Who this page is for
- Chief Digital Officers and Chief Data Officers running enterprise retail or CPG transformation programs
- Chief Information Officers weighing AI investment against the next budget cycle
- Chief Marketing Officers asking why agentic personalization isn't moving the needle yet
- VPs of Transformation building the business case for board approval
- PE / VC partners evaluating retail or CPG portfolio readiness
What I help with
1. Building the AI investment case the board will fund
ROI alone justifies projects. CODN — the Cost of Doing Nothing framework — justifies programs. CFOs are asking "what does it cost us to not do this?" Most CDOs aren't ready. I help bridge that with a defensible four-component CODN model — margin erosion, execution lag, talent flight, optionality decay — bounded and pressure-tested against external benchmarks.
2. Retrofitting the data lake for agent consumption
Three years ago, every Tier 1 retailer's transformation budget had a data lake line item. Now the conversations have moved on, and the lake has gone quiet. AI agents need clean, queryable, contextually-tagged data more than your dashboards ever did. The retrofit — semantic abstraction layer + latency tiering + first-class lineage — is where most of the actual AI lift lives.
Read: The $40M data lake nobody asks about anymore →
3. Closing the omnichannel measurement loop
Most omnichannel measurement stacks are dashboards in a trench coat. Closing the loop requires real-time signal ingestion, AI-native attribution, and an action layer that does something with the signal. I've shipped this against $50M-of-new-revenue scale.
4. AI orchestration for plan-to-cash and CPG trade promotion
Trade promotion has the data, the friction, and the margin to justify agentic deployment — yet CPGs keep deploying AI on personalization instead. Plan-to-cash cycle modernization with AI orchestration cut time-to-market 40% on a recent global CPG engagement. See the case →
5. Agentic operations for inventory, demand, and store ops
RFID got dismissed as 2010s tech. Agentic operations need real-time inventory state more than any prior workload did. RFID is back, quietly. Demand forecasting has a signal problem, not a model problem. The store-ops AI conversation is just starting.
Engagement shapes
- Fractional advisor — embedded in the leadership team, 10–20 hrs/week, 3–9 months. Best fit when the AI program needs a senior pattern-matcher, not another headcount.
- Transformation sprint — defined deliverable, 6–12 weeks. Best fit for a board-grade business case, a CODN audit, a measurement-stack rewire, or an AI-orchestration target map.
- Expert call — 60–90 min single session, written summary deliverable. Available through GLG, AlphaSights, Guidepoint, Third Bridge, or directly.
Engagements are delivered through Stravonvale, the advisory firm I co-founded with Josh Carter.
Selected retail / CPG case studies
- Fortune 500 omnichannel — $50M new revenue in 18 months
- Global CPG — plan-to-cash modernization with 40% TTM cut
- Global retail group — multi-workstream AI transformation business case
Recognition
- RETHINK Retail Top Retail Expert, 2025 and 2026
- RETHINK Retail Top AI in Retail Leader, 2026
Get on the calendar
Book a 30-minute discovery call →
Or read my Retail POV stream first. Same person, same principles, different audience.