Architecture governance should operate through evidence

Architecture governance is useful when it improves decisions and makes system risk visible. It becomes harmful when every change waits for a central meeting that lacks the context to make the decision. Match governance to impact Classify decisions by reversibility, blast radius, data sensitivity, external obligation, cost, and number of affected teams. Local and reversible choices should stay with the owning team. Cross domain contracts, identity boundaries, regulated data, and difficult to reverse platform choices deserve broader review. Publish the thresholds. Teams should know before design begins which evidence is required and who has decision authority. Provide executable standards A standard should include its purpose, scope, owner, required controls, reference implementation, validation method, exception path, and review date. Where possible, encode it in platform defaults, policy tests, templates, and CI checks. A slide deck that engineers must manually interpret will drift. Use a small number of principles to guide cases a standard does not cover. Keep a catalogue of approved patterns and their boundaries, but avoid presenting patterns as universal solutions. Review evidence, not presentation quality Ask for context, alternatives, threat model, reliability objectives, data flows, operating model, migration plan, and measurable consequences in proportion to risk. Link the decision record and resulting controls to the system inventory. NIST’s Secure Software Development Framework demonstrates how governance outcomes can be organised as practices and tasks rather than tied to one implementation. Architecture governance can use the same approach: state the required outcome and provide evidence backed ways to satisfy it. Manage exceptions as information Exceptions need an owner, rationale, compensating controls, expiry, and review trigger. Repeated exceptions may indicate an unrealistic standard or a missing platform capability. Analyse them as product feedback. Measure review lead time, recurring findings, exception age, control adoption, and production outcomes. Do not optimise for the number of approvals completed. The purpose of governance is distributed decision quality. Central architects should supply context, patterns, and challenge for high impact choices while platforms and automated evidence make the safe path routine. Create a decision rights model Define who recommends, who supplies required expertise, who decides, and who must be informed for each class of change. A service owner may decide a reversible internal library choice. A cross domain identity contract may require security and platform input with an accountable architecture owner. Clear decision rights prevent both central bottlenecks and decisions made without affected parties. Time box review according to risk. Publish response objectives and an escalation path. If governance cannot review within the delivery window, teams will either wait unnecessarily or bypass it. Build an evidence package For higher impact changes, collect system context, data flows, trust boundaries, objectives, alternatives, dependency and failure analysis, cost, migration sequence, and operating ownership. Reuse evidence already generated by code, infrastructure plans, threat models, tests, service catalogues, and production telemetry. Evidence must correspond to the actual release. A diagram from an early proposal is not proof that deployed network or identity controls match it. Link evidence to versions and automate drift detection where possible. Maintain the standards portfolio Each standard needs an owner and review trigger such as provider change, repeated exceptions, incident evidence, or new regulation. Mark obsolete standards clearly and provide a migration path. Overlapping standards should be consolidated so teams do not have to interpret conflicting authority. Effectiveness checklist Measure decision lead time, percentage resolved at the appropriate level, repeated review findings, exception age, adoption of paved paths, and incidents related to governed risks. Sample approved systems to verify evidence and real operation still align. Effective governance reduces surprise and repeated analysis; it does not maximise the number of committees involved.