In reinforcement learning (a field within AI), algorithms need to learn about an unexplored space. These algorithms need to balance exploration (learning about new options and possibilities) with exploitation (using the acquired knowledge to generate a good outcome). The general rule of thumb is that the less is known about the problem domain, the more the algorithm should focus on exploration. Similarly, the better the problem domain is understood, the more the algorithm should focus on exploitation.

The exploration/exploitation balance applies to companies too. Most companies have, for a long time, been operating in a business ecosystem that was stable and well understood. There were competitors, of course, but everyone basically behaved the same way, got access to new technologies at about the same time, responded to customers the same way, and so on. In such a context, a company naturally focuses more and more on exploitation as the reward for exploration is low. This is exactly what I see in many of the organizations I work with: for all the talk about innovation and business development, the result is almost always sustaining innovations that make the existing product or solution portfolio a bit better.

With digitalization and its constituent technologies – software, data and AI – taking a stronger and stronger hold of industry after industry, the stable business ecosystem is being disrupted in novel and unpredictable ways. Many companies find out the hard way that their customers never cared about their product. Instead, the customer has a need and your product happened to be the best way to meet that need. When a new entrant provides a new solution that meets the need better, your product is replaced with this new solution.

'Companies need to significantly increase the amount of exploration'

The only way to address this challenge is to significantly increase the amount of exploration your company conducts – we’re talking real exploration, where the outcome of efforts is unknown and where everyone understands that the majority of initiatives will fail. To achieve this, though, you need a game plan. This game plan needs to contain, at least, four elements: strategic resource allocation, reduced effort in commodity functionality, exploration of the novel business ecosystems and/or new positions in the existing business ecosystem and exploration of disruptive innovation efforts that are enabled through data and AI.

Many companies allocate the vast majority of their resources to their largest businesses. This makes intuitive sense, but fails to put a longitudinal perspective on the challenge of resource allocation. A model that can be very helpful in this context is the three horizons model. This model structures the businesses the company is in into three buckets. Horizon one are the large, established businesses that, today, pay the bills. Horizon two are the new, rapidly growing businesses that, however, are much smaller than the horizon one businesses. These are intended to be our future horizon one businesses. Horizon three are all the new, unproven innovation initiatives and businesses where it’s uncertain that things will work out but that are the breeding ground for future horizon two businesses. Resource allocation should restrict horizon one resources to maximally 70 percent of the total. Horizon two should get up to 20 percent and at least 10 percent of the total company resources should be allocated to horizon three.

Within horizon one, each business should grow its resource usage slower than revenue growth. That might mean that a horizon one business growing at 5 percent per year should cut its resource usage with 5 percent per year as this business is supposed to act as a cash cow for funding the development of future horizon one businesses.

In most companies, revenue and resource allocation are closely aligned with each other, but this is a mistake from a longitudinal perspective. A new business will require years of investment before it can achieve horizon one status and this new business can’t fund itself. Of course, you can have it bootstrap itself, but the result will typically be that competitors with a more strategic resource allocation will become the market leaders in these new businesses.

'Once you’ve defined the commodity, **stop** virtually all investment in it'

Second, reduce investment in commodity functionality. Our research shows that companies spend 80-90 percent of their resources on functionality and capabilities that customers consider to be commodity. I’ve discussed this in earlier blog posts and columns, but I keep getting surprised at the lack of willingness of companies to look into novel ways of reducing investment in places where it doesn’t pay off. Don’t be stupid and, instead, do a strategic review of your entire product portfolio and the functionality in your products and, together with customers and others, define what’s commodity and what’s differentiating. Once you’ve defined the commodity, **stop** virtually all investment in it. You need those resources for sustaining innovations that drive differentiation for your products.

Third, many companies consider their existing business ecosystem as the one and only way to serve customers. In practice, however, ecosystems get disrupted and it’s far better to be the disruptor than the disruptee. This requires a constant exploration of opportunities to reposition yourself in your existing ecosystem, as well as an exploration of novel ecosystems where your capabilities might also be relevant.

Finally, digital technologies – especially data and AI – offer new ways of meeting customer needs that you must explore in order to avoid being disrupted by, especially, new entrants. Accept that the value in almost every industry is shifting from atoms to bits, that data can be used to subsidize product sales in multi-sided markets, that AI allows for automation of tasks that were impossible to automate even some years ago and, in general, proactively explore the value that digital technologies can provide for you and your customers. This is where the majority of the resources that you freed up through horizon planning and reducing investment in commodity functionality should go.

Concluding, at the beginning of 2020, you need a game plan to significantly increase exploration at the expense of exploitation in order to identify new opportunities and detect disruption risks and to invest sufficiently in areas that provide an opportunity for growth. This requires strategic resource allocation, identifying and removing commodity, a careful review of your position in existing and new business ecosystems and major exploration initiatives in the data and AI space. It’s risky, it’s scary, most initiatives won’t pan out and customers, your shareholders and your own people will scream bloody murder. And yet, the biggest risk is to do nothing at all as that will surely lead to your company’s demise. Will you allow that to happen on your watch?

Have a look at the training of Jan Bosch 'Speed, Data and Ecosystems'.