Executive summary
Technology diligence is built into the deal process to identify risks and validate that systems are stable and can support a transaction. But those findings don't answer the question buyers are actually underwriting: Can the company's technology ecosystem support the growth and scalability assumed in the deal model? To ensure the technology they're buying will actually strengthen the deal thesis, buyers need to test technology capabilities against the commercial, operational and financial outcomes they can support, and take a value engineering approach to diligence.
Move from risk assessment to conviction-oriented value engineering
In many M&A deals today, the technology diligence process often ends with a reassuring conclusion that the platform is stable, systems are working and the risks are manageable. While a clean technology finding helps a transaction move forward, it doesn't answer the question most investors are actually asking: Can the company's technology, digital capabilities and AI readiness support the growth, margin expansion and enterprise value assumed in the deal model?
"Many buyers are still looking at technology through the wrong lens,” said TK Kakar, Grant Thornton Technology M&A Partner. “Too few recognize the role technology plays as a driver of the deal thesis, rather than simply a box to check during diligence.”
A company's value is built not only on the technology it has today, but also on the commercial, operational and financial outcomes that technology can enable. Buyers must assess technology as a strategic value driver focused on testing the deal thesis, identifying opportunities for value creation and strengthening conviction in the deal thesis.
Building conviction requires evidence-based confidence that the investment thesis is achievable. This requires a clear view of whether the business has the technology, digital capabilities, data assets, operating model, talent and execution capacity necessary to achieve the outcomes being underwritten and whether investment required is reflected in the deal model.
Questions to evaluate this often include:
- Can the company achieve revenue growth assumptions and sustain its competitive advantage?
- Can it expand margins without affecting service levels or customer experience?
- Can it scale without increasing costs at the same rate?
- Can it deliver the product roadmap required to support forecasted growth?
- Can digital capabilities and AI improve commercial and operational decision-making and deliver measurable commercial and operational value
- Can the business adapt to technology disruption and changing customer expectations?
- Can management execute the required changes within the investment period and planned budget?
- Will these capabilities strengthen the company’s strategic positioning and value at exit?
"A platform can pass diligence and satisfy insurance requirements and still be fundamentally incapable of supporting the value creation plan that justified the investment," Kakar said. "Deal value ultimately depends on whether technology can support the company's growth, margins and ability to execute the investment thesis."
Clean technology does not always mean scalable
Technology can perform well today, and still may not be able to support longer-term growth. In practice, that can look like:
- An application environment that functions properly, but lacks the integration and data required to automate operations
- A platform that performs reliably at current volumes, but requires substantial investment to support the growth forecast
- A software product that is technically sound, but is under an organization that lacks the capacity to deliver the roadmap assumed in the revenue plan
- A company that possesses large amounts of data, but lacks the quality, governance and operating discipline required to use that data effectively
These issues rarely appear as material diligence findings. They often appear later, when technology is assessed against the outcomes buyers expect the business to deliver, and even when transaction protections are in place. Representations and warranties insurance may protect against specific breaches of seller representation, but it doesn't protect EBITDA assumptions, growth targets or value creation plans.
Case study: Where a stamp of clean technology hid opportunity
During diligence, a private equity buyer evaluating a middle-market bathroom fixtures manufacturer found no material technology concerns. But sales representatives lacked real-time inventory and production information, so they could not suggest alternatives when a requested product was unavailable, and customers canceled orders. Giving representatives that information and relevant product alternatives gave the buyer a basis to consider a potential improvement in EBITDA.
“That's why a clean technology report can create false confidence,” Kakar said. "Technology diligence that relies on risk assessment examines whether the technology is likely to fail. A new approach must be embraced to examine whether the technology can actually help the investment succeed.”
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Technology must be tested against the deal thesis
Most investment theses depend on technology, even when technology is not explicitly identified as a central part of the deal.
"The technology diligence lens must move beyond describing the technology that exists today and show how technology could support or constrain the performance a buyer is underwriting," Kakar said.
But that can't be answered by examining technology on its own. It requires connected insights across the commercial, operational, financial and technology dimensions of the business.
Connected insights go beyond integrated diligence
Integrated diligence is important, but bringing multiple workstreams together doesn't automatically create conviction.
"Connected insights start with the business outcome and bring the relevant commercial, operational, financial and technology perspectives together to solve for that outcome," Kakar said.
For example, a commercial team may identify an opportunity to increase customer retention. The technology question is whether the company has the data, digital channels and decision tools required to act on that opportunity. The operational question is whether the company can fulfill the resulting demand. The financial question is whether the revenue benefit and required investment produce an attractive return.
These should be viewed as different dimensions of the same value thesis, rather than separate diligence questions.
Value engineering connects technology to business outcomes
Value engineering is the process of identifying and quantifying the technology-driven value that delivers the commercial, operational and financial outcomes in a deal thesis. This approach bridges technology capabilities to their impact on EBITDA, and starts with the buyer identifying the business outcomes they want to achieve and how tech can contribute to them.
"Technology teams often seek an outcome that ends with a platform, an application or an AI use case. But they should instead be looking at the business outcome: what forecasting, pricing or other business outcomes does the technology help improve?” Kakar said. “That’s what value engineering helps teams discover.”
| Technology driven outcomes that could be delivered through value engineering | ||
| Commercial | Operational | Financial |
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Buyers need this perspective during diligence, when they are testing whether the value creation plan is achievable and what it will take to deliver. It helps them distinguish opportunities that are practical within the investment period from those that require more time, capital or organizational change. The resulting priorities can then inform the post-close execution plan.
Putting value engineering into practice
Value engineering requires determining what is practical for the business, quantifying the value and developing an executable plan with clear ownership, sequencing and measurable results,” Kakar said.
The art of the possible
The first step to a value engineering approach to technology diligence is to understand what technology, digital capabilities, data and AI could enable. This requires knowledge of the industry, the customer, the operating model and relevant technology developments.
The assessment should identify where the business could operate differently, where decisions could improve and where digital capabilities could create new sources of growth or efficiency. This process helps the buyer discover value opportunities that may not be visible when diligence is limited to the existing technology environment.
Pragmatic outcomes
The second step determines which opportunities are practical for the company under the proposed ownership model and within the investment period. The opportunity must be grounded in the company's current maturity, available data, management capacity, technology foundation, capital requirements and ability to absorb change.
Pragmatic value engineering converts ideas into specific opportunities, each supported by an investment requirement, timing, dependencies, risks and expected business benefit.
Precision execution
The final piece of value engineering translates the value opportunities into an executable plan. That plan must define what needs to happen before close, requirements for Day 1, which initiatives should begin during the first 100 days and how the broader transformation should be sequenced.
The plan should identify accountable owners, funding requirements, operational dependencies, decision points and measurable outcomes. It must also recognize that value creation is not solely the responsibility of the technology organization.
"Technology may enable the change, but commercial, operational and functional leaders must own the business outcomes," Kakar said.
A new mandate for technology M&A
Risk assessment will always be core to traditional technology diligence because a value creation plan can’t be built on an insecure foundation. But it also has an opportunity to build conviction by connecting the investment thesis to the company's commercial, operational, financial and technology environments.
To assess whether technology can support the value creation plan, deal teams need financial, commercial, operational and technology teams working from the same assumptions. Together, they can identify what the technology could improve, determine what is practical for the business to achieve and execute, and quantify the potential impact across functions.
“Technology M&A needs move from assessing risk to addressing how technology, digital capabilities and AI can help build a more valuable business than the one being acquired,” Kakar said. “A clean technology report helps close the deal. But from there, connected thinking builds conviction in the deal thesis, and value engineering turns that conviction into measurable results.”
Content disclaimer
This Grant Thornton Advisors LLC content provides information and comments on current issues and developments. It is not a comprehensive analysis of the subject matter covered. It is not, and should not be construed as, accounting, legal, tax, or professional advice provided by Grant Thornton Advisors LLC. All relevant facts and circumstances, including the pertinent authoritative literature, need to be considered to arrive at conclusions that comply with matters addressed in this content.
Grant Thornton Advisors LLC and its subsidiary entities are not licensed CPA firms.
For additional information on topics covered in this content, contact a Grant Thornton Advisors LLC professional.
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