Data Governance = EBITDA multiple expansion


Hey there Reader!

We're in the 'ice age' time of year with 10+ inches of snow forecast to fall here in the mid-Atlantic. No time for chill with clients and prospects though, who are all well into their stride and pushing hard towards ambitious 2026 goals!

Luckily for me, I'm heading south to Florida this weekend rather than shovelling snow, spending the weekend with Greg Isenberg and his team to talk building distribution as a moat and play with all the latest AI tech to see how we can convert it into real business value.

Greg is a master of modern online business and has put together an awesome room of founders - I'm already feeling some great collabs and potential partnerships coming together. Full report in the next issue!

Hot news in the PE space:

Right on to this week's deep dive focused on data governance - is it burdensome policy or critical EBITDA protection? Let's take a look!

DEEP DIVE

Data Governance Is EBITDA Protection Disguised as Policy

Governance is multiple expansion

Private equity firms say "data governance," and portfolio company operators hear "more bureaucracy." Checkbox exercises. Policy documents nobody reads. Consultants at $500/hour building frameworks that gather dust.

They're not wrong. That's what bad governance looks like.

But the smart PE shops figured something out years ago: data governance done right is EBITDA protection. The difference between a 2x exit and a 3x. What keeps buyers from haircutting your valuation by 15% when they find data quality issues in diligence.

The valuation math nobody talks about

I've sat through enough deal processes to see the pattern. When a buyer's diligence team finds:

  • Revenue recognition that doesn't match across systems
  • Customer data that won't reconcile between CRM and billing
  • Inventory numbers that shift depending on which report you pull
  • Metrics that management "trusts" but can't verify

...they don't just flag it. They price it. Hard.

Portfolio company with $50M EBITDA and messy data? The buyer's building a $5-7M escrow into the deal structure. Or adjusting the multiple down by 0.5-1.0x. Same math, different mechanism. Either way, that's $25-50M in enterprise value gone because nobody treated data like the asset it is.

What governance protects

Real governance isn't about policies. It's about reducing uncertainty for the next buyer.

When you can show a buyer:

  • Single source of truth for customer relationships (not three different "official" lists)
  • Automated reconciliation between systems (not manual spreadsheet heroics)
  • Data lineage that explains where every number comes from
  • Quality metrics that catch problems before they hit executive dashboards

...you're not selling them a company with "pretty good data, trust us." You're selling them investor-grade infrastructure that they can plug their own systems into on day one.

That certainty is worth 20%+ on the exit multiple. I see it consistently in the UK and US markets.

The operator's dilemma

Operators need flexibility. Move fast. Adjust metrics as the business evolves. Make judgment calls when systems don't perfectly align.

Governance feels like the opposite of that. Feels like rigidity.

But governance isn't just about freezing everything in place; it's about documenting the flexibility so the next owner understands what they're buying.

Your CRM and billing system show different customer counts? Fine, if you can explain exactly why, show it's intentional, and prove the reconciliation logic is sound. That's not chaos. That's documented complexity.

The problem isn't complexity. The problem is the undocumented complexity that appears to be incompetence during diligence.

What this looks like in practice

I've seen this pattern play out multiple times: a portfolio company has five different "official" revenue reports. Sales uses one number, finance uses another, and the board deck uses a third. All defensible. All slightly different.

When this hits diligence, it stalls for weeks while operators try to explain the differences. Buyers hear "inconsistent financial reporting" instead of "different views for different purposes."

The fix isn't eliminating the different views. It's building governance around them:

  • Document why each view exists and what decisions it supports
  • Create automated reconciliation showing exactly where the deltas come from
  • Build a master data dictionary explaining every field, every calculation
  • Set up quality checks that flag when the deltas exceed expected ranges

Same complexity. Now it's controlled complexity. Buyers see infrastructure instead of chaos. Deal velocity improves, valuation holds.

The 90-day window

For PE timelines, governance has to be in place before you go to market.

You can't build this during diligence. Once the buyer's team is crawling through your systems, it's too late. You're in defensive mode, explaining problems instead of demonstrating control.

The PE firms that consistently drive top-quartile exits are building this infrastructure 12-18 months before exit. Not as "exit prep." As an ongoing operating discipline that pays off spectacularly when it's time to sell.

That's the insight most operators miss. Governance isn't a tax on agility. It's insurance against valuation risk. And unlike most insurance, it pays out every single time.


The bottom line

Data governance protects EBITDA the same way good financial controls do. By giving buyers confidence that they're not inheriting a mess.

Clean data, documented complexity, automated reconciliation. That's not compliance theater. That's multiple expansion.

FINAL SEND OFF

Share this with any friends, family or colleagues that will benefit and, when you need help with your next round of data diligence, drop me a line to talk about how we might help.

Cheers,

Graeme

Graeme Crawford

CEO at Crawford McMillan

Helping PE firms protect and grow company valuations with clean, reliable data.

CRAWFORD McMILLAN
Professional Data Consultancy of 25+ years

The content provided in this newsletter, including discussions regarding data architecture, operational efficiency, valuation readiness, and business strategy, is intended strictly for informational and educational purposes only. Decisions regarding capital allocation, investments, acquisitions, or business strategy should always be made in consultation with qualified professional financial, legal, and investment advisors.

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