Capability Compounding

Quick wins fund bigger wins. Each sprint unlocks the next level.

The mistake: trying to plan a 2-year AI transformation. The reality: start small, prove value, compound.

The Pattern

1. Data Analysis Sprint ($30K) → Reveals what's possible, quantifies opportunities
2. Build Sprint ($30K) → Delivers working PoC, validates approach
3. Implementation (scoped from learnings) → Scale what works

Each phase generates data that informs the next. No big upfront bets.

Why This Works

• Low risk: $15-30K experiments, not $500K commitments
• Data-driven: Each sprint produces evidence for the next decision
• Compounding: Infrastructure from early sprints accelerates later work

Contrarian To

"We need a comprehensive AI strategy before we can start"

Example

Even if Sprint 1 finds nothing actionable, you now have:

• Queryable data warehouse
• Mapped entity relationships
• Foundation for future tooling

The investment isn't "solve problem X" - it's "build the substrate that makes solving future problems cheaper."