Decision Log

A Decision Log creates organizational memory. It records what was decided, who had the authority to decide, why the decision was made, what evidence was used, what tradeoffs were accepted, how the decision was communicated, and when it must be reviewed.

The object is reusable across three company profiles: 500+, 5,000+, and 10,000+ employees.

1. Human guide - plain-language guidance for executives, transformation leaders, product, technology, risk, operations, data, and AI leaders.
2. Template artifact - a downloadable decision log that teams can use during strategy, planning, governance, delivery, and AI scaling.
3. Machine-readable schema - fields, scoring logic, validation rules, mappings, prompts, review triggers, and version metadata.
4. Guided skill - an AI-assisted workflow that classifies decisions, detects missing accountability, creates decision summaries, and flags stale or conflicting decisions.

AI makes weak decision memory dangerous. When decisions are scattered across meetings, chats, documents, dashboards, and system tickets, AI cannot safely reason over enterprise intent. A decision log becomes the source of truth for what the organization actually chose and why.

Score each decision record from 0 to 4.

Decision memory score: average of ownership clarity, decision authority, evidence quality, rationale quality, impact mapping, communication completeness, review discipline, and AI boundary clarity.

High-risk flag: any material decision with a score below 3, AI involvement above Level 1, or missing control owner when risk is medium, high, regulated, or critical.

Every material decision needs one accountable decision owner. Committees can advise, review, or approve. They cannot replace accountable ownership.

A 500+ employee company usually moves fast, but decision memory often lives in leaders, Slack, Teams, and recurring meetings. The log should be lightweight enough to use, but strong enough to prevent ambiguity.

500+ design principle: keep the decision log simple, visible, and owner-led. The goal is not bureaucracy. The goal is to stop decisions from disappearing into tribal memory.

• Use one shared decision log for leadership, product, operations, technology, and AI initiatives.
• Require a decision owner, rationale, communication path, and review date for any material decision.
• Log AI-assisted decisions even when AI only drafted, summarized, or recommended.
• Review active decisions monthly during operating reviews.
• Mark superseded decisions clearly instead of deleting history.

A 5,000+ employee company needs decision memory across functions. The log should connect business direction, technology execution, risk input, data evidence, funding, product priorities, and platform dependencies.

5,000+ design principle: make the decision log the shared memory layer between business strategy, product delivery, technology, data, risk, and governance.

• Connect major decision records to roadmap epics, governance forums, architecture decisions, risk reviews, and operating metrics.
• Require options, rationale, evidence, decision owner, implementation owner, and affected systems for material decisions.
• Use the decision log in quarterly business reviews and portfolio reviews.
• Require AI decision boundary classification for AI-assisted or AI-enabled decisions.
• Use supersession history to reduce conflicting direction across departments.

A 10,000+ employee company needs an enterprise decision ledger. Local teams need speed, but the enterprise needs auditability, legal and regional awareness, risk traceability, AI boundary control, and decision lineage.

10,000+ design principle: federate decision-making, but centralize decision memory, evidence standards, AI boundaries, and supersession history.

• Maintain a federated decision ledger by business unit, function, region, legal entity, platform, initiative, and risk tier.
• Connect decision records to policy, controls, model registry, architecture repository, data catalog, roadmap, and audit evidence.
• Require formal evidence packs for high-impact, regulated, customer-facing, employee-impacting, financial, or AI-autonomous decisions.
• Create decision conflict detection across related initiatives and platforms.
• Use explicit supersession and retirement rules so old decisions do not remain operationally active.

• Classify this decision by type, LPM layer, risk level, and company profile.
• Identify the decider, decision owner, implementation owner, consulted roles, informed roles, and control owner if needed.
• Summarize the context, options considered, chosen option, rationale, evidence, assumptions, and tradeoffs in plain language.
• Detect whether AI influenced the decision and classify the AI decision boundary from Level 0 to Level 5.
• Find missing fields that would prevent this decision from being approved, implemented, or audited.
• Generate an executive decision summary, a team communication note, and a governance-ready record from the same object.
• Detect stale, superseded, conflicting, or duplicated decisions across an initiative, function, or enterprise portfolio.

• Decision reaches review date.
• Decision owner changes role or leaves the organization.
• AI begins influencing, recommending, routing, or executing work related to the decision.
• A downstream system, data source, policy, workflow, model, agent, or vendor changes.
• A risk, control, legal, compliance, privacy, or security issue appears.
• A newer decision supersedes the existing decision.
• Measured outcomes show the decision is not producing intended value.

Decision Log

A reusable LPM template for turning decisions into durable organizational memory. Use it to capture ownership, authority, rationale, evidence, tradeoffs, downstream impact, AI involvement, and review triggers before decisions become scattered across meetings, chats, decks, and systems.

A decision log is not meeting minutes. It is an operating control. It should be short enough that teams actually use it and structured enough that the organization can later understand, audit, automate, and improve decisions.