How private equity portfolio companies create value in practice
A PE fund buys a company, and then what? In practice, it’s a series of concrete actions spread over time. The first step is usually tidying up – implementing proper budgeting, clear KPIs, and monthly reports, because many Polish companies simply don't have them. The fund operator meets with management monthly, checks the numbers, and together they make decisions: do we acquire a competitor, invest in a new production line, or perhaps reduce costs? Often, the "buy and build" strategy is key – the fund helps the company acquire smaller competitors and build a market leader. And now the latest trend: more and more funds are using AI to streamline processes and find ways to increase profits, because a company with well-implemented AI is simply worth more when sold.
Why value creation does not always translate into results in portfolio companies
Problem 1: Long-term investments, short-term valuation
You buy a manufacturing company for 50 million. You see that if you invest 5 million in automating the line, EBITDA will jump by 3 million annually in 18 months. Great deal – the IRR looks fantastic. The problem? In a year, the fund is nearing the end of its investment period, and you need to look for an exit. You put the company up for sale. The buyer opens the data, and what do they see? EBITDA lower than a year ago (because the project is just getting started), new debt (because you financed the investment), implementation costs in the profit and loss statement.
You created value, but it hasn't landed in the numbers yet. And the buyer pays for numbers.
Problem 2: Digital transformation that transforms nothing
You've probably seen it hundreds of times. A company spends half a million on CRM, hires a Chief Digital Officer, gives presentations with PowerPoints full of arrows and clouds. A year later: the sales team is back to Excel, the system is dormant, and the only difference is higher costs. During due diligence, the buyer asks specifically: "how much has the margin increased?", "how many people have you saved?". The answer: "we are in a transformation phase" convinces no one. Without hard data, there is no higher valuation.
Problem 3: You improve profits, the market changes multiples
You work hard for two years. EBITDA grows from 12% to 18% margin. Great job. However, in the meantime, multiples in your sector have fallen. Interest rates have gone up, sentiment has changed. Your company is objectively better, but worth less. It's not your fault, but the result is the same.
Problem 4: AI on slides, not in financial results
You run pilots, test ChatGPT, publish case studies on LinkedIn. Management talks about AI at every meeting. During due diligence, the buyer asks: "How much have you saved thanks to AI?". The answer: "We are experimenting, we have 3 pilots, the team is trained." Zero hard numbers. Zero documented savings. AI as a buzzword does not increase valuation – only what is visible in EBITDA counts.
What is the role of a private equity fund in operational value creation?
A fund doesn't just provide money – it provides access to proven solutions from other portfolio companies and a network of experts who have seen the same problems dozens of times. The operator comes with specific tools: ready-made reporting models, a list of trusted IT providers, contacts to managers who have already undergone a similar transformation. In practice, it often looks like this: "In three of our other companies, we implemented the same WMS system and we know all the pitfalls – we'll give you a playbook and contact to an integrator who can handle it in 4 months instead of 12." The value lies not in the knowledge of "what to do," but in the knowledge of "how NOT to screw it up" – the fund has already paid for all the lessons on other projects.
What organizational barriers most often block value creation in practice?
The management team of the previous owner remains on board and deep down still believes that "their way worked for 20 years, so why change it" – they treat every fund initiative as a personal attack.
IT systems are so archaic that even basic KPIs have to be collected manually from Excels sent by email – there is no chance for quick data-driven decisions. The company culture is "we've always done it this way" and a fear of responsibility – no one wants to be the one who approved a change, because if it doesn't work out, they'll be blamed.
And on top of that, silos: production doesn't communicate with sales, finance doesn't understand operations, IT operates independently of the business – each department has its own goals and no one looks at the bigger picture.
How to approach value creation to support EBITDA growth
Personally, I don't quite understand this obsession with EBITDA – even as a finance person. Or perhaps precisely because I’ve seen many companies with beautiful EBITDA, under which hidden costs were labelled "below the line." Value cannot be created through accounting tricks.
The second issue is investments and actions that don't align with exit timelines. I know... it sounds bad, but that's how PE works. You buy a company, transform it, and sell it. The transformation must be completed before the sale, so that the effects are visible.
And the last point for today – AI hype. Implement AI wisely. A company's value won't increase just because someone spent $$ on AI initiatives. Like any other project, these expenditures must also bring a return on investment and increase operational revenue.
Value creation in a portfolio company often diverges from the exit result because long-term investments don't have time to show up in the numbers, digital transformations end up as higher costs without effects, and changes in market multiples erode operational improvements. A PE fund brings value not through capital, but through proven playbooks and "how not to mess up" implementation knowledge – the problem is that organizational barriers (management resistance, archaic IT, "we've always done it this way" culture) block most initiatives. The solution? Select only projects that will have time to show an effect on EBITDA before sale, document everything with hard data from day one, and forget the AI hype – only what increases revenue or reduces costs matters.
