One of the biggest quandaries in innovation is the discrepancy between our hopes and desires on one side and the real outcomes on the other. No matter how well intended, carefully planned, or diligently executed a project, often the result does not match the expectations. What’s the reason for that?
Now, you’ll find impressive volumes of writing on managing innovation projects, but that to me is only addressing the symptom, rather than the underlying challenge. Actually, before I can manage something, I first need to understand what it is. The key question in our case then is: How does innovation unfold in reality, as against how do we expect it to unfold?
The first aspect is time, or more specifically: Estimated Time of Arrival. Innovators have the natural desire to see their idea become reality sooner rather than later. And their customers and investors of course want to have the latest gadget, the better services, the new business model as soon as possible. Everybody wants it fast, so what is holding us back?
The second aspect is the reach and relevance on an innovation, or rather: its impact. Here we tend to focus on our good intentions, without paying attention to potentially negative, unintended consequences (I addressed that positive bias in a previous post).
And then there is the combination of time and impact, where we seem to fail miserably to have a realistic view. This failure was well captured by Roy Amara, then President of the Institute for the Future, when he observed what is now known as Amara’s Law:
We tend to overestimate the effect of a technology in the short run
and underestimate the effect in the long run.
If you are looking for a more graphical expression of this observation, you’ll find that the Gartner Hype Cycles make a good case for the difference between expectations and reality, and their evolution over time.
I realise that both, Amara and Gartner address technology rather than innovation, but I argued earlier that in a very broad sense every innovation can be considered a technology. I made that point based on Brian Arthur’s ideas, and once again his seminal work gets my closer to providing some answers to the questions I raised above.
In essence, Arthur observes a fundamental difference between a single technology (which he also calls the basic meaning of the term “technology”, take the steam engine as example) and a technology domain (the plural meaning of the term, with information technology or biotechnology as examples). He points out that:
An individual technology is to a technology domain
as a computer programme is to a programming language.
Of course both share the defining concept of technology: they are built from existing components, which in turn are technologies in their own right. But more importantly, single technologies and entire domains each develop through different processes along different timelines.
For an individual technology, this is pretty straightforward. A single technology defines a product, a process, or a service. It is created by somebody for a purpose, and it directly provides a functionality to its user. Developing an individual technology is largely standard engineering practice that happens within a stable, given context; that is a matter of months to years.
By contrast, a technology domain provides a family of single technologies that, when adopted, can define an entire industry. A domain is not deliberately created; rather it emerges piece by piece. And a domain gives potential to a whole society, rather than an individual. But here comes the main difference: a technology domain is not simply adopted by a society. Rather, society encounters a new domain, society reacts to a new domain and as a consequence changes its activities, institutions, even industries. Society restructures itself in response to a new domain. That changes the context for the further evolution of the domain as well. And the domain responds to society, seeking purposes for the application of its components and principles, seeking use and exploitation, so that the potential of the domain is released for the benefit of society. We can sum up to say that society and the new technology domain co-evolve in a process of mutual adaptation. Given this complex process, it comes as no surprise that the maturation of a technology domain can stretch over several decades. Think about the railroad system, electricity, or petrochemistry.
Arthur offers valuable insights here, so let’s pause for a moment and see what we have. This is in fact a solid, neutral account of how technology/innovation unfolds. Arthur thus describes the reality of “what happens under the hood“.
With expectations and reality properly described, we hold the two ends of the spectrum. We can then tackle the next question: What happens in-between? Or simply: Where and why do our expectations deviate from this reality? That’s the topic for part 2. Stay tuned …
understanding innovation 