When you think about the flow of useful knowledge through society, and then imagine how that flow enables innovation, you’ll realize a massive entanglement. At first glance, there is a myriad of different connections between people, processes, and locations: these are the tangible pieces of the puzzle. At second glance, you’ll find that they all play some role in the generation, dissemination, and application of useful knowledge: these are the invisible, the hidden, the intangible pieces. This entanglement of tangible and intangible elements forms the innovation supply chain, and it seems to be a conundrum, a genuine Gordian Knot. Let’ see how we can untie it.
Looking at its most basic function, any supply chain somehow connects an input to an output. Nothing more, nothing less. But very abstract. What does that mean in more concrete terms, and specifically for the innovation supply chain? In line with my working definition of innovation, the innovation supply chain delivers implemented novel problem-solutions; that’s the output. And once we have a clearer view of that output, we can deduct the required inputs to make the supply chain work. With that, our next task would be to describe the flow of useful knowledge that enables the implementation of novel problem-solutions.
This flow of useful knowledge comprises generation, dissemination, and application, i.e., the intangible pieces of the puzzle. In an attempt to give some structure to their interactions, we can begin with the application of useful knowledge, and then find out what the application can tell us about dissemination and generation: To what extent does useful knowledge already exist, so that it ‘only’ needs to be made accessible at the right location and to the right people? And to what extent must novel useful knowledge be created to enable innovation?
To frame this discussion on the application of useful knowledge, I’ll use the innovation landscape I’ve presented earlier. You could consider this landscape as the locus where useful knowledge is applied.
This landscape stretches between two axes: one represents the problems that need to be solved, the other represents the ideas for potential solutions. Depending on the nature of those problems and solutions (whether they are known or novel), you can easily see that the landscape falls into four quadrants, each with its own characteristics. While all of them apply useful knowledge to develop and implement novel problem-solutions, each of them has distinctly different requirements for the dissemination and generation of useful knowledge. Let’s briefly walk through them.
The first quadrant presents the simplest case. Business as usual is the domain of companies and corporations optimizing their internal processes to deliver their established products and services. You might call this routine-driven innovation; it is what Clayton Christensen calls efficiency innovation: delivering the same functionality more efficiently at lower production cost; it’s innovation within the existing business model.
Working in this quadrant, the innovator fundamentally depends upon the influx of useful knowledge about well-known problems and about established solutions. Novelty in this quadrant is limited to finding new combinations of previously known problems with previously known solutions. Hence the requirement for dissemination is high along both axes of the landscape, while there is no requirement for generation of useful knowledge – the problems and the solutions are sufficiently well understood and established.
These requirements change when we move to the second quadrant. Research strives to develop novel ideas for solving known problems. In Christensen’s terminology, this is the domain of sustaining innovation: replacing existing products and services with new offerings that deliver advanced functionality to meet customer needs. This type of innovation improves the existing business model. To succeed in these conditions, the innovator needs access to use knowledge about well-known problems; that’s similar to the first quadrant.
What’s different in the research quadrant is that dissemination alone is not enough. Innovation in this quadrant also depends upon the generation of useful knowledge; specifically, in this quadrant the innovator must develop new ideas for potential solutions. That means the innovator acts as the generator of novel useful knowledge. In summary, the requirements on the flow of useful knowledge are high on dissemination (regarding known problems) and high on generation (of novel ideas for potential solutions) in the research quadrant.
The conditions in the disruptive quadrant are characterised by known solutions and novel problems. According to Christensen, this type of innovation disrupts the business models of market incumbents from the outside. Today, this is essentially the domain of young and agile start-ups that identify yet un-targeted customer needs and tweak existing solutions to address those novel problems.
To succeed in this quadrant, the innovator must develop an understanding for novel problems, i.e., for challenges and needs that didn’t exist before or that haven’t yet been expressed. The requirements on the flow of useful knowledge are the flip side of those in the second quadrant: the dissemination of useful knowledge should be focused on known solutions, whereas the innovator will pay particular attention to generating useful knowledge on those novel problems he’s trying to solve.
Finally, the wicked quadrant is a real challenge. Framed by unknown problems and novel ideas for solutions, there’s little solid ground to start from. Characterised by uncertainty along both axes of the innovation landscape, success in this quadrant is far from guaranteed.
Hence the requirements on the flow of useful knowledge are the opposite of those for the first quadrant. Under the wicked conditions, there is no requirement on the dissemination of useful knowledge, but a strong need for the generation of useful knowledge along both axes, problems as well as ideas for their solutions.
The chart above summarises which areas of the innovation landscape are dominated by the need for dissemination, and which ones by the need for generation of useful knowledge. It goes without saying that this is illustration simplifies the messy reality of innovation. Yet the structure it offers is helpful to understand why our society is doing pretty well in some areas of the innovation landscape, while it is struggling in others. And that’s the ingoing question for the next post: Could it be that our innovation supply chain is too focused on solving known problem?