DECM — Decision Evidence Consolidation Module
Architecture:
VEGA™ — Value Execution Governance Architecture
Parent Standard:
Decision Governance Standard (DGS)
Category:
Governance & Enforcement
Subcategory:
Value Execution Governance
Type: Core Module
Governed Space:
Decision Evidence Consolidation Governance
Module ID: VEGA-DGS-DECM-001
Origin ID: OOF.CM.VEGA.10.01.01
Version: 1.0
Status: Canonical · Open Standard
Effective Date: 1 October 2026
Compatibility: OOF® Methodology OS™ · Modular OOF® Architecture Ecosystem
AI-Readable: Yes
Authority: OOF® — OriginOpen® Foundation
Protection:
MIP® — Methodological Intellectual Property
Canonical Language:
English (UCL™)
1. Canonical Definition
The Decision Evidence Consolidation Module (DECM) governs how materially relevant evidence required for an intelligence lifecycle decision is identified, collected from competent governed sources, normalized for decision use, reconciled where necessary, and consolidated into a coherent decision evidence state.
DECM establishes the evidentiary foundation from which continuation, scaling, migration, and retirement decisions can subsequently be evaluated.
It brings together governed evidence concerning:
Value,
execution,
productivity,
resources,
computational optimization,
economics,
Strategic Value,
sustainability,
Value Attribution,
and applicable governed constraints
without replacing the standards or governance architectures responsible for those domains.
DECM does not decide whether an intelligence operating model should continue, scale, migrate, or retire.
It determines whether the relevant evidence has been assembled into a sufficiently coherent state for those decisions to be governed.
Its principal output is:
Governed Decision Evidence State
Its foundational distinction is:
Available Evidence ≠ Decision-Ready Evidence.
2. Operational Role
The operational role of DECM is:
to transform distributed governed evidence into a coherent, traceable, decision-relevant evidence state without altering the meaning, confidence, uncertainty, provenance, or governance boundaries of the underlying evidence.
Decision Governance cannot begin with isolated metrics.
It requires an evidence state capable of representing the intelligence operating model as a connected system.
3. Position in the DGS Internal Flow
The DGS internal governance flow is:
Decision Evidence Consolidation → Continuation Decision → Scaling Decision → Migration Decision → Retirement Decision
DECM governs:
Decision Evidence Consolidation
It is the first operational stage of DGS.
Its principal upstream inputs are the relevant governed states produced across VEGA™ and competent interoperating governance architectures.
Its principal output is:
Governed Decision Evidence State
That state proceeds to:
Continuation Decision Governance
4. Central Operational Question
What governed evidence is materially relevant to the lifecycle decision, and has that evidence been consolidated into a sufficiently complete, current, coherent, traceable, and decision-ready state?
5. Decision Evidence Object
Every DECM assessment should define the Decision Evidence Object.
The object identifies the evidence required to evaluate a specific intelligence lifecycle decision.
It should be associated with:
the intelligence operating model,
decision scope,
decision horizon,
decision context,
applicable lifecycle stage,
and relevant Decision Governance Object.
6. Decision Evidence Boundary
DECM should establish which evidence belongs within the decision boundary.
Evidence should enter the consolidated state because it is materially relevant to the decision.
Not because it happens to be available.
Evidence Availability ≠ Decision Relevance.
7. Decision Evidence Horizon
Evidence may remain relevant for different periods.
DECM should determine whether evidence represents:
current operation,
historical performance,
expected future conditions,
transition conditions,
or another decision-relevant horizon.
Historical evidence should not automatically be treated as current evidence.
8. Decision Context
Evidence should be interpreted within the context in which the lifecycle decision is being considered.
Relevant context may include:
operational purpose,
deployment environment,
scale,
system configuration,
resource conditions,
economic conditions,
Strategic Value conditions,
dependencies,
and applicable governed constraints.
9. Decision Question Alignment
Evidence should be consolidated against the actual decision question.
Evidence relevant to continuation may differ from evidence required for scaling.
Evidence supporting current operation may be insufficient for migration.
Decision Evidence must be aligned with the Decision Question.
10. Evidence Source Identification
DECM should identify the competent source of each material evidence state.
Sources may include:
VEGA™ Parent Standards,
VEGA™ Core Modules,
interoperating OOF® architectures,
validated operational evidence,
competent external governance systems,
or other governed evidence sources.
Source identity supports boundary preservation.
11. Governed Evidence Preference
Where a governed evidence state exists, DECM should prefer that state over recreating the underlying assessment.
DECM consolidates.
It does not unnecessarily re-govern domains already governed elsewhere.
12. Value Evidence
DECM should preserve the applicable governed Value evidence.
Relevant evidence may include:
Value definition,
classification,
qualification,
validation,
threshold state,
and resulting Value state.
Activity ≠ Value.
13. Execution Evidence
Execution evidence may include:
execution legitimacy,
execution configuration,
trigger conditions,
execution boundaries,
termination conditions,
and material execution anomalies.
DECM preserves these states for decision use without replacing XGS.
14. Productivity Evidence
DECM should preserve the relevant Intelligence Productivity state.
Evidence may include:
validated productive output,
task completion,
Human Power Equivalency where applicable,
cognitive productivity,
or normalized productivity.
Activity ≠ Productivity.
15. Resource Evidence
Resource evidence may include consumption or allocation of:
compute,
energy,
hardware,
infrastructure,
human effort,
time,
or other materially relevant resources.
Resource consumption should remain connected to the Value-producing process.
16. Computational Optimization Evidence
DECM may consolidate evidence concerning:
Problem-Space Efficiency,
Cognitive Efficiency,
Orchestration Efficiency,
Model Allocation Efficiency,
Compute Allocation Efficiency,
and Hardware Execution Efficiency.
The evidence should remain connected to the applicable execution configuration.
17. Economic Evidence
Economic evidence may include:
Effective Task Cost,
Failure Spend,
Correction Cost,
Intelligence ROI,
Value-to-Cost relationships,
and other governed economic states.
Cost should not be interpreted independently from Value.
18. Strategic Value Evidence
Where immediate Value does not fully represent the purpose of the intelligence investment, DECM should preserve relevant Strategic Value evidence.
This may include:
capability formation,
Deferred Value,
Strategic Milestones,
and Capital-at-Risk conditions.
19. Sustainability Evidence
DECM should preserve relevant evidence concerning long-term viability.
This may include:
Sustainability Threshold,
Execution Energy Viability,
Infrastructure Sustainability,
Economic Continuity,
and Dependency Sustainability.
20. Value Attribution Evidence
DECM should preserve the applicable:
Governed Value Attribution State
where contribution structure is relevant to the lifecycle decision.
This may identify:
Value sources,
material contributions,
Human–AI contribution,
Multi-Agent contribution,
and Attribution Evidence.
21. Constraint Evidence
DECM should identify applicable governed constraints established by competent governance domains.
These constraints may define which decision options remain feasible.
A lifecycle option that violates a non-negotiable applicable constraint should not enter the feasible decision space merely because its VEGA™ performance is strong.
22. External Evidence
Decision-relevant evidence may originate outside VEGA™.
Where applicable, DECM may consume governed states concerning:
Harm,
Liability,
Accountability,
authority,
permission,
compliance,
Operational Reality,
or other relevant domains.
DECM preserves those states without redefining them.
23. Evidence Competence
Evidence should originate from a source competent to establish the relevant governed state.
A financial system may establish cost evidence.
It may not be competent to establish Harm.
A performance benchmark may establish technical performance.
It may not establish operational Value.
Evidence Source Competence matters.
24. Evidence Relevance
Evidence should materially inform the lifecycle decision under consideration.
DECM should exclude or de-emphasize evidence that is technically available but decision-irrelevant.
More evidence does not automatically improve the decision state.
25. Evidence Materiality
Material evidence is evidence capable of changing:
the feasible option set,
the decision evaluation,
a decision condition,
or the confidence of the decision state.
Materiality should be assessed relative to the Decision Governance Object.
26. Evidence Completeness
DECM should assess whether all materially relevant evidence domains are sufficiently represented.
Completeness does not require every possible data point.
It requires sufficient coverage of the evidence necessary for the decision.
27. Evidence Coverage
Coverage identifies which material decision dimensions are:
sufficiently evidenced,
partially evidenced,
unevidenced,
or unresolved.
This prevents strong evidence in one dimension from hiding missing evidence in another.
28. Evidence Granularity
Evidence may exist at different levels:
execution,
task,
workflow,
system,
deployment,
portfolio,
or organizational level.
DECM should ensure that evidence granularity corresponds to the Decision Governance Object.
29. Evidence Scope Alignment
Evidence generated for one scope should not automatically support another.
For example:
one workflow's productivity evidence should not automatically represent an entire organizational deployment.
Evidence Scope ≠ Decision Scope by default.
30. Evidence Temporal Alignment
Evidence from different time periods may not be directly comparable.
DECM should identify whether evidence represents compatible operating periods.
Material temporal differences should remain visible.
31. Evidence Configuration Alignment
Evidence should correspond to the configuration being evaluated.
Evidence from:
another model,
another agent configuration,
another infrastructure environment,
another workflow,
or another validation regime
should not automatically represent the current configuration.
32. Evidence Scale Alignment
Evidence produced at pilot scale may not remain representative at production scale.
DECM should preserve scale where it materially affects interpretation.
Pilot Evidence ≠ Scale Evidence by default.
33. Evidence Environment Alignment
Evidence produced in controlled environments may differ from operational reality.
DECM should preserve whether evidence originates from:
simulation,
testing,
pilot deployment,
limited production,
or full operational deployment.
34. Evidence Normalization
Different evidence domains may use different:
units,
scales,
time horizons,
measurement methods,
or state structures.
DECM may normalize evidence where necessary for decision comparison.
Normalization should preserve the original evidence.
35. Normalization Transparency
Every material normalization should preserve:
original state,
normalized state,
method,
assumptions,
and limitations.
Normalized Evidence must remain traceable to Original Evidence.
36. Evidence Comparability
Evidence should be compared only where the comparison is methodologically defensible.
Comparability may require alignment of:
scope,
configuration,
time,
scale,
measurement method,
or Value object.
37. Evidence Aggregation
DECM may aggregate evidence where aggregation improves decision usability without hiding material differences.
Aggregation should not erase:
outliers,
conflicts,
uncertainty,
or non-compensable constraints.
38. Evidence Compression
Large evidence volumes may require compression into decision-relevant states.
Compression should preserve the material information necessary to reconstruct the decision basis.
Evidence Compression ≠ Evidence Erasure.
39. Evidence Weighting
Where evidence receives different decision relevance, weighting may be used.
Weighting should be:
explicit,
justified,
traceable,
and appropriate to the Decision Governance Object.
No universal evidence weighting formula is required.
40. Non-Compensable Evidence
Some evidence may represent constraints that cannot be offset by strength elsewhere.
For example, strong economic evidence should not cancel a competent non-compensable constraint.
DECM should preserve these conditions separately from ordinary weighted evidence.
41. Positive Evidence
Positive Evidence supports the viability or justification of one or more lifecycle options.
It should remain associated with the dimension it supports.
42. Negative Evidence
Negative Evidence indicates weakness, deterioration, failure, or another factor that may reduce justification for one or more lifecycle options.
Negative evidence should not be suppressed because positive evidence exists elsewhere.
43. Conflicting Evidence
Evidence domains may support different conclusions.
For example:
Value may be high,
cost may be high,
Strategic Value may remain strong,
and sustainability may be uncertain.
DECM should preserve the conflict for DGS rather than force premature resolution.
44. Evidence Reconciliation
Where evidence conflicts because of:
different scopes,
different periods,
different methods,
different configurations,
or different definitions,
DECM should attempt methodological reconciliation.
Reconciliation should not mean arbitrary averaging.
45. Irreconcilable Evidence
Where material evidence cannot be reconciled, DECM should preserve:
the conflicting states,
their sources,
their evidence quality,
and their decision relevance.
The resulting Decision Evidence State may remain:
Conflicted
or
Unresolved
where appropriate.
46. Evidence Uncertainty
DECM should preserve uncertainty associated with each material evidence state.
Consolidation must not convert uncertain evidence into certain evidence.
Consolidation ≠ Certainty Creation.
47. Evidence Confidence
Evidence confidence should remain traceable to its source.
DECM may represent consolidated confidence, but it should not silently increase confidence beyond what upstream evidence supports.
48. Evidence Gap
An Evidence Gap exists where materially relevant decision evidence is unavailable or insufficient.
The gap should identify:
the missing evidence,
the affected decision dimension,
and the lifecycle decision potentially affected.
49. Critical Decision Evidence Gap
A Critical Decision Evidence Gap exists where missing evidence prevents a materially consequential lifecycle decision from being sufficiently governed.
The appropriate response may include:
additional evidence acquisition,
conditional decision,
reassessment,
or unresolved status.
50. Known Unknown
Known Unknowns should remain visible in the consolidated state.
A missing state should not automatically become a neutral state.
Unknown ≠ Neutral.
51. Evidence Freshness
DECM should determine whether evidence remains sufficiently current for the decision.
Evidence may become stale because of:
model changes,
configuration changes,
cost changes,
infrastructure changes,
dependency changes,
Value changes,
or operating-environment changes.
52. Evidence Expiration
Where appropriate, evidence may have an explicit validity period.
Expired evidence may remain historically relevant without remaining decision-ready.
53. Evidence Drift
Evidence Drift occurs where previously representative evidence no longer reflects the current intelligence operating model.
DECM should identify material drift before consolidation.
54. Evidence Update
Where material evidence changes, the consolidated evidence state should be updated.
Updates should preserve previous versions where decision traceability requires them.
55. Evidence Versioning
DECM should preserve:
evidence version,
source version,
configuration version,
methodology version,
and effective time
where material.
56. Evidence Provenance
Each material evidence state should remain traceable to its origin.
Provenance may include:
governing standard,
assessment,
system,
dataset,
record,
method,
or competent external source.
57. Evidence Traceability
DECM should preserve:
Evidence Source → Governed Evidence State → Consolidation Method → Decision Evidence State
This allows the decision basis to be reconstructed.
58. Evidence Integrity
Consolidated evidence should remain protected from:
selective omission,
undocumented modification,
unsupported weighting,
misclassification,
or manipulation.
The consolidated state should reflect the evidence rather than the desired decision.
59. Selective Evidence Risk
Selective Evidence Risk exists where only evidence supporting a preferred lifecycle option is consolidated.
DECM should preserve materially relevant evidence both supporting and challenging the option.
60. Evidence Dominance Risk
One highly visible evidence dimension may dominate decision interpretation.
Examples include:
cost,
model performance,
ROI,
energy consumption,
or benchmark performance.
DECM should prevent visibility from becoming unjustified dominance.
61. Metric Dominance Risk
A single metric should not automatically substitute for the broader governed evidence state.
One Metric ≠ Decision Evidence.
Even a strong metric may represent only one dimension of the lifecycle decision.
62. Dashboard Illusion
A dashboard may create an appearance of comprehensive evidence while omitting material decision dimensions.
DECM should evaluate evidence coverage rather than interface completeness.
Dashboard Completeness ≠ Governance Completeness.
63. Evidence Duplication
The same underlying evidence may appear through multiple systems or metrics.
DECM should identify duplication where it could artificially increase perceived support.
Repeated Evidence ≠ Independent Evidence.
64. Evidence Dependency
Evidence states may depend on the same underlying measurement, dataset, or assumption.
DECM should preserve material evidence dependencies where they affect interpretation.
65. Evidence Independence
Independent evidence may strengthen a decision basis.
DECM should distinguish independent corroboration from repeated transformation of the same underlying evidence.
66. Evidence Corroboration
Where multiple sufficiently independent sources support the same material conclusion, DECM may identify corroboration.
Corroboration can increase confidence without eliminating uncertainty.
67. Decision Evidence Matrix
Where useful, DECM may construct a Decision Evidence Matrix linking:
decision dimensions,
governed evidence states,
evidence sources,
confidence,
uncertainty,
freshness,
and material gaps.
The matrix is an implementation mechanism, not a mandatory universal format.
68. Decision Evidence Profile
A Decision Evidence Profile may summarize the current evidence landscape across relevant decision dimensions.
The profile should preserve material differences rather than collapse everything into a single score.
69. Decision Evidence Baseline
DECM may establish a baseline against which later decision evidence can be compared.
The baseline should preserve:
configuration,
time,
scope,
scale,
and methodology.
70. Decision Evidence Change
Material changes in evidence should be identifiable relative to previous states.
Change may be:
positive,
negative,
mixed,
or unresolved.
Change alone does not determine the lifecycle decision.
71. Decision Evidence Trend
Where sufficient time-series evidence exists, DECM may identify trends.
Possible trends include:
improving,
stable,
deteriorating,
volatile,
or unresolved.
Trend interpretation should remain evidence-based.
72. Decision Evidence Scenario
Where future lifecycle decisions depend on uncertain conditions, DECM may preserve scenario-specific evidence.
Examples may include:
expected demand growth,
future cost conditions,
infrastructure transition,
or dependency changes.
Scenario evidence should remain distinct from observed evidence.
73. Observed vs Projected Evidence
DECM should distinguish:
Observed Evidence
from
Projected Evidence
Projected evidence may be decision-relevant.
But it should not be represented as an observed state.
74. Decision Evidence Sensitivity
Where a decision depends strongly on uncertain assumptions, DECM may identify Evidence Sensitivity.
This reveals which assumptions or evidence states materially influence the available decision options.
75. Evidence Threshold Readiness
DECM may assess whether evidence is sufficiently mature to support application of downstream Decision Thresholds.
This is distinct from determining whether the threshold itself has been satisfied.
76. Decision-Ready Evidence
Evidence becomes Decision-Ready when it is sufficiently:
relevant,
material,
complete,
aligned,
current,
traceable,
and coherent
for the lifecycle decision under consideration.
Decision-ready does not mean perfect.
77. Conditional Decision Readiness
Where some evidence gaps remain but a bounded decision can still be governed, DECM may establish:
Conditionally Decision-Ready
The unresolved conditions should remain explicit.
78. Evidence-Limited Decision Readiness
Where material evidence is insufficient for a definitive lifecycle evaluation, the state should remain:
Evidence-Limited
rather than being forced into artificial completeness.
79. Decision Evidence State
Possible consolidated states may include:
Decision-Ready
Conditionally Decision-Ready
Partially Consolidated
Evidence-Limited
Materially Conflicted
Stale
Integrity-Constrained
Insufficient
Unresolved
These states describe the decision evidence condition.
They do not determine the lifecycle decision.
80. Governed Decision Evidence State
The principal output of DECM is:
Governed Decision Evidence State
It should identify, where applicable:
Decision Governance Object,
decision scope,
decision horizon,
decision context,
Value evidence,
execution evidence,
productivity evidence,
resource evidence,
Computational Optimization evidence,
economic evidence,
Strategic Value evidence,
sustainability evidence,
Value Attribution evidence,
external constraint evidence,
evidence sources,
materiality,
coverage,
alignment,
normalization,
conflict,
uncertainty,
confidence,
gaps,
freshness,
provenance,
traceability,
integrity,
and Decision Readiness.
81. Evidence Consolidation vs Decision Evaluation
DECM establishes what evidence is available and sufficiently ready for decision use.
It does not determine the final lifecycle option.
Decision Evidence Consolidation ≠ Lifecycle Decision.
This boundary prevents the evidence assembly mechanism from becoming the decision mechanism.
82. Evidence Consolidation vs Validation
DECM does not independently validate every upstream evidence object.
It should preserve governed validation states and identify where validation is absent or insufficient.
VALIDOS™ may govern applicable validation methodology.
83. Evidence Consolidation vs Audit
DECM is not a general audit architecture.
It requires traceable decision evidence but does not replace broader evidence and auditability governance.
ADIT® may govern those broader requirements.
84. Evidence Consolidation vs Operational Reality
Evidence may depend on Operational Reality.
DECM may consume relevant Operational Reality states.
It does not independently govern the complete operational-reality lifecycle.
85. Evidence Consolidation vs Harm
Harm evidence may constrain lifecycle options.
HAGA™ governs Harm.
DECM may consume the governed Harm state without redefining Harm.
86. Evidence Consolidation vs Liability
Liability evidence may affect lifecycle decisions.
LIGA™ governs Liability.
DECM may preserve the relevant Liability state without converting economic cost into Liability or vice versa.
87. Evidence Consolidation vs Authority
DECM may identify evidence relevant to authority constraints.
It does not grant authority.
Evidence of Capability ≠ Evidence of Permission.
88. Decision Evidence Handoff
The Governed Decision Evidence State should be sufficiently explicit for subsequent lifecycle decision governance.
The handoff should preserve:
material evidence,
constraints,
confidence,
uncertainty,
conflicts,
gaps,
freshness,
and provenance.
89. Handoff Integrity
The downstream decision process should not receive a cleaner or more certain evidence state than DECM actually established.
Material uncertainty and conflict must survive the handoff.
90. Evidence Reassessment Trigger
DECM should support reassessment where:
material evidence changes,
a new constraint appears,
the configuration changes,
evidence expires,
a critical gap is resolved,
or a decision horizon changes.
91. Evidence Consolidation Lifecycle
Decision evidence is not necessarily a one-time package.
It may move through:
Identification → Qualification → Alignment → Consolidation → Decision Readiness → Update → Reassessment
This lifecycle should remain traceable.
92. Minimum Implementation Framework
A conforming implementation of DECM must provide exactly the following six capabilities:
1. Decision Evidence Object & Boundary Governance
Capability to identify the Decision Governance Object, evidence boundary, decision scope, decision horizon, context, and Decision Question.
2. Multi-Domain Evidence Consolidation Governance
Capability to consolidate relevant governed evidence concerning Value, execution, productivity, resources, Computational Optimization, economics, Strategic Value, sustainability, attribution, and applicable external constraints.
3. Evidence Alignment, Normalization & Reconciliation Governance
Capability to assess scope, time, configuration, scale, environment, comparability, normalization, aggregation, conflict, and reconciliation without altering the original evidence meaning.
4. Evidence Sufficiency, Gap & Readiness Governance
Capability to assess materiality, completeness, coverage, uncertainty, confidence, Evidence Gaps, Critical Evidence Gaps, freshness, and Decision Readiness.
5. Evidence Integrity, Provenance & Lifecycle Governance
Capability to preserve provenance, traceability, integrity, independence, corroboration, versioning, drift, updates, scenarios, and reassessment.
6. DGS Continuation Decision Handoff Governance
Capability to produce a Governed Decision Evidence State sufficiently explicit for subsequent Continuation Decision Governance.
93. Governance Logic
The canonical DECM governance logic is:
Relevant Governed VEGA™ States
↓
Identify Decision Governance Object
↓
Define Decision Scope / Horizon / Context
↓
Define Decision Evidence Boundary
↓
Identify Decision Question
↓
Identify Competent Evidence Sources
↓
Consolidate Value Evidence
↓
Consolidate Execution Evidence
↓
Consolidate Productivity Evidence
↓
Consolidate Resource Evidence
↓
Consolidate Computational Optimization Evidence
↓
Consolidate Economic Evidence
↓
Consolidate Strategic Value Evidence
↓
Consolidate Sustainability Evidence
↓
Consolidate Value Attribution Evidence
↓
Identify Applicable External Governed Constraints
↓
Assess Evidence Materiality / Relevance
↓
Assess Completeness / Coverage
↓
Align Scope / Time / Configuration / Scale / Environment
↓
Normalize where necessary
↓
Identify Evidence Dependencies / Duplication
↓
Assess Conflict / Reconcile where possible
↓
Preserve Irreconcilable Evidence
↓
Assess Confidence / Uncertainty
↓
Identify Evidence Gaps / Critical Evidence Gaps
↓
Assess Freshness / Drift
↓
Verify Provenance / Traceability / Integrity
↓
Assess Decision Readiness
↓
Establish Governed Decision Evidence State
↓
Handoff to Continuation Decision Governance
94. Governance Outputs
DECM may produce:
Decision Evidence Object
Decision Evidence Boundary
Decision Scope Record
Decision Horizon Record
Decision Context Record
Decision Question Record
Evidence Source Map
Value Evidence State
Execution Evidence State
Productivity Evidence State
Resource Evidence State
Computational Optimization Evidence State
Economic Evidence State
Strategic Value Evidence State
Sustainability Evidence State
Value Attribution Evidence State
External Constraint Evidence State
Evidence Competence Record
Evidence Relevance State
Evidence Materiality State
Evidence Completeness State
Evidence Coverage State
Evidence Granularity State
Evidence Scope Alignment State
Evidence Temporal Alignment State
Evidence Configuration Alignment State
Evidence Scale Alignment State
Evidence Environment Alignment State
Evidence Normalization Record
Evidence Comparability State
Evidence Aggregation Record
Evidence Weighting Record
Non-Compensable Evidence Record
Evidence Conflict Record
Evidence Reconciliation Record
Evidence Uncertainty State
Evidence Confidence State
Evidence Gap Record
Critical Decision Evidence Gap
Known Unknown Record
Evidence Freshness State
Evidence Expiration State
Evidence Drift State
Evidence Provenance Record
Evidence Traceability Record
Evidence Integrity State
Evidence Dependency Record
Evidence Independence State
Evidence Corroboration State
Decision Evidence Matrix
Decision Evidence Profile
Decision Evidence Baseline
Decision Evidence Change Record
Decision Evidence Trend
Decision Evidence Scenario
Decision Evidence Sensitivity State
Decision Readiness State
The principal output is:
Governed Decision Evidence State
95. Critical Distinctions
DECM preserves the following distinctions:
Available Evidence ≠ Decision-Ready Evidence
Evidence Availability ≠ Decision Relevance
Evidence Volume ≠ Evidence Completeness
Evidence Scope ≠ Decision Scope by default
Pilot Evidence ≠ Scale Evidence by default
Historical Evidence ≠ Current Evidence by default
Observed Evidence ≠ Projected Evidence
Normalized Evidence ≠ Original Evidence
Evidence Compression ≠ Evidence Erasure
Evidence Aggregation ≠ Evidence Agreement
Repeated Evidence ≠ Independent Evidence
Evidence Conflict ≠ Evidence Failure
Unknown ≠ Neutral
Consolidation ≠ Certainty Creation
One Metric ≠ Decision Evidence
Dashboard Completeness ≠ Governance Completeness
High Technical Performance ≠ High Operational Value
Activity ≠ Productivity
Productivity ≠ Value
Cost ≠ Value
Evidence of Capability ≠ Evidence of Permission
Decision Evidence Consolidation ≠ Lifecycle Decision
Decision-Ready Evidence ≠ Decision Authority
96. Cross-Architecture Boundary
DECM governs consolidation of evidence for VEGA™ lifecycle decisions.
It does not replace the governance domains from which that evidence originates.
VGS governs Value.
XGS governs execution.
IPS governs Intelligence Productivity.
RGS governs resource allocation.
COS governs Computational Optimization.
IES governs Intelligence Execution Economics.
SVGS governs Strategic Value.
ISS governs Intelligence Sustainability.
VAS governs Value Attribution.
DGS governs lifecycle Decision Governance.
HAGA™ governs Harm.
LIGA™ governs Liability.
Relevant Accountability architectures govern Accountability.
Relevant identity architectures govern identity.
VALIDOS™ may govern validation methodology.
ADIT® may govern broader evidence and auditability.
Relevant agent and autonomous-system governance architectures may govern authority, permission, delegation, escalation, and Human Override.
DECM consolidates relevant governed states from these domains only where they are material to the Decision Governance Object.
97. Canonical Boundary
DECM begins when an intelligence lifecycle decision requires evidence from multiple governed domains.
DECM governs:
Decision Evidence Objects,
evidence boundaries,
decision scope,
decision horizons,
decision context,
Decision Question alignment,
Evidence Source Identification,
source competence,
Value evidence,
execution evidence,
productivity evidence,
resource evidence,
Computational Optimization evidence,
economic evidence,
Strategic Value evidence,
sustainability evidence,
Value Attribution evidence,
external constraint evidence,
evidence relevance,
materiality,
completeness,
coverage,
granularity,
scope alignment,
temporal alignment,
configuration alignment,
scale alignment,
environment alignment,
normalization,
comparability,
aggregation,
compression,
weighting,
Non-Compensable Evidence,
positive evidence,
negative evidence,
conflicting evidence,
reconciliation,
irreconcilable evidence,
uncertainty,
confidence,
Evidence Gaps,
Critical Decision Evidence Gaps,
Known Unknowns,
freshness,
expiration,
drift,
updates,
versioning,
provenance,
traceability,
integrity,
Selective Evidence Risk,
Evidence Dominance Risk,
Metric Dominance Risk,
Dashboard Illusion,
duplication,
dependency,
independence,
corroboration,
Decision Evidence Matrices,
Decision Evidence Profiles,
baselines,
change,
trends,
scenarios,
Observed versus Projected Evidence,
sensitivity,
threshold readiness,
Decision Readiness,
handoff,
and reassessment.
DECM does not independently determine:
Continuation Decisions,
Scaling Decisions,
Migration Decisions,
Retirement Decisions,
Harm,
Liability,
Accountability,
legal permission,
or Decision Authority.
DECM ends when the relevant evidence has been represented as a:
Governed Decision Evidence State
for subsequent Continuation Decision Governance.
98. Use Case 1 — Every Department Has a Different Answer
An organization must decide whether to continue a large AI deployment.
The technical team reports strong model performance.
Operations reports useful outputs.
Finance reports rising costs.
Infrastructure reports increasing compute demand.
Strategy identifies substantial long-term capability Value.
Dependency analysis identifies growing reliance on one provider.
Each department has evidence.
But no single evidence source represents the lifecycle decision.
DECM consolidates the governed evidence while preserving:
the different domains,
their confidence,
their time horizons,
their conflicts,
and their limitations.
The result is not a forced yes-or-no decision.
It is a:
Governed Decision Evidence State
from which continuation can subsequently be evaluated.
Many Evidence Sources ≠ One Governed Decision State.
99. Use Case 2 — The Dashboard Is Green, but the Evidence Is Not Decision-Ready
An AI program has an executive dashboard showing:
high uptime,
high user adoption,
fast response times,
and improving technical benchmarks.
Management considers the deployment ready for large-scale expansion.
DECM identifies that the dashboard contains little evidence concerning:
validated operational Value,
cost per validated outcome,
Failure Spend,
dependency sustainability,
Human–AI contribution,
and infrastructure requirements at the proposed scale.
The dashboard may accurately represent the metrics it contains.
But the evidence set is incomplete for the scaling question.
DECM therefore establishes:
Evidence-Limited Decision Readiness
and identifies the missing decision evidence.
Dashboard Completeness ≠ Governance Completeness.
100. Canonical Closing Statement
A lifecycle decision can be only as governable as the evidence brought into it.
The evidence may already exist across dozens of systems.
It may exist in technical metrics, financial records, productivity measurements, infrastructure data, Value assessments, sustainability states, and attribution records.
But distributed evidence is not yet decision evidence.
It must be connected to the same Decision Governance Object.
It must refer to the relevant scope.
It must remain sufficiently current.
Its conflicts must remain visible.
Its uncertainty must survive consolidation.
And its provenance must remain traceable.
Available Evidence ≠ Decision-Ready Evidence.
One Metric ≠ Decision Evidence.
Pilot Evidence ≠ Scale Evidence by default.
Consolidation ≠ Certainty Creation.
Dashboard Completeness ≠ Governance Completeness.
Decision-Ready Evidence ≠ Decision Authority.
DECM does not determine what the organization should ultimately authorize.
It establishes whether the evidence required to govern that choice is actually ready.
DECM turns fragmented evidence about intelligence into a coherent decision foundation without allowing consolidation to erase the uncertainty, boundaries, or operational reality contained in the evidence itself.