Analytic Governance
Exists to de-risk high-cost research when analytics are optimized for Insight Compliance, not decisions.
Prevents failure before it becomes an irreversible strategic mistake. Includes scoping, decision logic, and risk. Not just execution.
The risk compounds in any high-cost research, pricing, portfolio design, innovation, or strategy, where best-practice methods break under real constraints.
Pricing research is a common example.
When price and pack size are confounded, models can produce internally valid but economically incoherent outputs, such as inverted demand curves.
Those outputs distort decision-making, and once deployed, can drive real-world outcomes the analysis was never fit to support. Margin loss isn’t the model’s failure. It is the downstream cost of relying on curiosity-grade evidence where decision-grade evidence was required.
Most analytics fail quietly.
Not because the data is bad, but because the work passes methodological review while failing the decision it was meant to inform.
That’s Insight Compliance: research designed to satisfy process, not reduce decision risk.
Analytic Governance exists to surface those failures while change is still possible.
Insight Compliance is how organizations spend millions on research and still avoid making a decision.
Every strategy-worthy research project is governed by three non-negotiables.
Resource Allocation Clarity
The objective must be a decision, not a topic. If the decision isn’t explicit, the data can’t reduce uncertainty and should not proceed.
Business Model Alignment
The design must align with how the business makes money, or intends to. Insights that cannot be implemented fail the governance test.
Critical Modeling
The model must fit the decision, not the method library. Models that are not boardroom-ready, pressure-tested and purpose-built do not qualify as decision-grade evidence.
When Analysis Must Survive Deployment
Governance becomes necessary when analytic outputs will be used in live pricing, portfolio, or launch decisions, not just reviewed internally.
When Best Practices Break
When standard models no longer map cleanly to customer behavior or constraints, governance determines whether methods must be redesigned, or abandoned.
When the Cost of Being Wrong Is Material
Governance is required when analytic failure cannot be absorbed quietly and correctness matters more than speed.
Case Snapshot: Snack Brand Price Hike
Rising ingredient costs forced a price increase. Standard pricing models produced inverted demand curves. This signals that the analysis was no longer decision-safe.
By correcting the pack-size confound, the analysis returned to decision-grade territory, where pricing options could be evaluated with confidence. More Cases