Article ยท Private Equity
From Good to Great: How Digital Transformation Unlocks Hidden Value in Private Equity Portfolio Companies
Executive summary. Digital transformation is one of the most important value-creation levers a private equity owner controls. A Harvard Business School working paper finds that private equity ownership goes with more spending on digital technology at portfolio companies, more so in growth deals and where the sponsor has digital expertise, and that higher digital spending after the deal is tied to faster growth in sales per employee (Baik, Chen and Srinivasan, Private Equity and Digital Transformation). This article sets out where that value comes from, in order, and the failures that repeat.
Digital is now a decisive value-creation lever in private equity, and the reason is arithmetic. A company’s worth is revenue times margin times the multiple, and of the three, the multiple is the one that re-rates most when a business stops looking like a services shop and starts looking like a platform. Buyers pay more for recurring revenue, for owned intellectual property, and for operations a data room can verify. Digital maturity is what moves a company from the first kind to the second.
The best sponsors understood this and stopped treating technology as a cost of the hold. They build a repeatable operating capability and apply it across the portfolio: a way to read a company’s digital gap at entry, a plan to close it on a clock, and a bench that executes rather than advises. The value sits in the discipline of tying every digital move to a number an investment committee already tracks; the tooling follows.
Where does that value actually come from? Five places, in roughly this order.
Customer experience is the most immediate. Self-service, real-time visibility and a single view of the customer cut the cost to serve and lift retention, and retention is what a strategic buyer pays a premium for.
Data and analytics are the foundation underneath everything else. Without one clean, accessible source of truth, AI and automation fail quietly. Most portfolio companies carry fragmented systems and inconsistent definitions; fixing that is unglamorous, and it is where the compounding begins.
Operations and automation are the fastest path to margin. Intelligent automation of the back office and prediction in the plant take cost out and release the working capital tied up in inefficiency. This is Engine 1 work: today’s profit, kept on its own books.
Revenue models are the multiplier. Moving from one-time transactions to recurring, contracted revenue changes how the market values the company as well as how much it earns. This is Engine 2: tomorrow’s value, built as a standalone asset.
Talent and culture decide whether any of it holds. Technology is the easy part; the capability and the willingness to run differently are what separate the companies that transform from the ones that buy software and change nothing.
The sequence matters as much as the list. Assess the gap honestly in the first 100 days, build the data and cloud foundation next, scale what works across the business, and only then reach for the differentiating bets. Trying to do all of it at once is the most common way to do none of it.
The failures repeat, and they are avoidable. The first is starting from technology instead of a business outcome: every initiative should name the metric it moves. The second is underinvesting in change management, where most of the real effort belongs. The third is attempting everything at once instead of sequencing three to five moves that compound. The fourth is building analytics on dirty data, which guarantees the AI on top of it will disappoint.
This is a leadership decision before it is a technology project: a decision to make a business so efficient, and so clearly built to keep earning, that its value is undeniable to the next owner. That is the work: re-rating the multiple, with modern IT as one of the means.