Full Portfolio Transformation · 6 to 8 Months · Executive Board
Your data department runs as a cost center: funded every year, reviewed almost never, and rarely asked for a return. That translation gap compounds quarterly: in infrastructure expansions that are not financially justified, in legacy initiatives that never get decommissioned, and in an engineering team that works exceptionally hard but cannot prove its yield to the boardroom.
The Data Capital Program is a comprehensive, deeply embedded integration. Over six to eight months, we permanently install five operational instruments across your executive workflow, aligning your technology footprint directly with your financial margin.
Scope
Six to eight months, phase-gated, ending with team handover
Profile
Executive Board (CEO, CFO, Head of Data)
Deliverables
Three-Year Compass, Portfolio Reset, Capacity Rhythm, Short Validation Cycles, Financial Dashboard
30 minutes. No slides. Bring the last conversation where your CFO asked about data ROI and nobody had a number.
01
TL;DR
A data strategy becomes real the day it survives contact with the quarterly calendar: when the budget review, the initiative approval, and the kill decision all run on the same numbers without anyone pushing.
A data strategy becomes real the day it survives contact with the quarterly calendar: when the budget review, the initiative approval, and the kill decision all run on the same numbers without anyone pushing. That requires two things no document can carry on its own: financial instruments that make the portfolio legible to a CFO, and an operational rhythm that keeps those instruments running long after any advisor has left the building.
The Data Capital Program is built around that requirement. I operate inside your decision cadence for the full term, then exit with the instruments transferred and the rhythm running independently. Without instruments, a strategy is an opinion. With them, every data capital decision is a clear number the board can audit.
02
TL;DR
A Three-Year Compass, a Portfolio Reset, a Capacity Rhythm, Short Validation Cycles, and Three Numbers on One Page. Each one transfers to your team before the engagement ends.
Your long-term data capability compass, anchored in an audited present-state cost baseline. It defines exactly what your portfolio costs today, what it returns to the margin, and what it needs to become. Every new data initiative checks against this baseline before authorization.
A rigorous financial evaluation of your entire accumulated footprint. Every active data asset is assessed for carrying cost versus business yield. Kill decisions are made based on financial realities rather than departmental politics. What earns its place stays; what fails, exits.
Your engineering team's time allocation split cleanly across building new capabilities, launching initiatives, and maintaining legacy stack elements. This capacity is tracked and reported directly to the CEO and CFO in standard financial language. "The team is at capacity" stops being a vague feeling and becomes an auditable trend line.
Structured explore-and-exploit cycles that force new data or AI initiatives to prove their frontline value at weeks three, five, and seven before full capital investment is unlocked. This eliminates six-month engineering builds that occur before anyone verifies if the front line needs the tool.
Your critical metrics: frontline workaround costs (FTE Debt), per-product background carrying weight, and true team capacity splits, integrated directly into your bi-weekly executive management cadence. Your CFO reads the data portfolio like a traditional P&L line. Your Head of Data presents without a translator.
03
TL;DR
Phase 1 is the baseline diagnostic. Phase 2 builds the compass and installs the initial instruments. Phase 3 completes installation and transfers governance to your team. Each phase has a gate.
The complete Hidden Cost Recovery diagnostic. We isolate your exact frontline FTE Debt, calculate background asset weights, and set the stop-gate threshold before Phase 2 begins.
We build your three-year capability compass, lock in the present-state cost baseline, and integrate the initial capacity tracking models into your leadership workflow.
Full instrument installation and organizational governance transfer. Short validation cycles run natively on all new requests, the portfolio reset is executed, and data capital allocation choices are driven by a live executive financial dashboard.
04
TL;DR
The engagement ends when your organization can run every instrument without me in the room. Your Head of Data leads the portfolio review. Your CFO evaluates the dashboard without a translator. Your CEO makes data capital allocation decisions based on audited numbers.
The engagement terminates the exact week your organization can execute every instrument without an external advisor in the room. Not an arbitrary calendar date, and not a deliverable count. When your Head of Data leads the portfolio review fluently, your CFO evaluates the data dashboard without a translator, and your CEO executes resource allocation choices based on audited numbers, the transformation is complete and the role ends.
05
TL;DR
Each phase is priced separately and gated. The terms for the next phase are agreed only after the previous one delivers, and each gate includes the condition under which I recommend stopping.
Each phase is priced separately and gated: the terms for the next phase are agreed only after the previous one delivers, and each gate includes the condition under which I recommend stopping. You control the capital deployment at every stage, in writing, before that stage begins.
06
TL;DR
Not for companies still building their first pipelines. This is for CEOs and CFOs at Series B to E companies where the infrastructure is operational, the data team is working, and the problem is that nobody in the executive suite can read what it costs or what it returns.
The Data Capital Program assumes a functioning data team and an established data portfolio. The problem it solves is not infrastructure. It is the absence of a shared financial language between the engineering layer and the executive layer. If you are still hiring your first data engineer or deciding on a warehouse, this is not the right moment. Come back when the function is running and the CEO can't explain to the CFO what it costs to maintain it.
Start with Phase 1. In the first month, we map your operational reality and hidden payroll friction. From there, the data tells us whether the full program is justified.