IT cost benchmarking is no longer just a post-close optimization exercise. For private equity teams, it is a pre-close value creation lever that reveals hidden SaaS waste, shadow IT, and technology spend risks before they compress returns.
Most PE deal models carry a technology cost reduction assumption that was never properly tested. Here is what a structured IT spend analysis actually finds, and why the difference matters before you sign.
The Number That Gets Every Deal Model Over the Line
There is a line in almost every private equity deal model that gets filled in the same way. IT cost savings: assume 10 to 20 percent of technology spend, carry it forward, move on. It is defensible, it is fast, and for most deal teams it is the right call given everything else competing for attention during due diligence.
Private equity due diligence is rightly focused on the questions that determine whether a transaction succeeds: whether the revenue is sustainable, whether the market thesis holds, whether the management team can execute under new ownership, and whether there are liabilities that could reshape the deal structure entirely. Against that backdrop, technology cost reduction is a known lever. A portfolio-informed estimate is sufficient to progress.
The issue is not the assumption. It is the gap between what that assumption implies and what a structured review of the technology environment consistently finds. That gap is larger than most deal models anticipate, and it is entirely quantifiable before you close.
What the Stack Actually Looks Like When You Open It
When you map a company’s full technology environment properly, tracking every vendor, every contract, every software licence, and comparing what is provisioned against what employees are genuinely using, what you find is rarely what the IT team believes is there.
Across the organisations we work with at SaaSrooms, identifiable savings opportunities average around 18 percent of total tracked technology spend, ranging from 14 to 22 percent depending on the governance maturity of the business. The number is not the interesting part. What sits behind it is.
In one organisation we assessed, a single ERP contract review identified savings of over 28 percent on a contract worth more than £400,000 annually. The contract had rolled into renewal without a competitive process. Nobody had tested the market. The savings were there the whole time, waiting for someone to ask the question.
In another, a routine Microsoft 365 audit found 18 users with zero logins recorded over the entire analysis period. Active licences, no active users. Those accounts had accumulated over time as the business evolved and headcount changed, but nobody had ever gone back to clean them up.
In a third, two safety management platforms were running simultaneously across different teams. Neither team knew the other had signed up. On top of that, a legacy IT support contract was still being paid alongside the replacement service it was supposed to have made redundant. Three separate decommissioning opportunities, all invisible to the business until someone mapped the stack.
These are not unusual findings. They are typical ones. The savings categories that appear with near-total consistency across organisations are:
- Licence right-sizing: seat counts and licence tiers set at contract inception rarely reflect actual usage as the business evolves.
- Tool decommissioning: duplicate platforms, legacy contracts, and zero-usage applications that auto-renew because nobody owns the decision to remove them.
- Contract renegotiation: agreements rolling into renewal without market testing, consistently above comparable rates.
- Supplier switching: equivalent capability available from alternative vendors at materially lower cost, never evaluated because there was no structured sourcing process.
“Deal teams know a deeper analysis would add value. The process simply has not allowed for it. The answer has always been to rely on historical metrics and move forward.”
Jason Stern | CEO, SaaSrooms | Forbes Business Council Contributor
That constraint has always been time. A comprehensive technology spend assessment, done properly, has historically required weeks of specialist work, and deal timelines simply do not accommodate that. What has fundamentally changed is how AI now handles that workload. Where it once took a team of analysts days to reconcile vendor contracts, cross-reference usage data, identify redundancies, and surface savings opportunities, AI-powered analysis can now process the same volume of data in a fraction of the time. The depth of insight that was previously reserved for post-close integration planning is now accessible within the window of an active transaction.
IT Spend Benchmarks by Industry
The reference ranges below are drawn from observed corporate technology spend patterns across the organisations we work with, cross-referenced against sector data. All figures represent IT operating expense as a percentage of total revenue, normalised to exclude one-time project costs.
Use these as a starting position rather than a verdict. A company within the average range for its sector can still carry recoverable waste in the double digits, as the examples above illustrate. The benchmark tells you where to direct the conversation. The stack analysis tells you what you are actually dealing with.
Industry | Lean (%) | Average (%) | Overspend Flag |
Financial Services | 4 – 6% | 7 – 10% | > 12% |
Healthcare | 3 – 5% | 5 – 8% | > 10% |
Manufacturing | 2 – 4% | 4 – 6% | > 9% |
Retail / E-commerce | 2 – 3% | 3 – 5% | > 7% |
Professional Services | 4 – 6% | 6 – 9% | > 11% |
Software / Technology | 8 – 12% | 12 – 18% | > 22% |
Logistics / Supply Chain | 2 – 3% | 3 – 5% | > 7% |
Four caveats worth keeping in mind when applying these figures:
- Lean does not mean well-managed. Below-benchmark spend can reflect a clean, appropriately matched IT environment or years of underinvestment that will surface as a capital requirement post-close.
- Above benchmark does not always signal waste. Transformation programmes, post-acquisition integrations, and rapid hiring phases all create legitimate upward pressure on the IT cost line.
- Company size shifts the range. Smaller organisations spend a higher percentage of revenue on technology than larger ones, primarily because they have not yet achieved economies of scale in licensing and vendor management.
- Composition matters more than the total. Two companies at identical IT spend percentages can carry entirely different risk profiles depending on what that spend is actually doing.
A Five-Step Framework for IT Cost Benchmarking in Due Diligence
The sequence below covers how a rigorous technology spend assessment should be structured in a private equity due diligence context. The logic holds whether the analysis is done manually or with AI-powered tooling. What changes with the latter is the time required and the depth of visibility into shadow IT and actual usage data.
Step 1: Build the Normalised IT Cost Base
Request a complete, itemised breakdown of all technology costs: personnel and contractors, software licensing, SaaS subscriptions, cloud and infrastructure, hardware, managed services, and IT consulting. Where the company capitalises software development costs, request those separately and add them back to arrive at total technology investment rather than just the expensed figure.
This step almost always reveals a gap between what the business believes it spends and what it actually spends. Subscriptions on team cards, tools bought by departments outside IT, and untracked SaaS renewals all sit beneath the reported number. In organisations without active software asset management, that gap consistently runs to 15 to 25 percent of reported spend, which means the baseline needs validating before benchmarking can begin.
Step 2: Map to the Right Industry Benchmark
Using the reference table above, establish where the target sits within its sector. Lean, within average, or into overspend territory? For businesses operating across multiple verticals, weight the benchmark proportionally rather than forcing a single category.
This positioning shapes the next conversation. A company well above benchmark with no visible transformation programme requires a specific explanation. A company at the lean end during a period of fast growth raises an equally important question about whether technology investment has been deferred and at what cost.
Step 3: Analyse the Composition of Spend
The total spend percentage is a starting point. The composition is where the real picture emerges. The patterns that most consistently signal concern are: spend concentrated in legacy maintenance rather than capability, high vendor counts with no rationalisation history, and productivity platforms that have never been right-sized since original implementation.
SaaS sprawl is one of the most common findings in mid-market technology stacks. Multiple tools doing the same job across different teams, legacy contracts still running alongside their replacements, and zero-usage applications renewing quietly year after year are not edge cases. They are the norm in organisations that have grown without a structured approach to SaaS procurement and vendor management.
There is also a less visible layer of technology spend that is growing rapidly: AI features embedded directly into existing SaaS platforms and vendor tools. Across the enterprise, 32 percent of organisations now cite more stringent vendor security standards as their top priority for managing the risks posed by embedded AI in third-party software. For a deal team assessing a target’s technology stack, this means the cost and risk profile of an existing SaaS contract is no longer just about what the software does today. It also includes what AI capabilities the vendor is quietly adding, how that data is being used, and whether any of that is visible to the organisation at all.
Step 4: Separate One-Time Costs from the Run-Rate
Ask specifically what was spent in the past 12 months that will not recur. Migrations, integrations, and major implementations inflate the IT cost line in ways that do not reflect ongoing expenditure. Model both the reported spend and the normalised run-rate. Apply the run-rate to benchmarking. Use the one-time costs to assess whether the investment was strategic or reactive.
Step 5: Stress-Test the Post-Acquisition IT Trajectory
Project where IT spend will sit 18 to 36 months post-close under three scenarios: base case, growth acceleration, and cost optimisation. If spend is lean, is there deferred investment that will surface? If elevated, are there credible reduction pathways that do not compromise the capabilities driving value in the business?
This is where IT cost benchmarking connects directly to the PE value creation plan. The analysis is not complete until it has shaped what the acquirer plans to do after close.
The goal of IT cost benchmarking in due diligence is not to find the lowest spend. It is to find the right spend for the business model, the growth trajectory, and the competitive environment of the company being evaluated.
Red Flags That Warrant Deeper Investigation
The signals below reflect what surfaces when you build structured visibility into a target organisation’s technology environment. Some are visible in spend data alone. Others only emerge when usage data is examined alongside the contract record.
Signal | What Sits Behind It | Deal Implication |
SaaS spend above benchmark | No asset register, no renewal calendar, no ownership | Accumulated cost habit, not intentional investment |
Shadow IT at scale | Employees buying tools outside IT on personal cards | Uncontrolled spend and data risk invisible to leadership |
High seat counts, low active usage | Licences set at peak headcount and never adjusted | Paying for seats that serve no active user |
Duplicate tools across teams | Independent purchasing decisions, no consolidation | Redundant spend, fragmented data, no clear owner |
Auto-renewing contracts throughout | No renewal calendar and no competitive review process | Vendors increasing prices with no resistance |
Below-benchmark spend, fast growth | Revenue scaling but infrastructure not keeping pace | Emergency technology investment required post-close |
The shadow IT row in this table deserves particular attention in the current environment. What was once a problem of untracked SaaS subscriptions has expanded significantly with the rise of AI tools. The scale of this blind spot is consistent across organisations of every size. Among large organisations, 47 percent lack full visibility into which AI tools their employees are actively using. Among mid-sized organisations, that figure rises to 68 percent. These are not small businesses with limited IT resources. They are established organisations with technology teams in place. The blind spot exists because AI tool adoption is moving faster than procurement processes and governance frameworks can keep up with. For a deal team, this means the shadow IT line in any target organisation is almost certainly larger than it appears, and a meaningful portion of it is now AI-related.
These signals are almost never the result of deliberate decisions. Duplicate platforms, idle licences, and auto-renewing contracts accumulate gradually, in the absence of visibility and process. That also means they are fixable. A scoped technology cost remediation plan is a credible post-close value creation input, not simply a risk item to log and set aside.
What a Well-Governed Technology Environment Actually Looks Like
The companies that perform best after acquisition are rarely the ones with the lowest IT spend. They are the ones with the most intentional IT spend.
A well-governed technology environment is one where spend is aligned with the business model. Every significant application has a named owner, a documented renewal date, and a clear connection to a business outcome. The tools in use reflect what actually creates value in the business, not what was inherited from a previous strategy or never properly reviewed.
Governance is the most reliable indicator. Where technology spend is well-managed, there is clear visibility into what is being spent, who authorised it, and what it is producing. Licences are tracked and right-sized. Cloud costs are monitored rather than left to accumulate. Vendor contracts are reviewed competitively at renewal rather than rolled forward by default. This discipline almost always correlates with broader financial rigour across the organisation.
The value of that governance posture is measurable. Organisations with a formal AI governance framework in place consistently report stronger confidence in their security controls and meaningfully higher visibility into how technology is actually being used across the business. Yet only 41 percent of organisations currently have such a framework in place. For a PE acquirer, that figure is an indicator worth checking: a target with formalised technology governance is not just better managed today. It is structurally easier to integrate, optimise, and scale.
Scalability is the other indicator worth examining. The most resilient technology environments allow revenue to grow without requiring a proportionally equivalent increase in IT cost. That ratio is measurable, and it is one of the clearest signals of a well-architected foundation.
When a target meets these criteria, even at a slightly above-benchmark spend level, the quality of the foundation often justifies the premium. Conversely, a company running below benchmark because of chronic underinvestment will require capital post-close, and that capital should be in the model before the deal closes.
Why the Benchmark Is Only Half the Picture
“A headline number confirms whether a company is in the right range. What it cannot tell you is whether that spend is working.”
Philip Allouche | Founder & CEO, SaaSrooms | 20+ years in procurement and supply chain | ex-Microsoft
That distinction matters more than it might appear. A company can sit comfortably within its industry benchmark and still be carrying recoverable waste well into the double digits. The three organisations referenced earlier in this piece were not outliers. Their spend profiles looked reasonable at the headline level. The issues only became visible when someone looked at what was actually inside the stack.
For acquisitions carrying material technology spend, the difference between a percentage assumption and what a structured review finds is frequently the difference between a satisfactory return and a substantially better one. The data to close that gap exists inside every target company. The question is whether it gets examined before the deal closes or after, when the leverage to act on it has largely gone.
The Data Is There Before You Close. Most Teams Look After.
If you are currently working through a transaction, start with the normalised technology cost base this week. Request the full itemised breakdown, map it against the benchmark reference, and identify whether the composition of spend supports the investment thesis or complicates it. That exercise alone will tell you whether you are looking at a well-governed technology environment or one that will require more capital and more time than the model currently reflects.
If you are preparing for a process or building a deal thesis, completing a benchmark-grade technology spend assessment before the process opens means entering due diligence with evidence-based assumptions rather than building them under competitive time pressure, when every day of analysis costs negotiating leverage.
The most expensive technology environment in any acquisition is not the one with the highest spend. It is the one nobody examined before signing.
