Decision Governance & Management
Govern every high-stakes decision, and run decisions as a managed, measurable process
Treat decisions as a managed asset, not one-off events. Standardize how choices get framed, modeled, and reviewed, then put a governance layer over the decisions your people and AI systems make every day: enforce policy before execution, route approvals, map accountability, and close every decision with a defensible audit trail and a tracked outcome.
Challenges We Solve
Governance gaps that structured controls and audit trails eliminate.
Decisions Made Without Guardrails
High-stakes decisions execute before anyone checks them against policy. Enforce policy guardrails at decision time, so violations are blocked or escalated, not discovered in an audit.
No One Can Say Who Decided
When a decision goes wrong, accountability is unclear. Map every decision to its owner, approver, inputs, and rationale so responsibility is never ambiguous.
Every Decision Is Ad Hoc
The same kinds of decisions get made differently every time, depending on who's in the room. Standardize decision framing and method so quality doesn't depend on the individual.
Undocumented Decisions, No Institutional Memory
Decisions live in inboxes and slide decks with no record of why, so organizations repeat the same debates. Capture the model, assumptions, and approvals behind each decision in an immutable, replayable trail you can learn from.
Assumptions Go Unchallenged
Decisions rest on assumptions no one stress-tests. Run sensitivity and scenario analysis to see which assumptions actually move the outcome, and focus debate where it matters.
Drift Goes Undetected, Outcomes Go Unreviewed
Policies say one thing while practice drifts somewhere else, and no one compares predictions to reality. Detect decision drift continuously and track realized outcomes against forecasts.
Use Cases
Real governance scenarios powered by DecisionLedger.
Uses policy compliance guardrails to enforce approval thresholds across the business, ensuring no high-value or high-risk decision executes without the required sign-off.
Eliminated out-of-policy decisions with automated pre-execution enforcement
Relies on decision traceability and accountability mapping to reconstruct exactly how a contested decision was made, who approved it, and what evidence supported it.
Reduced decision-defense preparation from weeks to minutes
Runs decision drift detection across the organization to find where actual decisions are diverging from approved policy before it becomes a systemic problem.
Caught governance drift early and re-aligned practice to policy
Uses the decision readiness assessment and trade-off analysis to standardize how the leadership team frames and compares major choices before they reach the table.
Cut decision cycle time while improving the quality of options considered
Runs scenario planning and assumption sensitivity models to identify which assumptions actually drive a strategic bet, focusing debate where it matters.
Re-prioritized analysis onto the few assumptions that moved the outcome
Maintains a decision portfolio with traceable rationale, then reviews outcomes against forecasts to learn which decision patterns consistently pay off.
Built an institutional memory that reduced repeated debates
Measurable Impact
Based on platform benchmarks across early adopters.
Policy Enforcement
Accountability
Audit Readiness
Decision Consistency
Assumption Testing
Outcome Review
A Governance Layer and System of Record for Every Decision
Standardize framing, apply rigorous methods, enforce policy before execution, and learn from every outcome.
Decision Framing
Structure options, criteria, and constraints consistently so every decision starts from a clear, shared definition.
Method Library
Apply the right decision science method to each choice, from weighted scoring and trade-off analysis to scenario and sensitivity modeling.
Policy Enforcement
Check every decision against codified policy before it executes. Block, escalate, or approve based on configurable thresholds and authority.
Accountability Mapping
Tie each decision to its owner, approvers, inputs, and rationale so you can always answer who decided, and why.
Immutable Audit Trail
Capture and replay the full lineage of any decision, from inputs and model run to approval and outcome, for regulators and the board.
Outcome Feedback Loop
Track realized outcomes against predictions to measure and improve decision quality over time.
Connects With
Part of 150+ native integrations across CRM, marketing, finance, HR, ecommerce, and analytics
Salesforce
HubSpot
Stripe
Shopify
Google Analytics 4
Workday
QuickBooks
Snowflake
Slack
Zendesk
GitHub
Meta Ads
Mailchimp
NetSuite
Jira
Power BISalesforceHubSpotStripeShopifyGoogle Analytics 4WorkdayQuickBooksSnowflakeSlackZendeskGitHubMeta AdsMailchimpNetSuiteJiraPower BIFeatured Models
Pre-built decision models ready to run with your data.
Algorithmic Impact Assessment
Formal AIA as quantitative decision model with statistical bias analysis, EU AI Act article scoring, and remediation roadmap
Assumption Sensitivity Model
Identifies which assumptions most influence the outcome and how changes to them could materially alter the decision.
Decision Accountability Mapping
Assigns clear ownership and escalation paths for decisions using RACI governance analysis. Validates accountability structures, detects gaps and concentration risks, scores coverage completeness, and generates remediation recommendations.
Decision Drift Detection
Identifies when decisions diverge from original intent over time.
Decision Portfolio Balance Model
Detects over-concentration of risk across decisions. Analyzes the aggregate portfolio of active decisions to identify clustering, correlation, and concentration risks that could amplify failures. Computes Herfindahl-Hirschman Index, category and risk-level concentration, timeline clustering, risk factor correlation, and portfolio balance scoring with rebalancing recommendations.
Decision Readiness Assessment
Determines whether a decision is truly ready to be made by evaluating data completeness, risk exposure, and unresolved dependencies.
Decision Traceability
Decision Traceability Model - Links inputs, assumptions, approvals, overrides, and outcomes into a directed traceability graph. Scores completeness of each link, detects broken chains, identifies orphaned decisions, flags stale assumptions, and computes override-to-decision ratios for governance and audit compliance.
Policy Compliance Guardrails Model
Ensures HR decisions align with organizational policies and legal requirements for selected US states. Evaluates termination, hiring, compensation, leave, accommodation, and discipline decisions against federal and state employment laws.
Scenario Planning & Stress Testing
Model multiple future scenarios and stress test decisions against adverse conditions. Quantifies upside, downside, and base-case outcomes with probability-weighted expected values. Computes Value at Risk (VaR), Monte Carlo confidence intervals, scenario comparison matrices, sensitivity analysis, and risk-adjusted recommendations.
Strategic Option Viability Model
Compares strategic paths with quantified upside, downside, and execution risk. Evaluates multiple strategic options through financial, operational, and risk lenses to identify the most viable path forward. Computes expected monetary value, risk-adjusted EMV, asymmetry ratios, real options value, viability composite scores, dominance analysis, breakeven probabilities, and Monte Carlo confidence intervals.
Trade-off Analysis Model
Explicitly surfaces opportunity cost between competing options. Quantifies what you gain and what you give up for each alternative using multi-criteria comparison with explicit cost-of-not-choosing analysis.
Model Provenance Attestation
Verifies model lineage, training data attestation, and supply-chain trust.
Causal Decision Intelligence
Builds causal graphs from organizational data to distinguish correlation from causation in business metrics. Identifies true drivers of outcomes, estimates intervention effects, and prevents costly decisions based on spurious correlations.
How It Works
Three steps to structured, auditable decisions.
Frame & Set Policy
Structure the choice: options, criteria, constraints, and stakeholders. Codify the policies, thresholds, and approval authority that govern it, and assess decision readiness before investing in analysis.
Model, Compare & Enforce
Apply the right decision method, run scenarios, and stress-test assumptions. Every decision and model run is checked against policy before it executes: compliant decisions proceed, violations are blocked, flagged, or routed for human approval.
Record, Audit & Learn
Capture the inputs, rationale, approvers, and outcome of each decision in an immutable trail. Replay any decision to prove it followed policy, then track the outcome against forecast to improve the next one.
When a regulator, board member, or plaintiff asks how a decision was made and who approved it, can you answer in minutes with evidence, or does decision quality still depend on who happened to be in the room?
Policy documents in wikis
Written policies no system actually enforces at decision time
Email and Slack approvals
Approvals scattered across tools with no link to the decision or its evidence
Manual audit reconstruction
Weeks of digging to prove how a single decision was made
GRC tools bolted on after
Compliance checks that run after decisions execute, not before
Decision-by-meeting
Outcomes that depend on who attends and who speaks loudest
One-off spreadsheets
Bespoke analysis with no shared method or memory