For PE operating partners protecting value across the hold

Fix the Data.
Grow the Value.

Most of your portfolio companies can't reproduce last quarter's revenue from source in under an hour. A buyer finds it in week eight of diligence, and it costs the fund a turn at exit.

We find it first, and fix it in 90 days.

20 yrs
Fortune 100 data leadership
90 days
To measurable impact
$100M+
Delivered at Fortune 100 scale

Problems We Solve

Bad data costs you whether you sell or hold.

These are the data issues across your portfolio that surface in diligence, stall integrations, and cost multiples at exit. Each one bites at a different stage of the deal.

Diligence

Revenue that doesn't reconcile

Finance reports one number. The CRM says another. The warehouse says a third. When a buyer asks what the company's MRR is and the answer changes depending on who they ask, it creates transaction risk.

Diligence

Diligence surfaces problems too late

Eight weeks in, the target's customer data is unreliable or financial reporting can't be reproduced from source systems. The deal slows, the price adjusts, or the deal dies.

Integration

Integration without a common language

Two companies merge. Active customer means one thing in Company A and something else in Company B. Consolidating reporting is impossible until someone reconciles the data model.

Value creation

Leadership can't agree on what to measure

The CEO says growth. The COO says efficiency. The CFO says margin. None can point to a dashboard that tells the story. The technology follows the strategy, not the other way around.

Value creation

AI initiatives stall on the data

Every portfolio company wants to do AI. But the underlying data is fragmented and ungoverned. AI amplifies whatever it is fed. If the data is wrong, the AI is confidently wrong.

Exit

The exit is 18 months out and the data isn't ready

You want to exit, but the data can't support the story. Customer counts are unreliable and revenue attribution is manual. Buyers will find it, and it will cost you multiples.

What a buyer tests first

Reported numbers rarely survive diligence.

The figures in a board deck and the figures a buyer can reproduce from source are rarely the same. We find the gap before diligence does, and close it. Here is a real readout from one portfolio company.

The signature of defensible data

Every number, traced back to source.

Defensible data is not a dashboard. It is a number a buyer, a board, or an AI can follow all the way back to the systems it came from, in minutes, and trust.

We reconcile the metrics that matter, document the lineage, and leave the operating model that keeps them true. When diligence asks where a figure comes from, the answer is already on the page.

Many systems, one verified number

Why us

Built for PE timelines, not the consulting calendar.

Other agencies

  • 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
  • Strategy decks from people who can't build what they recommend

Crawford McMillan

  • 90-day sprints aligned to your value creation plan
  • Fix the ten 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
  • Consulting and engineering in one team. We build the fix, not just the deck
  • Weekly demos and measurable outcomes, not status updates

How we work

One staged program, on a deal clock.

Phase 1
Data Readiness Assessment
4 to 6 weeks

On-site discovery of how data actually moves, where it breaks, and who it depends on. You leave with a scored baseline, the constraints ranked by commercial damage, and a costed, sequenced plan.

See what the assessment covers →
Phase 2
Implementation
60 to 90 days

We deliver the Phase 1 plan. Not just pipelines and reporting, but the operating model and ownership that keep the fix in place. Fortune 100 engineering at mid-market speed.

Phase 3
Sustain
Ongoing

Monitoring, optimization, and knowledge transfer. The capability and the people to run it stay after we leave.

Graeme Crawford, Founder and CEO of Crawford McMillan

Leadership

Graeme Crawford

Founder and CEO

Twenty years leading data programs at Fortune 100 scale. At Capital One, led a cloud migration that enabled the closure of legacy data centers, saving hundreds of millions, and built a real-time analytics platform with sub-millisecond latency across billions of transactions.

Before that, at IBM, the designated fixer for hostile recoveries and severely damaged implementations. Now that same discipline goes to work inside your portfolio, building value and preparing companies for exit.

What clients say

Operators who have been through it.

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.

Jack KaravichCEO, Tigeraire

Working with them is both memorable and impactful, with dividends well beyond the initial scope of any engagement. I wholly recommend their partnership.

Allison PickettCEO, AMPlify

Crawford McMillan brought the data architecture and governance expertise we needed to unlock AI across our research portfolio.

Jason GamelCEO, American Resort Development Association

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.

Neil TolaniCofounder, Kunai

Weekly brief

Inside the Data Room

The weekly brief for PE operators. What buyers actually test, one free tool every week, no theory.

Get Inside

FAQ

Questions operators ask first.

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.

Grow the value

Find out where your portfolio's data is holding back value.

Run the free VCP Data Score on any portfolio company in a few minutes, or book a short call and we will tell you straight whether we can fix it in 90 days.