Over the past three decades, I have helped businesses at every stage of growth — from early expansion through rapid national scaling to successful sales to private equity. I have advised institutional landlords, worked alongside PE-backed management teams, and watched the due diligence process from both sides of the table.
One pattern has become unmistakable over the past five years: the buyers who are paying the highest multiples are the ones asking the most detailed questions about intangible assets. Not just intellectual property in the formal sense — patents, trademarks, registered designs — but the full range of value-creating assets that traditional accounting does not capture: proprietary technology, customer relationships, organisational knowledge, data assets, and brand equity.
This is not a passing trend. It reflects a fundamental shift in where enterprise value resides. When 92% of S&P 500 value is attributable to intangible assets, buyers who fail to assess them are flying blind. And sellers who fail to present them are leaving money on the table.
My career started in commercial property — an industry where asset valuation is second nature. Surveyors assess buildings, investors price them against rental yields, lenders collateralise them against loan books. There is a mature, regulated, well-understood framework for determining what a physical asset is worth.
When I moved into broader commercial growth advisory, I watched the same kinds of businesses — solid, growing, profitable — achieve dramatically different valuations at exit. Two companies in the same sector, with similar revenue and EBITDA, would sell at multiples that differed by 2-3x. The difference was almost never in the financials. It was in the assets the financials could not see.
The company that sold at a 12x multiple had a proprietary technology platform with deep customer integration. It had documented processes that made the business operate independently of its founder. It had customer contracts with high switching costs and measurable lifetime value. It had a brand that attracted talent without recruitment agency fees.
The company that sold at a 6x multiple had the same revenue. But its technology was a collection of customised off-the-shelf tools. Its processes were in the founder's head. Its customer relationships were personal, not institutional. Its brand was functional, not distinctive.
The spread between premium and average exit multiples is increasingly explained by intangible asset quality and visibility. Buyers are not simply paying more for intangible assets — they are paying significantly less when intangible assets cannot be identified, measured, and defended during due diligence.
Having worked alongside PE firms and their portfolio companies for many years, I have observed a clear evolution in what due diligence teams prioritise. The traditional focus — financial performance, legal compliance, market position — remains essential. But it is now the floor, not the ceiling.
The highest-quality PE buyers now conduct structured assessment across five intangible asset categories:
What they want to know: Does the company own its technology, or does it depend on third-party platforms? How defensible is the technology moat? What is the replacement cost — how much would it cost to build this from scratch?
What impresses them: Proprietary systems with measurable performance advantages. APIs with external integration partners. Technology roadmaps that demonstrate ongoing investment and competitive positioning.
What concerns them: Heavy reliance on a single vendor. Technology built by a single developer with no documentation. Custom integrations that would be expensive to maintain or rebuild.
What they want to know: How sticky are the customer relationships? What is the net revenue retention rate? Are relationships institutional (with the company) or personal (with the founder)?
What impresses them: High net revenue retention (above 110%). Long average contract lengths. Customer relationships that survive staff turnover. Measured customer lifetime value with clear drivers.
What concerns them: Revenue concentrated in a small number of accounts. Customer relationships that depend on the founder's personal network. No formal measurement of customer health or lifetime value.
I advised a professional services firm preparing for PE exit. Their largest client represented 28% of revenue, the founder personally managed the top 10 accounts, and there was no documented client success methodology. We spent 18 months institutionalising client relationships, documenting service delivery frameworks, and diversifying the revenue base. The eventual sale achieved a 2x premium over the initial indicative valuation — the buyer explicitly cited the quality of the client relationship documentation in their investment committee paper.
What they want to know: Can this business operate without its current management team? Are processes documented and repeatable? How dependent is the business on key individuals?
What impresses them: Documented standard operating procedures. Quality management systems. Succession planning for key roles. Operational metrics that demonstrate process consistency.
What concerns them: Founder dependency. Undocumented tribal knowledge. High staff turnover in critical functions. No process for capturing and transferring institutional knowledge.
In my experience, founder-dependent businesses routinely sell at a 25-40% discount to businesses with equivalent revenue but independent operations. PE buyers quantify this risk in their models: they estimate the probability and cost of founder departure, then adjust their offer accordingly. Making yourself dispensable is one of the most value-creating things a founder can do before exit — and it is entirely an exercise in building organisational capital.
What they want to know: Does the company have unique data that competitors cannot access? Is the data structured, maintained, and usable? Does the data create competitive advantage in operations, product development, or customer engagement?
What impresses them: Proprietary datasets that improve with use. Data-driven decision-making embedded in operations. Clean, structured data that can be analysed and leveraged post-acquisition.
What concerns them: Data scattered across spreadsheets and personal drives. No data governance or quality standards. Compliance risks around data collection and processing (GDPR, CCPA).
What they want to know: Is the brand recognised in the target market? Does it attract customers and talent organically? Is there brand equity that would survive a change of ownership?
What impresses them: Measurable brand-driven customer acquisition (organic traffic, direct enquiries, referrals). Employer brand strength (application volumes, offer acceptance rates). Market positioning that is defensible and distinctive.
What concerns them: Brand entirely dependent on a single individual. No measurement of brand contribution to revenue. Brand that lacks distinctiveness in a crowded market.
Despite the growing importance of intangible assets to enterprise value, most businesses preparing for PE sale focus overwhelmingly on financial and legal preparation. This creates a significant gap between the value that exists in the business and the value that is visible during due diligence.
The businesses that bridge this gap — that present their intangible assets with the same rigour and structure as their financial statements — consistently achieve premium valuations. Not because the assets were not there before, but because buyers could finally see them.
Based on what I have seen work in practice, here is the programme I recommend for businesses 12-18 months from a potential PE process.
Identify and categorise all intangible assets across the five categories. Assess current documentation quality and measurement maturity. This is the baseline from which all improvement is measured.
Document key processes, customer engagement methodologies, technology architecture, and data governance frameworks. Establish baseline metrics: customer LTV, NRR, technology replacement cost, process dependency maps.
Address the gaps identified in the audit. Reduce founder dependency. Institutionalise customer relationships. Document and protect IP. Build data governance. Strengthen the brand independent of individuals.
Apply structured valuation methodologies to each intangible asset category. Relief-from-royalty for technology and brand. Multi-period excess earnings for customer relationships. Replacement cost for organisational capital and data assets.
Package intangible asset evidence into a structured data room section. Prepare management narratives that connect intangible assets to financial performance. Rehearse responses to buyer questions about technology dependency, customer concentration, and founder risk.
AI has added a new dimension to this preparation, and it cuts both ways.
For sellers, AI investments create intangible assets — technology capital, data assets, organisational capital — that can significantly enhance enterprise value if properly documented and measured. A company that has deployed AI to automate operations, personalise customer engagement, and codify institutional knowledge has created genuine competitive advantage that buyers will pay for.
For buyers, AI capability is becoming a core due diligence question. PE firms increasingly assess whether portfolio companies have AI-ready data infrastructure, whether their technology platforms can integrate AI capabilities, and whether their organisational culture can adapt to AI-augmented workflows.
| AI Readiness Factor | Value Enhancer | Value Destroyer |
|---|---|---|
| Data infrastructure | Clean, structured, governed datasets ready for AI | Siloed, unstructured data with compliance risks |
| Technology platform | Modern, API-driven, AI-integration capable | Legacy systems requiring costly migration |
| Organisational culture | Adaptable, learning-oriented, AI-curious | Resistant to change, manual-process dependent |
| AI deployment | Genuine capability with measurable outcomes | AI-washing — superficial claims without substance |
PE buyers are increasingly sophisticated about distinguishing genuine AI capability from AI-washing. Superficial AI claims that cannot withstand due diligence scrutiny will damage credibility and reduce valuation. Only present AI capability that you can demonstrate with evidence.
The commercial property industry solved the asset visibility problem decades ago. Every commercial building has a surveyor's report, a yield calculation, a comparable transactions analysis, and a maintenance schedule. Investors, lenders, and buyers can assess the value of a commercial property with confidence because the measurement frameworks are established, standardised, and trusted.
Intangible assets deserve the same treatment. The businesses that will achieve the highest valuations in the next cycle of PE activity will be those that present their intangible assets — technology, customers, processes, data, brand — with the same structured rigour that a commercial property investor expects from a building survey.
Intangible asset preparation is not about creating value that does not exist. It is about making the value that already exists visible, measurable, and defensible. The assets are already there — in your technology platform, your customer relationships, your team's institutional knowledge, your data. The question is whether a buyer can see them, quantify them, and price them into their model.
The Opagio Growth Platform provides the structured framework for this preparation — helping businesses identify, measure, and present their intangible assets with the rigour that PE buyers require. For businesses 12-18 months from a potential PE process, this preparation is not optional. It is the difference between a standard multiple and a premium one.
Mark Hillier is Co-Founder and Chief Commercial Officer of Opagio. He brings 30+ years of experience advising businesses through growth, scaling, and successful PE exits. His client roster includes Legal & General, AEW UK Investment Management, and Salmon Harvester. At Opagio, Mark leads go-to-market strategy and client acquisition across the SME and investor markets.
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