Learning and innovation go hand in hand. The arrogance of success is to think that what you did yesterday will be sufficient for tomorrow – William Pollard.
Ensuring that innovations are taken up by the marketplace is a challenging problem. The spread of technological innovations is influenced by a range of factors, from supply and demand factors, to learning-based effects, through to technology substitution and management techniques. The range of factors that affect this spread is very large. One of the factors that receives relatively little attention however, is the social nature of technological innovations and the environments that supports their adoption.
As a starting point for exploring this issue, consider for a moment what ‘technology’ is. Technology is often represented by objects, for example, a smart phone, a car or some software. However, technological innovations are much broader in scope than this. In addition to ‘hardware’ and ‘software’ (in a general sense), it can include the knowledge required to design, build and utilise the technology, along with socially-defined rules that determine how it is used in practice.
In thinking about this approach, consider the case of smart phones. At the level of the object, smart phones are a collection of metals, plastic and glass combined with software. However, what distinguishes technology from other objects we create is that technology serves a purpose and that purpose is defined by people, rather than the object itself. That is, technology can be defined by how we use it, or what purpose we put it to. After all, that’s why we create technologies in the first place – to do something we couldn’t do before. So smart phone technology includes the things we do with it, from tracking our fitness to playing music and talking to friends and acquaintances. Without those purposes, the hardware would be meaningless.
A by-product of using such a definition is that technology can be seen to change over time, even if the hardware remains static. This doesn’t occur much in practice though, as people tend to refine technological innovations to better suit their evolving needs. Returning to the smart phone example, the programmable nature of this technology allows it to evolve quite quickly. And this has enabled the rapid evolution of the technology based on how it gets used by people, in many cases in ways that couldn’t even have been imagined when smart phones started their relentless rise in 2007.
Following from this, an important observation is that the creation of a technological innovation involves the creation of something that is new in both a technical and a social sense. New technologies require new habits, routines, expectations and practices to be developed as well the hardware and software. The technical elements of the innovation can often be created ‘in the lab’, but the other parts of the technology need to be developed by users actually using it. The problem for innovators therefore, is to work out what these habits, routines, expectations and practices are likely to be before they spend too much time and money on development of the technical innovation.
In this context, approaches to innovation such as lean start-up and design thinking provide much stronger platforms for creating technological innovations than more traditional technology-push or technology-pull approaches. Lean start-up does this by minimising development work (to create the ‘minimum viable product’) before testing with users, followed by further, rapid evolution of the idea. Design thinking takes this a step further by matching what is technologically possible with user needs at the very outset. In both cases, the innovation stands a much better chance of being accepted once it’s released into the wild.
However, this approach won’t always be successful. Users don’t always know what they need. This is a central idea in the concept of disruptive innovation: it isn’t always possible to predict what the market for an innovation might be and extensive exploration might be required to find a market that works. In this event, innovations that go on to redefine an industry – or even create new ones – are going to be much more difficult to create using lean or design thinking principles.
What’s required, then, is a way to recognise that all the parts of a technological innovation evolve following the initial creation. It requires the basic cycle suggested by design thinking to be repeated at a more global level once a first cut innovation is released into the market. By inserting a deliberate repeating loop into the process (as a type of ‘double loop’ or ‘multi-loop’ learning) it allows for the continued evolution of the artifact and the habits, routines, expectations and practices that accompany that technical innovation; that is, the technology in its entirety. A modified version of the design thinking process might provide a method to achieve this.
Such an approach would allow the initial social and technical configuration of the innovation to converge with the social context of the marketplace; a process that could be called ‘convergent innovation’. This recognises that the evolution of a technology combines things that the innovator can address (in how the technology functions) as well as things they can’t (how people actually use the technology). It creates a challenge insofar as innovation becomes a continual process involving relatively uncontrollable use of technology in practice. But in return, it offers the opportunity to raise the chances that a technology will be adopted – and adopted widely – in the marketplace.
And when companies are looking to extract maximum value from a limited set of valuable ideas who wouldn’t want that…?