We have a new report out on DU Press: Your next future: Capitalising on disruptive change. Disruption is something we’d been puzzling for some time as it’s a fuzzy and poorly defined concept despite all the noise it generates. It’s also concerning that few, if any, of the theories have much predictive power.
Our contribution is fairly straight forward.
First we make that point that disruption, as the term is commonly used, covers a broad range of phenomena. This creates tension between our desire for a comprehensive definition, one encompassing this broad scope, and the need for a precise definition, so that we are all clear on what we’re talking about. Many academic theories (such as Clayton Christensen’s) come unstuck when it’s pointed out that the theory might refer to some disruptive phenomenon, but they don’t account for many other phenomena that can also be considered disruptive.
Consequently we must acknowledge that disruption operates are at least three different levels of abstraction:
- At the highest level are long-term whole-of-economy shifts that disrupt all of us. The shift from stocks to flows – which we try and measure in the Shift Index – is one of these.
- At the mid-level are disruptions focused on a sector or industry. Our colleagues in the US have be cataloging these in the Patterns of Disruptionseries.
- At the lowest level are the things that disrupt us, our firm.
It was the observation that value used to be objective and defined relative to the market, in terms of product feature-function, but now value is more commonly defined subjectively, relative to the firm and the firm-customer relationship, that prompted us to look at disruption with a wider lens and make this subjective disruption the subject of a our essay.
Next we wanted to create a model of disruption that was predictive, which could be fed into a strategy-formation process to enable a firm to identify concrete actions that would enable a firm to prepare for a (potential) disruption and either capitalise on it or defuse it (i.e. neuter the disruption). The resulting model relies on three observations.
- Disruption is degenerate. A single outcome, a disruption, might be triggered by a large number of different processes. This means that will be impossible to understand disruption by identifying and analysing individual contributors without considering the complex relationships between them.
- Disruption is constructive. While technology is important to a disruption, technology alone is not enough and we need to also consider social and commercial forces as well that come together to trigger a disruption.
- Disruption is subjective. A new technology might disrupt our sector or industry, but it may not disrupt us. The reverse is also true. Our concern is disruption to our business, not markets (via patterns of disruption), the economy (via the Big Shift) or disruption in general.
The result a model that shows us why we we cannot predict disruption by identifying ‘disruptive’ technologies’, but which does enable us to do something about shaping how we approach disruption.
We’re pretty happy with the result, which you can find at DU Press.