Companies rarely suffer from too few ideas. Strategy meetings are full of new products, sales opportunities, emerging technologies and possible new business fields.
Somewhere there is a promising pilot, a customer has described a need that could become something larger, or a competitor is moving into a market that has not played a major role until now.
The executive team knows that something has to change. And yet the new business surprisingly often remains exactly there: in presentations, pilots and initiatives that are important in principle, but never important enough to prevail in the competition for capital and attention.
The Bertelsmann Stiftung study Innovative Milieus 2026 shows that a broader pattern lies behind this. It is based on a representative survey of 1,146 companies from manufacturing and industry-related service sectors in the IW Future Panel.
Together with earlier survey waves, it allows a comparison of Germany’s innovation landscape since 2019. The share of companies at the leading edge of innovation has fallen markedly over this period. In 2019, around one quarter of companies still belonged to the innovation-strong milieus; today, the figure is only 13 per cent. At the same time, the innovation-distant segment has grown from 27 per cent to almost 40 per cent.
It is not only the intensity of innovation that is changing, but also its character.
The former milieu of disruptive innovators no longer exists in the current typology. Radical innovation orientation has become less common, and initiatives that could substantially change business models or open up new business fields have lost importance.
Instead, innovation activity is increasingly focused on product improvements, processes and internal modernisation. Innovation is still taking place, but more often within the boundaries of the existing business.
For an individual company, this development is easy to understand. The existing business has customers, revenue, processes and experience indicating which investments may pay off.
A new business field initially consists of assumptions about a market that may emerge, customers who may buy, and a model that may become profitable. When both compete for the same resources, the existing business therefore has a considerable structural advantage.
The existing business can prove its urgency every day
Day-to-day operations come with concrete numbers, deadlines and obligations. An important customer is waiting for a decision, two major proposals must be completed, a project has escalated, and current financial performance demands attention. At that point, the new business field may have ten customer interviews, a prototype and the first indications that a market could exist.
When both sides need the same people, a comprehensible priority emerges. The head of sales first looks after the customer who is generating revenue today, IT first solves the problem in the existing system, and the executive team postpones the discussion about the new business model because a current earnings deviation has to be clarified. None of these decisions is problematic in isolation, but taken together they can leave a strategically important initiative making hardly any progress for months.
The existing business does not have to explain its importance because it is visible every day. The situation is different for the new business. At the beginning, it lacks precisely the evidence that gives established activities internal legitimacy: reliable revenue, historical margins, repeatable sales processes and dependable planning.
Anyone who evaluates such an initiative after only a few months using the same criteria as the core business is demanding certainty at a point when the real task is to reduce uncertainty systematically.
This is one of the defining features of business building in established companies:
New business needs enough freedom to emerge in the first place. At the same time, that freedom must not lead to years of experimentation without the economic substance of the initiative becoming more robust.
Several different proofs lie between an idea and a business
A convincing presentation, a working prototype and a first customer can all be important advances. Yet each proves something different. In early business initiatives, these distinctions are often blurred.
A prototype can show that a solution is technically feasible. A positive customer conversation can show that a problem appears relevant. A first order shows that at least one customer is willing to pay. None of these steps automatically proves that a repeatable and economically attractive business can emerge.
Four different maturity levels can therefore be distinguished in the development of a new business:
- Problem–solution fit: A relevant customer problem is sufficiently understood and the proposed solution creates recognisable value. The main task in this phase is not to build an interesting solution for an insignificant problem.
- Product–market fit: Interest turns into repeatable demand. More than a few pilot customers are prepared to buy the offer, and it becomes clearer which customer segment receives the greatest value.
- Business-model fit: Demand is not the only thing that works. Price, sales effort, delivery and costs add up to an economic logic from which an attractive business can emerge.
- Scale readiness: The model can grow without complexity, costs and bespoke work increasing at the same or an even higher rate than revenue.
These stages are not a mechanical checklist that every initiative passes through in the same order. They do, however, help answer one decisive question:
Which uncertainty needs to become smaller next before additional resources are committed?
→ A company that invests in a large technical platform immediately after ten positive customer conversations may be skipping the question of actual willingness to pay.
→ A company that builds a large sales organisation after three paying customers may not yet know whether those customers bought a repeatable offer or an individually tailored project.
→ A company can therefore generate revenue with a new offer and still be a long way from a robust business model.
The most difficult phase often begins after the first success
There is a great deal of discussion about early-stage innovation. Scaling is also a familiar term. The phase in between receives less attention, even though this is precisely where many new business initiatives get stuck.
An offer has found its first customers. The underlying need is no longer in question. Perhaps meaningful revenue is already being generated and expectations are growing internally that the business can now scale quickly. At the same time, much of it still works only because individual people devote extraordinary attention to the initiative.
The first salesperson knows every customer personally. The product team adapts features for individual orders. The executive team joins critical sales conversations. Operations finds pragmatic solutions for special requests. As long as the number of customers remains small, this can create the impression of a functioning business.
Growth changes the equation. What personal attention could solve for five customers will not automatically work for fifty. A successful offer has to become a repeatable system.
At this point, the central task shifts. The main question is no longer whether customers want the product. It is now whether the company can serve that demand economically.
Other metrics now become relevant. What are the true customer-acquisition costs? How long does it take for a customer to become profitable? Which parts of the offer can be standardised? How much implementation effort is required per customer? Which special requests add complexity without commanding an appropriate price? Which capabilities are needed for further growth, and which of them cannot be built at will?
This phase often determines whether an innovation actually becomes a business.
An early business case is not a forecast
Established companies understandably want to assess a new business as early as possible using the same criteria as the existing one. Anyone investing capital wants to know when revenue will be generated, what margin can be achieved and how long it will take for the investment to pay back. The problem lies less in these questions than in the certainty that early answers can suggest.
An established product with years of sales history can be planned comparatively well because prices, costs, conversion rates, customer behaviour and sales channels are known. For a new business field, the same variables initially rest on assumptions. A detailed five-year plan can therefore create an impression of precision even though the decisive parameters are not yet sufficiently understood.
At this stage, the business case serves a different purpose. It is less a forecast than a structured hypothesis about the conditions that must be met for an idea to become an economically attractive business. Market size, achievable prices, gross margin, customer-acquisition costs, necessary upfront investment and the greatest uncertainties should be made visible without pretending that they can already be predicted exactly.
The calculation changes with every new insight. An estimated price becomes a more credible price range after the first sales conversations. An assumed customer group becomes a more specific segment. A theoretical sales model generates initial data on how long a deal actually takes. A good business case at this stage does not improve because its numbers remain as stable as possible, but because fewer and fewer of its central assumptions remain pure guesses.
More innovation input does not automatically create more innovation success
One particularly interesting finding in the Bertelsmann study is that innovation cannot be explained by the quantity of resources deployed alone. Innovation input includes strategic focus, culture, capabilities, networks and organisational conditions. Overall, this input remains below the 2019 level. At the same time, some groups in the middle improved their innovation performance even though their innovation effort increased only moderately.
The authors draw an important conclusion: the absolute level of investment is not the only deciding factor. Strategic direction, targeted collaboration and capability building can have a stronger effect than simply expanding resources.
For companies, this matters because innovation capability cannot be reduced to a budget. A company can invest substantial resources in new technologies, pilot projects and programmes and still struggle to turn them into marketable products or new business fields. Conversely, more limited resources can be effective when they are concentrated on a few relevant initiatives and those initiatives are consistently moved closer to customers, the market and economic viability.
In a more difficult economic environment, the task therefore changes. It is less about maintaining as many innovation activities as possible and more about distinguishing between interesting possibilities and business opportunities that genuinely deserve further investment.
Technology is increasingly a prerequisite and therefore less often an advantage
The Bertelsmann study also examines the significance of 13 key technologies. Digital technologies in particular are gaining relevance across industries. Among the technology leaders, more than half of companies report that they already use artificial intelligence and machine learning intensively. For the next five years, almost every company in this group expects these technologies to be of high strategic importance. The Internet of Things, cybersecurity, and virtual and augmented reality are also continuing to spread.
This development changes the logic of technological differentiation. As a technology increasingly becomes standard equipment, using it no longer automatically creates a competitive advantage. What matters is what a company does with it.
A widely available tool that makes the same process somewhat more efficient for every competitor can make economic sense. It does not necessarily create a lasting difference. Technology becomes strategically more relevant when it solves a customer problem in a new way, changes an existing cost logic, enables a new product, or opens access to a market that previously could not be served economically.
This connects technology directly with business building. Access to the technology is only the beginning. The more demanding economic task is to develop an offer and ultimately a business model from it.
Not every good idea deserves the next round of investment
The longer a team works on a new product, the harder it becomes to decide to stop. Customers have been interviewed, prototypes have been built, people may have been hired and initial revenue generated. This can create the impression that ending the initiative would devalue all the work already done.
Yet a robust negative finding can have considerable economic value. If a test phase shows that customers find a problem interesting but are not willing to pay enough for the solution, a central uncertainty has been resolved. The same applies when customer acquisition would remain too expensive, the offer can only be sold through extensive customisation, or an attractive market exists but the company has no realistic way to build an advantage in it.
A sound investment logic therefore asks not only about progress to date at each stage. It asks what new evidence is available and which next investment that evidence justifies. The larger the investment becomes, the more robust the findings from the preceding stage should be.
This also changes the meaning of ending a project. An initiative that disproves an important assumption after a manageable capital investment may be economically more successful than a project that continues for years because no one defined a clear decision point.
Tomorrow’s business needs fewer ideas and more economic discipline
The Bertelsmann study describes an innovation landscape whose leading edge has become smaller and in which radical initiatives are less common. At the same time, digital technologies are spreading while more demanding technological capabilities remain concentrated among a smaller group of companies. Innovation is becoming more cautious and more strongly focused on existing products, processes and structures.
This does not justify a blanket call for more radical innovation. Not every company needs a new business model, and not every technological possibility deserves its own business field.
What matters is whether companies can identify relevant possibilities early and develop them further with economic discipline.
That includes distinguishing between technical success, customer interest, repeatable demand and a viable business model.
It also means taking seriously the difficult stretch between the first paying customers and a scalable business. This is where it becomes clear whether revenue is created only through the exceptional effort of a few individuals or whether there is a model that can actually be multiplied.
Companies therefore do not need as many ideas as possible for the future. They need a robust process through which a small number of ideas become either a viable new business or a well-founded decision against further investment. Innovation thus becomes less a matter of creative activity and more an entrepreneurial discipline that connects market, capital and execution.
Original source and inspiration:
Bertelsmann Stiftung: Innovative Milieus 2026. Die Innovationsfähigkeit der deutschen Unternehmen in schwierigen Zeiten. https://pub.bertelsmann-stiftung.de/Innovative-Milieus-2026/