, source, confidence, gaps, contradictions, reviewer, and next action.", "Determine whether this evidence requires a Decision Log entry, Escalation Map trigger, AI Initiative Owner Register update, or governance review.", "Detect when AI is being treated as evidence instead of a tool for summarizing or reasoning over evidence.", "Generate the correct checklist version for a 500+, 5,000+, or 10,000+ employee company." ], "renderTargets": [ "docx", "pdf", "markdown", "json", "website_page", "interactive_form", "csv_import", "lapemo_in_app_workflow" ], "reviewTriggers": [ "Company crosses 500, 5,000, or 10,000+ employees", "New AI initiative, agent, model, automation, or decision-support workflow is introduced", "Major decision, escalation, audit finding, incident, or governance exception occurs", "Source system, BI tool, data warehouse, GRC tool, workflow platform, or model registry changes", "Evidence owner, source owner, data owner, control owner, or AI boundary owner changes", "Evidence becomes stale, contradictory, incomplete, disputed, or unsupported by source lineage", "Regulatory, legal, privacy, security, financial, customer, or employee-impacting requirement changes" ], "websitePositioningCopy": "A reusable LPM method for defining the evidence required before decisions, AI initiatives, controls, recommendations, escalations, and operating-model claims are trusted.", "governanceNotes": [ "AI output is not evidence by itself.", "Evidence without owner, source, freshness, and lineage should not support material decisions.", "Evidence gaps are operating-model signals, not just documentation problems." ] }