Implement

Implement

One record, many outputs.

A concept, not a product. It will be built when the pilots show which parts of the method earn automation.

GOVBRM platform architecture concept

Status: draft v0.1, GOVBRM original, Hypothesis.. Not to be built yet.

Why this document exists

The method runs today on twenty canvases stored on the practitioner's own device, exported and filed by hand into the organisation's records. That is deliberate. This document records what a platform would be, so that pilot evidence can be tested against it, and states why building it now would be premature.

The concept in one sentence

One demand record producing multiple governance outputs.

A request is captured once. Everything the organisation's governance later needs, the privacy assessment, the equality assessment, the transparency record, the security case, the commercial case, the appraisal, the service assessment, the architecture review and the AI assurance record, is generated from that one record and its evidence, rather than re-keyed into separate forms by separate people at separate times.

The flow

StepWhat happensCanvases todayOutput of the step
AI requestA request or opportunity is captured as facts01, 03Demand record opened with an identifier
ShapeThe need beneath the request, the value range, the counterfactual, the route02Need sentence, value hypothesis, route
EvidenceReadiness scored on what was seen04Readiness score, weakest dimension
Risk and autonomyFlags, floors, exposure rating; the lowest rung that solves the task; the four agent questions05, 11Risk rating, lane, rung, accountable role
RouteLane and gate sequence set by consequence02, 10Lane, playbook match, gate plan
Governance outputsThe record is compiled into each receiving process's input05, 09, 11, 12, 13, 14Draft inputs for: data protection impact assessment, equality assessment, transparency record (Algorithmic Transparency Recording Standard or equivalent), security assurance, commercial and procurement, appraisal (Green Book or equivalent), Service Standard assessment, architecture review, AI assurance (ISO/IEC 42001, NIST AI RMF or equivalent)
DecisionRank and Commit gates; a named owner and a committed number06, 07, 08, 09Gate records with reasons
DeliveryBuild under the rung and controls committed12, 13Supplier conditions, prompt governance, build status
AdoptionWho changes how they work and how it is seen15, 16, 17Adoption measures, task changes, released time
BenefitsThe evidence ledger fills18Measured value with confidence
Value Realisation ReviewMeasured value beside the committed number; Scale, Continue, Adjust, Stop19Review decision, countersigned
LearningWhat the front door must learn10, 20Playbook and roadmap changes
New demandThe loop closes; learning reshapes the next request01Next demand record

Data model sketch

Entities, with the relationships that matter. Fields are illustrative, not a schema.

EntityKey fieldsRelationships
DemandRecordidentifier, requester role, date, need sentence, route, lane, statushas many CanvasVersions, GateDecisions, GovernanceOutputs, Handoffs; belongs to Portfolio
CanvasVersioncanvas number and title, version, signed by role, signed date, contentbelongs to DemandRecord; immutable once signed
ValueHypothesisbenefit type, unit, lower bound, upper bound, conditions, owner rolebelongs to DemandRecord; measured by BenefitReading
RiskFlagflag, floor, exposure rating, accountable role, data and population affectedbelongs to DemandRecord; feeds GovernanceOutput
AutonomyAssessmentrung, systems touched, decisions taken alone, human review, evaluation planbelongs to DemandRecord
GateDecisiongate (Request, Shape, Rank, Commit, Build, Review), decision, reasons, decided by role, datebelongs to DemandRecord
GovernanceOutputtype (privacy, equality, transparency, security, commercial, appraisal, service, architecture, AI assurance), generated fields, source canvas versions, receiving reference, statusbelongs to DemandRecord; compiled from CanvasVersions by a Compiler rule set
CompilerRulegovernance output type, target field, source canvas and field, transformation, jurisdictionmany per GovernanceOutput type; versioned; the cross-framework compiler
Ownerrole, not person, scope of sole decisionattached to DemandRecord from Commit; a person is resolved from the client's directory at run time, never stored in the record
BenefitReadingdate, measured value, confidence, measurement owner role, baseline referencebelongs to ValueHypothesis
ReviewDecisiondecision, the two facts that decided it, next review date, countersigned by rolebelongs to DemandRecord
Playbookrequest category, routing rules, lane defaults, learned from ReviewDecisionsbelongs to Portfolio
Portfolioorganisation unit, heatmap position, value map quadrant, roadmap horizonhas many DemandRecords

Design rules. Every signed canvas is immutable; changes create a new version. Every governance output records which canvas versions it was compiled from. Every decision records the role that took it and the reasons. The record holds roles, not names.

Integration points

All Hypothesis; none built.

PointDirectionPurpose
Service management or intake platformInRequests arrive from the channel the organisation already uses; the record is opened, not duplicated
Records management systemOutSigned canvas versions and gate records filed under the organisation's retention schedule
Privacy and equality assessment toolingOutPre-filled assessment drafts from the RiskFlag and DemandRecord fields
Transparency registerOutDraft transparency record entry
Security and architecture assurance workflowOutRung, systems touched, controls
Procurement and contract managementOut and inSupplier conditions out; contract reference and exit terms in
Portfolio and benefits managementOut and inCommitted numbers out; benefit readings in
Identity and directoryInRoles resolved to people at run time, with the organisation's own access control
AI management system (ISO/IEC 42001 or equivalent)OutAI inventory entry and impact assessment inputs
Model providers and AI platformsNoneThe platform never calls a model with record content by default; any assistant feature is a separate, opt-in decision with its own assessment

Privacy by design

  • Data minimisation: the record stores roles, need sentences, scores, flags and decisions. It does not store the personal data that the AI system itself will process, only the categories and populations affected.
  • The organisation is the controller of its own records. A platform would be deployed inside the organisation's own tenancy or as a processor under a data processing agreement, never as a shared pool across organisations.
  • Requester identity is held as a role and a directory reference; the record can be exported without names.
  • Immutable, versioned evidence supports audit without editing history.
  • Retention follows the organisation's schedule, set at deployment; deletion is a first-class operation.
  • Any feature that sends record content to a model provider is off by default and passes through the organisation's own AI governance before it is enabled.

Why it waits for pilot evidence

  1. The compiler rules are the product. Which canvas fields map to which governance inputs, in which jurisdiction, is exactly what a pilot must discover. Building the mapping before a pilot would encode guesses.
  2. The lanes, scales and thresholds are initial calibration, published to be argued with. Software fixes them; a pilot should move them first.
  3. The value of "one record, many outputs" depends on governance owners accepting compiled inputs. That acceptance is Not yet demonstrated.
  4. The method runs today on canvases and exports. No client has yet said that the manual path is the constraint.

Gate for starting: at least one pilot with counts of requests routed, governance outputs accepted by their owners without re-keying, and a client willing to co-design the compiler rules on its own frameworks.

Dates come to members first

Courses and certifications are announced in the GOVBRM Newsletter before anywhere else.

Join free for the essays behind the framework, the access code for the free micro-courses, and first word of every cohort. Paid membership adds the toolkit, the framework and a seat at the masterclasses.