Company Valuation: The Most Valuable Part Does Not Fit the Model

Entrepreneur and investor Vladan Hejnic has set out a series of parameters he uses to judge whether a company has a future or not.

Commentary by Vladan Hejnic I have been through several negotiations about selling part or all of a company. I have been on both sides, as the seller and as the buyer. And every time, value rested on two legs: past results and a projection of future earnings. That model feels outdated to me, but we have no replacement for it. So I am trying to describe what I look for instead.

Until recently it worked according to a simple key. Very young companies were valued mainly on the promise of the future, because they had nothing else. The older the company, the firmer the foundation the past provided. From the history of revenues, margins and customer behaviour, much could be predicted. But today’s era is changing entire industries and demolishing this proven approach.

What am I talking about? I am not talking about companies in sectors that require large investments in physical technology, such as machines, production halls or vehicle fleets. There, capital still creates a barrier and the past says something about the future. I am talking about companies that provide services and develop software or hardware.

According to the Multiples portal, the median for publicly traded horizontal SaaS in August 2026 hovered around 2.2 times revenue, not the ten times the market grew used to in 2020 and 2021. Just over two! And the same analysis says something every software company owner should hear: the market today values a company by whether it uses AI or is dying because of AI. The spread between these categories is enormous. While devops sells at 8.7 times revenue, adtech goes for 0.9.

In the reports this collapse came to be called the SaaS apocalypse, and it wrote off value from software companies in the hundreds of billions, perhaps trillions of dollars. It did not fall because those companies suddenly stopped growing. The market simply stopped believing the projection. Exactly the projection I describe above.

We are therefore approaching a time when large companies will fail far faster and young ones will become mid-sized very quickly. AI will of course help them do it. Scaling businesses will happen through systems, not through people, and it will be significantly less demanding.

The numbers back this trend from both sides. According to a report by the consultancy Huron, the average time a company stays in the S&P 500 index shortened from 33 years in 1965 to 20 years in 1990 and is heading toward 15.

And what is happening on the side of small companies? The startup Cursor (acquired by SpaceX) went from its first million to a hundred million dollars in annual revenue in roughly a year. Sweden’s Lovable managed the same with forty-five people. Ten years ago, reaching a hundred million would have required hundreds of employees and several funding rounds.

All of this places enormous demands on the adaptability and flexibility of people, management and owners. If large companies fail to manage the transformation in time and at speed, their positions will be shaken and some will not survive. Conversely, small companies where adaptability, innovation and flexibility are part of their cultural DNA will be highly valued.

“Today’s era is changing entire industries and demolishing this proven approach.

We have already seen several times that a large strategic partner bought a smaller company not for its product or profitability, but for the capabilities of its team. Microsoft paid roughly 650 million dollars for Inflection, and it was not about a chatbot, it was about Mustafa Suleyman and his research team. Google paid 2.7 billion for Character.AI for a non-exclusive licence and two founders. And a year later 2.4 billion dollars so that Windsurf CEO Varun Mohan would join DeepMind with the core of his research team. Neither deal can be justified by an EBITDA multiple. Neither rests on a product revenue projection. What was being bought was adaptability and the ability to build the next thing.

How can financial valuation models capture this ability to adapt? We will have to work that out. Perhaps a set of parameters and questions will emerge from which a coefficient can be derived. Here is what I would ask about. It is not a finished methodology, but a first draft I want someone smarter to tear apart. It is in the following infobox.

Seven Points to Look At

1.The share of revenue from what did not exist two years ago. The 3M group has used this indicator since 1988 under the name New Product Vitality Index, and today most large companies with their own development track it in some form. For dynamic sectors I would shorten the window to twenty-four months.

2.How long it takes the company to decide. Not the quality of the decision, which only shows after the outcome. The time from “we know there is a problem” to “it is decided and we are moving”. This can be established from history and cannot be staged for a single meeting.

3.How many times the company killed something of its own that was still earning. The ability to abandon something is often rarer than the ability to launch something.

4.How much of the know-how sits in heads and how much in systems. A company where the process is documented, automated and transferable adapts. A company where everything rests on three people adapts only as fast as those three can retrain.

5.The trend in revenue per employee, not its absolute level. The direction of this curve over the past two years says more about how a company scales than an entire chapter on strategy.

6.Retention of key people and whether the buyer can even name them. When nobody in due diligence can say which five people the company rests on, that in itself is a finding.

7.How many decisions are reversible. A company built only on long irrevocable commitments has less room to manoeuvre regardless of how good its culture is.

One last, uncomfortable question: How do you tell adaptability from luck? Evaluate the process, not the outcome. Translated into due diligence language, do not ask whether the company got the last big change right, but how it arrived at that decision, who knew about it first and what the company did with that information. Getting it right can be chance. How a company learned about the change and how quickly it responded is not.

Source: CC.cz