Fix the Data.
Grow the Value.
We help PE-backed portfolio companies find and fix the data problems that erode valuation, stall AI, and slow growth.
Bad data costs you whether you sell or hold.
Most portfolio companies can't reproduce last quarter's revenue from source systems in under an hour. Finance, sales, and ops report different numbers for the same metric. Critical workflows run through spreadsheets maintained by one person. This isn't just a diligence problem. It slows every operating decision, undermines AI initiatives, and erodes the value you're trying to build.
Finance, sales, and ops all report different numbers. Close enough for a board meeting. Not close enough for real operating decisions or diligence.
Critical processes run through Excel files maintained by one person. Every growth initiative stalls while someone rebuilds the same data manually.
The operating plan says "deploy AI." The data says "not yet." Without clean, governed data, AI projects burn budget and deliver nothing.
We make your data an asset, not a liability.
Not with dashboards. With reconciled numbers, documented lineage, and a data foundation that supports real operating improvement and withstands buyer scrutiny.
Graeme Crawford
Founder and CEO
Graeme Crawford spent 20 years leading data programs at Fortune 100 scale. At Capital One, he led a cloud migration that enabled the closure of legacy data centers, saving hundreds of millions. He built a real-time web analytics platform with sub-millisecond latency that powered personalization and fraud decisioning across billions of transactions.
Before that, at IBM, he was the designated fixer for hostile recoveries and severely damaged implementations. Now he applies that same discipline to mid-market PE-backed companies building value and preparing for exit.
View LinkedIn →Built for PE timelines, not the consulting calendar.
- 12-month roadmaps that outlast the deal timeline
- Platform implementations that solve the wrong problem
- Dashboards that can't survive a follow-up question
- Junior teams running enterprise playbooks at mid-market scale
- AI projects launched on top of broken data
- 90-day sprints aligned to your value creation plan
- Fix the 10 numbers that matter most to the business first
- Every deliverable built to drive decisions and withstand scrutiny
- Senior operators with Fortune 100 and deal-side experience
- Weekly demos and measurable outcomes, not status updates
What we do
Whether you're building value during the hold or preparing for exit, the work starts in the same place.
Value CreationRevenue Reconciliation
Transform scattered data into a clear view of exactly where your revenue comes from and which activities truly drive growth.
Operational Reporting
Replace the spreadsheet chaos with automated, trusted reporting that operating partners and management teams can actually use to make decisions.
AI and Data Readiness
Audit and fix the data layer before you invest in AI. Clean inputs, governed pipelines, and measurable outcomes instead of expensive experiments.
KPI Documentation
Define, document, and stress-test every metric in your equity story under multiple calculation methods before a buyer does it for you.
Data Lineage Mapping
Trace every number from executive summary back to source transaction. No black boxes. No "Dave knows how that works."
Data Room Preparation
Pre-populate the data room with reconciled, documented, traceable data. Your team answers diligence questions in minutes, not weeks.
Data Governance
Establish who owns the data between finance, ops, and technology. Lightweight controls that support growth without slowing operations.
Historical Normalization
Produce 3-5 years of clean, monthly, segmented data that accounts for system migrations, definition changes, and restructuring.
Post-Acquisition Integration
Consolidate data from newly acquired companies into a single source of truth. The first 100 days determine whether the data helps or hinders the thesis.
What clients say
"They transformed our data in clear, automated insights that drive real business decisions. Their combination of big platform experience and practical, actionable results is uniquely invaluable."
"Working with them is both memorable and impactful, with dividends well beyond the initial scope of any engagement. I wholly recommend their partnership."
"They will come to the table as a true thought partner at the onset of your process, bringing reliable, well-managed systems that ensure your company truly shows the receipts."
"They helped us pioneer brand new technology to turn complex data into clear business value. If you want to unlock the real potential in your business data, they are the partner you need."
Inside the Data Room
The weekly brief for PE operators. One free tool every week.
Get InsideQuestions
How long does this take?
Our standard engagement is a 4-week Data Readiness Assessment followed by a 90-day sprint. The assessment identifies the 2-3 constraints doing the most commercial damage. The sprint fixes the primary one. Most clients see measurable improvement in data defensibility within 90 days of starting.
We're not planning to sell for 3-5 years. Is it too early?
It is never too early. The companies that fix their data during the hold period make better operating decisions, get more from AI investments, and trade at premium multiples when they do go to market. The work that makes data defensible for exit is the same work that makes it useful for growth.
When should we start relative to our exit timeline?
12 months before exit is ideal. 6 months is tight but workable. 3 months is emergency triage. The earlier you start, the more you can fix and the less it looks like you are cleaning up for a sale. Buyers can tell the difference between genuine operational improvement and last-minute window dressing.
We already have a data team. Why do we need outside help?
Your internal team knows the business. We know what PE firms and buyers look for. The gap is usually not technical skill. It is knowing which data points matter most for value creation and what "defensible" looks like when the pressure is on. We work alongside your team, not instead of them.
How much will this cost?
The Data Readiness Assessment is a fixed fee in the low-to-mid five figures. Follow-on sprints are scoped and priced based on the assessment findings. Every engagement has a defined scope, timeline, and deliverable. No open-ended retainers.
How do you work with our existing advisors and bankers?
We complement them. Your banker tells the equity story. Your accountant runs QoE. We make sure the data underneath both of those survives scrutiny. We have worked alongside investment banks, QoE providers, and legal teams. Our deliverables are built to support theirs, not compete with them.
Can you help with AI readiness?
Every AI initiative lives or dies on the data underneath it. We assess your data quality, governance, and pipeline readiness before you invest in models or platforms. Most companies that come to us after a failed AI project discover the root cause was data, not the technology.
Find out where your data is holding you back.
Ten questions. Two minutes. You'll know whether your data is ready to support growth, AI, and buyer scrutiny.
Free Data Valuation Score