Use Cases — Decision Failures That Break at Scale

Grain works on decision failures, not just analytics outputs. When foundational decisions—like identifying a customer—break, the impact isn't just bad data. It cascades across the entire executive team.

This page outlines the recurring decision-level use cases we see as organizations scale, and how stabilizing the root cause restores commercial authority.

Decision Framing: "Who is the customer?"

Customer Identity & Commercial Truth

At scale, customer identity fractures across systems. When Sales, Finance, and Marketing define "The Customer" differently, analytics becomes a negotiation rather than a source of truth.

The Fracture
Identity Not Governed
↓
CMO Impact
Segmentation & ROI Inconsistency
↓
CRO Impact
Account Ownership & Pipeline Distortion
↓
CFO Impact
Revenue & Forecast Inconsistency
↓
CSO / Strategy Impact
GTM & Territory Breakdown

What Changes Once This Decision Is Stabilized

  • A single, trusted customer view across functions
  • Consistent national-level rollups without breaking regional nuance
  • Reduced reconciliation and rework
  • Downstream analytics that are trusted and actually used
Related case: Enterprise entity resolution as a shared capability
Decision Framing: "Which numbers do we operate from?"

Metric Truth & Executive Alignment

Conflicting metric definitions turn planning sessions into political debates.

Result: Unreliable forecasts and eroded board confidence.

Related case: Stabilizing metric truth for executive planning
Decision Framing: "When is it acceptable to override price?"

Pricing & Margin Control

Unclear authority makes "exceptions" the rule. Ad-hoc overrides bleed margin invisibly.

Result: Silent margin erosion and failed pricing strategy.

Related case: Restoring pricing authority and margin discipline

Downstream Analytics

Advanced analytics only succeeds after these foundations are stabilized. Once the decision layer is fixed, we enable:

Whitespace Analysis: Finding growth in stabilized accounts.
GTM Prioritization: Scoring leads with trusted data.
Executive Planning: Forecasting with single-entity truth.
See how this showed up in practice →