A deal team is in its final week before closing. The data room holds thousands of documents. The seller says the company runs 8 million euro in adjusted EBITDA. After due diligence, it turns out to be 6.2 million. That 1.8 million gap is not abstract: at a multiple of 8, more than 14 million euro in valuation evaporates.
That is where data and private equity meet. Not in a nice dashboard afterwards. In the number the whole deal rests on.
But private equity is not one thing. Where data pays off most depends on what kind of investor you are: do you take control, or do you buy secondaries? Before I draw that distinction, first the part every deal shares: due diligence.
Where data makes or breaks a deal
Every transaction runs through a due diligence, the investigation where the buyer opens the hood and checks whether the seller’s numbers hold up. It happens in a data room: a secure online environment full of financial statements, contracts and exports. That is where deals die, or change price.
But a data room full of raw files is not insight. It is the difference between forty tabs that don’t reconcile and one source that does. The value only appears when someone turns that pile into a single model you can query: cleaning, modelling, joining, making it auditable. And that under time pressure, because the deal won’t wait.
And it sets the price. A buyer who can move through the numbers fast verifies in days what otherwise takes weeks, and bids with confidence instead of on a hunch. That confidence is part of the valuation: a tight, searchable data room pushes it up, a messy one breeds doubt and drags it down. The good news for the seller is that you hold that side yourself.
For a buyer who takes control, a messy data room is not only a risk, by the way, but also an opportunity. You buy cheaper because the numbers are murky. Put the reporting in order afterwards and it works two ways: a business with clean, auditable numbers earns a higher multiple, and only once you can see what is going on do you find the operational improvements that actually lift profit. Sell it on a few years later, and that difference in valuation is yours. On the condition, though, that no real skeletons fall out of the closet that the messy numbers were hiding. More on that in the next part.
Adjusted EBITDA: prove your number before the buyer asks
Take the number most deals turn on: adjusted EBITDA. EBITDA is raw operating profit. “Adjusted” strips out the one-off and non-operating items to show the real, repeatable profit: the owner’s excess salary, a family member on the payroll, personal costs booked as business expenses, above-market rent to the owner’s own property company. Each of those add-backs pushes EBITDA up, and so the price.
The risk for the seller: during the actual due diligence the buyer tests your numbers through a quality of earnings, add-backs among them. Whatever you can’t support gets removed. And because the price is a multiple of EBITDA, every add-back that gets struck moves the valuation by that same multiple.
This is where data helps, and up front. As a seller you can run a due-diligence readiness first: the same test, but beforehand, to avoid surprises. Instead of fishing the add-backs out of an export by hand every time, you set rules that map bookings automatically to add-back categories, by general ledger account, supplier or cost center. Only the edge cases you still review by hand. After that the bridge from EBITDA to adjusted EBITDA rebuilds reproducibly on every refresh, with lineage down to the underlying invoices: every adjustment clicks back to its source, reconciled against the books and ready to survive the other side’s scrutiny.
That way you don’t walk into the data room with a number you still have to defend, but with a number that is already proven.
Two kinds of private equity, two kinds of data work
Now the distinction. Because where data pays off most differs fundamentally with your position.
When you take control
A control buyout: you buy a majority and take the wheel. Your return comes from three levers: governance, operational improvement and financial structure. The middle one is where data counts.
You can only improve the operation once you can see it. And most companies you acquire can’t see themselves. Hours sit in one system, costs in another, sales in a third. Nobody can say in a single number which site, which product or which customer actually makes money.
That is exactly the work. Building a shared data layer. A P&L you can actually break down by site, product and customer, instead of a spreadsheet that gets assembled differently every month. Because you hold control, you are allowed to rebuild the data model. And your 100-day plan largely wins or loses on how fast you get that done.
Put shortly: in a control buyout, data is not reporting after the fact. It is part of the value creation itself.
When you buy secondaries
Secondaries are a different game. You buy an existing stake from another investor, in a company or in a fund. You rarely get operational control. And the previous owner has usually already wrung out the operation.
That means your value doesn’t come from an operational turnaround. You can’t open up the engine, because you’re not at the wheel. So the data work shifts to two other things.
First: pricing with less visibility. Your data room is often thinner. You buy a position you can’t fully open up. Reading fast and sharp what is there becomes your edge.
Second: aggregating and monitoring. A secondaries portfolio is diverse. Stakes in several funds, direct holdings, each with its own reporting: different schemas, no shared identifier across funds, numbers you sometimes have to pull out of PDF reports, rarely on time. Pulling that together into one living picture, where your exposure sits, how value evolves, which positions carry and which slide, that is the real engineering work. No operational lever, but speed and clarity of judgment.
What this means for you
Taking control? Build the data layer early. Treat it as part of your value creation, not as something for later.
Doing secondaries? Your edge is in aggregation and in the speed with which you can read a position.
Either way it starts with the same question: can you see in time what is really going on? Most funds think they can, until due diligence proves otherwise.
Sitting with that question for a specific deal or portfolio? Book a call and we’ll look together at where your visibility falls short.