The New Killer Apps
Here’s a startling quote from Chunka Mui and Paul B. Carroll in their new book The New Killer Apps:
That $36 trillion is the total market valuation of public companies in the ten industries that will be most vulnerable to change over the next few years: financials, consumer staples, information technology, energy, consumer goods, health care, industrials, materials, telecom, and utilities. Incumbent companies will either do the reimagining and lay claim to the markets of the future or they’ll be reimagined out of existence.
Who is covered in that list of 10 industries? Well, everyone.
The six drivers of change that they lay out are:
The technologies are: mobile devices, social networks, cameras, sensors, cloud computing and emergent knowledge. Together, these are the technologies that convert products into platforms.
So here’s a question: what impact will this set of technologies have on your industry?
In my main one, higher education, I suspect that things like MOOCs are actually behind the curve – few of them take advantage of these technologies. What is the next generation of higher education as a platform? I don’t know, but the question is well worth considering.
It’s worth considering for your industry too.
How can you respond to this disruption?
Mui and Carroll make another interesting claim – that big companies are better placed to take advantage of these changes than small ones are:
This book aims to reverse a bit of conventional wisdom that’s taken root in recent decades: that start-ups are destined to out-innovate big, established businesses. The conventional wisdom just isn’t true. Or, at least, it need not be. Yes, small and agile beats big and slow, but big and agile beats anyone—and that combination is now possible.
The second reason that we focus our innovation work on incumbents is that they should win. Yes, we all know that big companies are sometimes complacent about threats, especially if those threats start small. But big companies have everything they need to continue to dominate: unmatched people, resources, supply and distribution capabilities, brand power, and customer relationships. And in the context of today’s immense technological opportunities, incumbents have growth platforms that would take start-ups years to build.
The question then, is how do we become big and agile?
Their answer is to do three things:
- Think big. If you are in one of the industries facing disruption, it’s not enough to think about making changes at the margin. Instead, you have to be thinking about reimagining – you need to look for that 10X performance improvement.
- Start small. Instead of making big bets, they recommend starting small, then iterating. This means prototyping, and it means experimenting.
- Learn fast. Mui and Carroll say: “little tests can be cycled through faster than full-scale implementations, and cycle time is crucial when it comes to innovating. If you give us two moves in a chess match for every one you take, we’ll beat you every time, no matter who you are.”
They lay out a compelling case for taking a scientific-method style approach to innovation.
And they’re right in saying that given their resources, big firms should win. But then they spend plenty of time outlining ways in which big firms have failed to leverage the tools available to them.
The danger of ignoring disruption
Mui and Carroll use Google’s driverless car as a case study throughout the book. For me, the most interesting part of this is where they start to look at the impact of driverless cars on other industries. Check out this discussion of the impact that they will have on insurance:
However, based on numerous conversations, it’s clear that insurance-industry executives mostly just roll their eyes if asked to contemplate the implications of driverless cars. Even if driverless cars are possible, conventional wisdom goes, it will be decades before they are relevant. Therefore, there is little need to worry now. Here’s how insurers figure the math: Begin with the assumption that it will be years before the technology matures. Add several more years to sort out the regulatory complexities, including licensing and liability issues. Add some more years to gain consumer confidence. Then, given the long lifespan of cars, add another decade or more before driverless cars make up a significant percentage of the cars on the road. On top of that, the argument goes, even if the frequency of accidents goes down, the severity will go up—as measured in the cost to fix cars with all the cameras, sensors, radars, and so on, that are going into them. And, remember, even if you don’t crash into someone else, someone else might well crash into you. So, it will be decades before anyone could even imagine giving up car insurance. Besides, there might be no short-term cost to being wrong. Fewer accidents would just mean fewer claims, and therefore greater profits, until enough actuarial data proved that driverless technology delivered the conjectured savings and forced premiums down. Thus, the prevailing attitude is probably much like that of Glenn Renwick, CEO of Progressive Insurance, as expressed during Progressive’s February 2013 earnings call: “The technology to do an autonomous car has been around for a while. We’re now seeing them; we’ll see a lot of talk about them. The real issue is exactly how they are able to be part of the fleet of vehicles on the road in America, and that is probably not something that need keep anyone awake for quite some time.”
You can see that they are still at the first stage of dealing with disruption: ridicule.
This is another example of incumbents misunderstanding the S-Curve of technology diffusion. The mismatch between hype and early results makes it very easy to dismiss new technologies. The S-Curve lies underneath Bill Gates’ famous quote about disruption:
We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.
When you dismiss disruptive technology early, you are not thinking big. Mui and Carroll give a compelling explanation for how things are changing across many industries these days. The book is well worth reading.
But acting is more important than reading! My prescription is to take the smart small and learn fast ideas to heart. These are the core skills that you need to build a culture of experimentation, and experimenting is the best way to cope with an uncertain future.
If change is inevitable, it’s always better to be the driver of change, rather than waiting for it to come, and then reacting. If you’re big, you have the resources available to do this. But you also have an existing core business that can keep you from acting. If you’re faced with this conflict, the best step is to start experimenting.