Building for what’s next

Most established businesses are designed to become better at what they already do. That is entirely rational. Existing customers need to be served, products improved, operations made more efficient and revenue protected. Over time, organisations develop capabilities, processes, systems and measures around a business they understand increasingly well.

There is enormous value in getting better at the core. In fact, as I argued in The next generation of growth, much of a company’s future growth will often come from strengthening or expanding what it already has.

But there is a tension hidden inside that success. The capabilities that make an organisation exceptionally good at running today’s business are not necessarily the same capabilities that allow it to imagine and create tomorrow’s.

I think that tension is becoming more important as the range of what businesses can create expands. AI is changing the economics of building products and services, technology is making previously difficult propositions possible, industries increasingly overlap, and new combinations of capabilities can create businesses that would have been unrealistic only a few years ago.

For an established company, the natural response is to consider what these developments mean for the business it already has. That is important, but it can also be limiting. Sometimes the more interesting question is what the company could now create that it could not create before.

That takes us beyond improving the existing business and into the territory of business creation.

Giving an idea room to become a business

New ideas inside established organisations have an awkward problem: we naturally evaluate them using what we already know.

We compare them with existing customers, margins, sales channels, processes and expectations about how the business should perform. Those comparisons provide useful discipline, but they can also make genuinely new possibilities appear unattractive precisely because they are new.

A proposition aimed at a different customer may not fit the existing sales organisation. A new service may have unattractive economics before it reaches scale. An AI-native proposition may depend on capabilities the organisation does not yet possess. Something that could eventually become a significant new business may initially look small when placed beside the revenue of the core.

None of those things tells us that the idea is good. But neither do they necessarily tell us that it is bad. Often they simply tell us that we do not know enough yet.

I think the distinction between bad and unknown is one of the most important in business building.

Established companies understandably prefer certainty. Plans, forecasts, budgets and business cases exist because capital has to be allocated responsibly. The difficulty begins when we expect a new venture to demonstrate the same level of certainty as a business that has operated for decades.

An early venture cannot honestly provide that certainty, and trying to manufacture it tends to produce false precision. We can build a spreadsheet predicting revenue five years into the future, but the sophistication of the spreadsheet does not make the assumptions behind it any more true.

A more useful business case makes those assumptions visible and helps us determine which ones need to be tested first. We may believe a particular customer has an important problem, that our proposition can solve it, that customers will change their behaviour, that we can deliver the solution reliably and that the economics can eventually work. At the beginning, these are beliefs rather than facts.

The job is not to disguise that uncertainty.

It is to reduce it.

This is why I think investment in a new business should develop differently from investment in an established one. When uncertainty is high, much of the purpose of investment should be to create evidence. As evidence becomes stronger, the organisation can make larger commitments with a better understanding of what it is committing to.

That is the principle behind Evidence Before Scale.

The important idea behind the model is that big ambition does not require a big initial bet.

A company does not always need to build the product before it can learn whether customers understand the proposition. It does not need to automate an entire service before learning how customers use it. Nor does it necessarily need to build a complete technology platform before testing whether its most important technical assumption is true.

There are many ways of making an idea sufficiently real to learn from it without pretending that we have already decided to build the final business.

This is where making becomes so important. The moment an idea becomes tangible, even in an incomplete form, it begins to encounter reality. Customers behave differently from our assumptions. Technical constraints become visible. Operational implications emerge. The economics become less theoretical.

Reality starts to replace belief with evidence.

The venture eventually has to become a business

One of the risks in innovation is that we become fascinated by the idea itself. We move from insight to concept and from concept to product, but a successful venture is not simply a compelling idea or even a good product. Eventually it has to become a business.

That means the proposition and customer experience have to connect to technology, operations, distribution, economics and a viable business model. Customers have to be found and served. The organisation has to be able to deliver what has been promised. The cost of doing so has to make sense. Over time, the venture needs capabilities and structures that allow it to function without continuous intervention from the small group of people who originally created it.

This is where our idea of The Business Is a System becomes particularly relevant.

A venture may begin with one interesting insight, a technology or an unmet customer need, but eventually the entire value creation system has to work together. In the earliest stages many of those elements can be deliberately incomplete because the purpose is still to learn. As the evidence grows, however, the components have to become increasingly coherent.

I think this transition from something people might want to a business that actually works is where much of the difficult work in venture building sits.

It is also why business building is inherently multidisciplinary. Customer understanding, design, technology, commercial thinking, operations and economics cannot remain separate workstreams indefinitely. They have to converge around the same emerging business.

The venture becomes real when those different perspectives begin to work as one system.

Using the core without being trapped by it

Corporate venture building is sometimes described as though established companies should learn to behave like start-ups. I have never found that comparison particularly helpful.

An established business is not a start-up, and there is no obvious reason it should pretend to be one.

It may already possess things a start-up would spend years trying to acquire: customer relationships, distribution, domain expertise, data, technology, capital, credibility and people who understand an industry in extraordinary depth. Those assets can give a new venture a significant advantage.

The difficulty is that the same organisation also contains processes, incentives, systems and assumptions designed around the existing business. What creates stability and efficiency in the core can make experimentation with something fundamentally different surprisingly difficult.

The challenge is therefore not to separate the new business from the core as quickly as possible, nor to integrate it completely. It is to design the relationship deliberately.

Research into repeat corporate venture builders supports this distinction. More experienced builders tend to create greater independence for new ventures while maintaining access to senior sponsorship and valuable capabilities from the parent organisation.

I think there is a useful principle in this:

Borrow the advantage. Escape the constraint.

A new venture should be able to borrow whatever genuinely gives it an advantage from the existing business while avoiding the assumption that it must inherit everything else.

Customer access might be valuable while the existing sales process is not. Domain expertise may be critical while existing technology architecture creates unnecessary constraints. The parent company’s credibility might open doors while its established brand would confuse the proposition. Capital may provide runway while existing investment expectations make it impossible to learn properly.

The choices will be different for every venture.

The important thing is that they are choices.

The emerging business should be exposed to market reality rather than forced to reproduce the organisational reality of the company that created it.

Building is becoming cheaper. Learning should become better.

AI adds another dimension to this because it is beginning to change the economics of making itself.

Historically, a significant part of the cost of creating a new business occurred before anyone really knew whether the business deserved to exist. Research took time, concepts needed specialists, prototypes had to be produced, software had to be developed, and many operational activities required people long before there was enough evidence to justify building them at scale.

AI is beginning to compress parts of that work. McKinsey’s recent research into AI-first venture building points to faster validation cycles, greater output from smaller teams and the possibility of reaching meaningful scale with fewer resources than traditional venture-building models required.

The obvious interpretation is that new businesses can become cheaper to build.

I think the more interesting interpretation is that they can become cheaper to learn about.

If the cost of making something tangible falls, we do not necessarily have to use that advantage to rush more quickly towards a predetermined solution. We can use it to explore alternatives. Different propositions can be made tangible earlier, different experiences tested, assumptions explored and working versions put in front of people before the organisation has committed heavily to one direction.

That creates an important connection between AI and Evidence Before Scale. Lower cost of making can give us more evidence for the same investment, which should allow us to make better decisions about where larger investments belong.

Speed matters, but better decisions matter more.

Knowing when not to build

This brings us to one of the less celebrated parts of venture building.

Not every venture should survive.

There is a tendency in innovation to celebrate failure as though failure itself were valuable. I don’t think it is. What is valuable is learning something important early enough for it to change what we do next.

If an organisation spends two years and a large amount of money building something nobody wants, describing the outcome as learning does not make the investment wise. If the same organisation discovers in a few weeks that a fundamental assumption is wrong and decides not to invest further, that can be an excellent outcome.

An early venture therefore exists partly to discover whether it deserves to continue existing.

That can be psychologically difficult inside organisations because ideas gradually acquire owners, teams, names and sponsors. The further they travel through the organisation, the more stopping can begin to feel like failure.

A good venture process needs to resist that dynamic.

The purpose of an early stage is not automatically to reach the next stage. It is to create enough evidence to make a better decision. Sometimes the evidence tells us to continue. Sometimes it tells us that the proposition needs to change substantially. Sometimes it tells us to stop.

All of those outcomes can represent progress if we know more than we did before.

This distinction also makes it possible to remain ambitious without becoming attached to a particular solution. We can continue to believe that an important customer problem deserves solving while accepting that our first idea for solving it was wrong.

From a venture to a capability

Something else happens when an organisation builds more than one new business.

It starts learning not only about the individual ventures but about how to build.

Teams become better at identifying the assumptions that matter. They learn how much evidence is useful at different stages, how to prototype without overbuilding, when specialist capabilities are required, how to work with uncertainty and when a new business needs more independence from the core.

Over time, business building itself can become an organisational capability.

Recent McKinsey research into repeat venture builders describes a clear “serial builder advantage”. Companies with greater experience of creating new businesses report stronger returns on venture investment than companies approaching venture building for the first time.

I find that interesting because it suggests that the strategic value of venture building may eventually become larger than any one venture.

The organisation is developing the ability to create new businesses repeatedly.

That connects directly to the broader idea of The Adaptive Business.

An adaptive business needs to be capable of changing the way it creates value as the world around it changes. Much of the time that will mean strengthening the core or extending existing capabilities into adjacent areas. Sometimes, however, the possibility will sit far enough from the existing business that changing the core is not enough.

Something new needs to be created.

This is the third territory in the growth model we developed earlier: strengthen the core → expand the core → create the new.

The important point is that Create the New does not necessarily mean searching for ideas with no connection to the existing business. Some of the strongest possibilities may begin with something the company already possesses: knowledge, a customer relationship, technology, data, intellectual property, distribution or an insight into a problem that others do not see.

The creative leap is to ask what else those assets could become.

At some point, the answer may no longer look like an extension of the existing business. It may need a different proposition, different economics, different capabilities and enough freedom to develop on its own terms.

At that point, adaptation becomes creation.

Building for what’s next

This is why I don’t see venture building as something separate from Business Design.

Business Design asks how different elements of a business need to come together to create value. Venture building applies that question to something that does not fully exist yet.

At the beginning there is a possibility surrounded by assumptions. As we make, test and learn, some assumptions disappear, others become stronger and the shape of the business gradually emerges.

I would capture that journey in one final, deliberately simple model.

The underlying questions evolve with it: first we are trying to understand whether the possibility could create meaningful value; then whether there is enough evidence to justify increasing our commitment; and eventually whether the proposition, delivery model and economics can become a business that genuinely works.

The purpose of venture building is therefore not to manufacture start-ups.

It is to give valuable possibilities a disciplined path towards becoming real businesses.

Some will eventually strengthen the organisation that created them. Some may need to become more independent. Others will be stopped when the evidence tells us that the original promise isn’t there. And occasionally one may become far more important than anyone imagined when the first rough version was created.

We cannot know which at the beginning. If we could, there would be very little need for venture building in the first place.

What we can do is create the conditions for learning: make enough of the idea to encounter reality, invest in proportion to the evidence and allow what we learn to change what we build.

The future of a business will not always emerge naturally from the business it has today.

Sometimes we have to build enough of that future to discover whether it deserves to exist.

And if it does, continue building until it becomes real.