Tech Due Diligence as a Private Equity Value Creation Tool

The funds generating the strongest returns in today’s market aren’t just buying better companies. They’re building a repeatable system for turning technology into measurable portfolio value, from the first diligence call to the exit deck.

Private equity holding periods have stretched to their longest point in decades. After peaking at a record seven years in 2023, the median hold period still sits at six years as of 2025, well above the pre-pandemic average of 5.5 years, according to PitchBook data. Exits have gotten harder to engineer on favorable terms, and LP patience is not unlimited. The room for error in the post-acquisition phase has narrowed accordingly.

A 2024 Harvard Business School working paper found that PE-backed companies significantly increase digital investments after acquisition, and that those increases correlate with stronger sales growth, higher employee productivity, and gains in innovation output. The link between technology spend and portfolio value is no longer theoretical. What’s less clear, for many funds, is how to turn that observation into a repeatable operating model.

Recognizing that technology matters is not the same as having a system for deploying it. The funds generating consistent alpha have figured out the latter: a structured way of identifying, prioritizing, and executing technology initiatives across the full investment cycle, from the deal through to exit.

Why the traditional playbook is running out of runway

For most of PE’s modern history, value creation followed a recognizable arc: buy at an attractive multiple, apply financial discipline, cut costs where possible, optimize the capital structure, and exit higher. It worked well in a low-rate environment where financial engineering carried real weight and holding periods were shorter.

The quick wins available through vendor renegotiations, back-office headcount consolidation, or working capital cleanup have largely been captured. What’s left requires deeper intervention. With holding periods now routinely exceeding five years and acquirers scrutinizing scalability and profit quality more carefully, funds that are still running a primarily financial playbook are finding themselves with fewer levers to pull by year three.

A 2025 value creation study by Simon-Kucher found that 33% of deal teams and operating partners now rank operational improvements as the primary driver of their equity story, nearly double buy-and-build at 20% and well ahead of financial engineering. Technology sits at the center of that shift. Not as a separate workstream, but as the underlying capability that makes sustained operational improvement possible.

Technology due diligence: from risk checklist to value map

Most tech due diligence still functions as a risk screen. Teams go in looking for technical debt, integration exposure, compliance gaps, and post-close surprises. That work is necessary. But it answers only half the relevant question.

The other half is forward-looking. Which processes could be automated, and at what cost? Where are the data gaps that will limit the operating partner’s visibility once the deal closes? Which legacy systems will slow down integrations or cap the company’s growth ceiling? A tech DD that surfaces those answers early gives the operating partner something to work with on day one, instead of spending the first quarter re-diagnosing what diligence already found.

According to KPMG's 2024 Technology M&A Survey, the top diligence challenge for PE respondents is understanding the true capabilities and scalability of a target's technology platforms. That's a framing problem as much as a data problem. It's also where having the right technical partner in the room during diligence changes the output entirely. At Making Sense, our IT due diligence engagements are built around exactly this: moving beyond the risk register to map where value can actually be created. A useful tech DD covers:

• Architecture and technical debt: realistic cost-to-maintain or cost-to-replace estimates for core systems.
• Data maturity: whether reporting infrastructure exists to support the operating metrics the fund will need to manage the business.
• Automation potential: specific manual workflows that could be addressed in the first 12 to 18 months, with rough effort and impact estimates.
• Scalability constraints: what breaks first under 30% growth or during an add-on integration.
• Vendor dependencies: contractual obligations and licensing structures that affect post-acquisition flexibility.

A diligence process that produces this kind of output functions as the first draft of a value creation roadmap. That changes what the operating partner can do with the first 90 days.

The first 90 days: where the roadmap either starts or stalls

The post-close transition follows a pattern that people who have been through it will recognize. The deal team moves on. The operating partner is now accountable, but is simultaneously trying to establish governance, set up financial reporting, manage the reactions of a leadership team that is still adjusting to new ownership, and figure out which problems to tackle first. Technology decisions get deferred because they feel like they require more information.

Sometimes a consulting engagement gets commissioned to re-evaluate the technology landscape. It surfaces mostly what diligence already found, three months later. Sometimes the CTO or IT lead simply stays in maintenance mode while everyone else figures out priorities. Either way, the company loses the early momentum that determines the character of the whole holding period.

Continuity between diligence and execution is what prevents this. When the DD team has already identified the first wave of initiatives, prioritized by impact and implementation risk, the operating partner can arrive with a plan rather than a question. At minimum, the first 90 days should produce:

• A technology roadmap tied to specific EBITDA levers, not a list of IT deliverables
• Two or three visible quick wins that build credibility with the portfolio company team
• Clear ownership of technology decisions, assigned at the management level
• A baseline reporting layer so the operating partner is not flying blind on the metrics that matter

This is where the distinction between vendor and partner becomes operational rather than rhetorical. A vendor executes against a defined scope. A partner who was involved in diligence already knows the systems, the constraints, and why certain decisions were deferred. That shared context is not a soft benefit. It’s the difference between a roadmap that starts moving in week one and one that spends the first quarter in discovery.

Two modes of technology value: running them in parallel

Technology-driven value creation in a PE context tends to fall into two distinct modes, and managing them as if they were sequential is a common mistake.

Defensive: protect margins, improve visibility

Defensive initiatives reduce cost, reduce operational risk, and give the fund better visibility into what’s actually happening inside the business. They tend to have shorter payback cycles and are easier to justify early in the hold. Common examples include automating manual processes in finance or operations, consolidating redundant systems after an add-on acquisition, cleaning up data pipelines so that reporting reflects reality, and modernizing legacy infrastructure that is creating maintenance drag or integration bottlenecks.

The practical value here is often underestimated. An operating partner who can’t trust the numbers coming out of the portfolio company’s ERP is making decisions based on lagging, incomplete, or conflicting data. Fixing that is not glamorous, but it changes the quality of every subsequent decision made during the hold.

Offensive: build the capabilities that drive exit premium

Offensive initiatives use technology to expand revenue, improve customer experience, or build capabilities that show up in how an acquirer values the business at exit. They require more capital and carry more execution risk, but they are also what separates a good exit from a great one. 

Recent M&A analysis suggests that companies actively investing in digital transformation are three times more likely to achieve premium valuations in acquisition processes.

Offensive plays look different across industries and business models, but the underlying logic is consistent: build better data infrastructure so commercial teams can price, target, and retain more effectively; deploy AI tools against workflows where speed and accuracy create customer-facing impact; develop the kind of scalable, documented technology platform that a strategic acquirer will pay to acquire rather than re-build.

Most operating partners understand both modes. The execution challenge is running them simultaneously rather than sequentially. Early in the hold, defensive work tends to dominate. But the offensive roadmap should be designed in parallel, not deferred until the defensive work is finished, because the exit window rarely waits for a clean handoff.

This is where structured AI adoption tools have found real traction in mid-market environments. The obstacle for most portfolio companies is not interest in AI. It’s timeline. Traditional implementation cycles of six to twelve months before measurable output don’t fit the holding period model. A structured approach combining off-the-shelf tooling with targeted custom development, what we at Making Sense call an AI Jumpstart Kit, can compress that to weeks, without generating the kind of technical debt that complicates the exit story later.

What it looks like when the technology partnership actually works

The firms executing this well share a common posture toward technology: they treat it as a capability to be built and managed across the investment cycle, not a set of discrete projects to be initiated and closed. The partners they work with have to operate at multiple levels, strategy and execution, without losing sight of either.

At Making Sense, we've worked with mid-market companies and PE-backed organizations across healthcare, legal, fintech, agtech, and other sectors for nearly two decades. What we've seen consistently is that technology only creates durable value when it's connected to how the business actually operates. As César Donofrio, our CEO, puts it: "AI doesn't fix a broken operating model. It exposes one." That's as true in a PE-backed company eighteen months into a hold as it is anywhere else.

In practice, this means different work at each stage:

• During diligence: a technology assessment that maps value creation opportunities alongside risk, producing the first draft of a post-close roadmap
• In the first 90 days: translating diligence findings into concrete workstreams, standing up quick wins, and establishing the reporting infrastructure the operating partner needs to manage the business
• During the hold: running defensive and offensive initiatives in parallel, adjusting the roadmap as business conditions evolve, and keeping velocity high without accumulating technical debt that will surface during exit diligence
• Approaching exit: ensuring the technology story is coherent, metrics-backed, and tied clearly to the growth trajectory, so it reinforces rather than complicates what the bankers are selling

That kind of engagement requires familiarity with how PE investments actually work, what operating partners need at each stage, and how to translate technical decisions into outcomes that matter to an investment committee. It’s closer to what a good operating partner provides on the business side than to what a typical technology vendor delivers on the IT side.

Key takeaways

A few things worth carrying forward:

• Tech DD that only identifies risk leaves a roadmap gap. The output should be usable on day one of the holding period, not filed as a reference document.
• The first 90 days set the operational tempo for the entire hold. Arriving without a technology plan means spending those months building one from scratch while the clock runs.
• Defensive and offensive technology work are not sequential. Stage them by risk and return profile, not by completion.
• AI adoption does not require a multi-year runway. Use-case-driven, structured approaches can show measurable output within a quarter.
• Exit valuations reflect the technology story. Companies that can demonstrate a clear line from digital investment to business performance command better outcomes.

Technology due diligence, digital transformation, AI adoption, legacy modernization: these are solvable problems when you have the right partner at the table. If you're working through any of them, we'd like to talk. You can also explore what we do specifically for private equity.