#0086: Technology as a driver of innovation
Braingasm
[ED: UPDATE20181005 This is an early draft of a chapter that I’ve been asked to write for an upcoming book on innovation. Regular readers will notice that it’s a mashup and refinement of a few concepts that I’ve been talking about for some time. Please let me know if there’s any howlers in here!]
[ED: UPDATE20181204: This is now the final edit of the piece that will go in the book (with US ‘z’s changed to UK ‘s’s for this post). Thanks to everyone who helped with edits!]
The idea that technology drives innovation seems so obvious that it’s almost unremarkable. So why do large enterprises still struggle to realise the value in technical innovation, lumbering along painfully while repeatedly making the same mistakes? There are two important reasons why.
First, successful corporations are very good at maintaining their status quo. To do that, they must become experts in establishing markets, products, processes, and cash flows — all of which obstruct innovation. When innovations emerge, the corporate body experiences a kind of allergic reaction, mustering innovation antibodies to minimise the effects of change.
Second, corporations typically seem to have trouble understanding the fairly reliable pattern that characterises the emergence of innovations. Blinded by corporate antibodies, misaligned incentives, unrealistic expectations, wilful ignorance, and a cultural fear of failure, they miss opportunity after opportunity. Successful entrepreneurs, on the other hand, do seem to understand how to realise the value in the pattern.
The pattern begins with the advent of new technologies. The technologies (or more often, confluences of various enabling technologies) allow entrepreneurs to try out new business models and customer experiences, and create new products and services that depend on the innovative technologies. This first phase of the pattern frequently draws much attention, sometimes to the point of becoming unrealistic hype, but latent opportunities in the raw technology are just the start.
These opportunities eventually emerge in the form of startups and other new businesses that treat the new technologies as a kind of playground. Once businesses begin to exploit the technologies, then opportunities for new types of supporting infrastructure emerge; these support the new technologies and their users’ interactions at scale. Only after this infrastructure begins to operate at scale do new types of marketplace and/or operating models emerge to facilitate interactions between producers and consumers of the new technologies. Finally, after the tech, infrastructure, marketplaces, and operating models bed down, opportunities for new types of aggregation arrive.
For example, consider how we ended up with Uber and the gig economy generally:
- New technology in the form of 3G, 4G, GPS, touch screens, CPU power optimisation, and a revolution in user experience combines to enable smartphones.
- New infrastructure springs up in the form of telcos providing ubiquitous wireless broadband. Smartphone users sign up in the billions.
- New marketplaces and operating models in the form of smartphone app stores provide mass distribution to end users.
- New aggregations in the form of Uber capture end-users seeking urban mobility services (demand) and a willing set of private drivers using their own vehicles (supply), all enabled by social-mobile-local and the gig economy.
This pattern of innovations washing through the economy, from developing new technology, to supporting infrastructure, to marketplaces and operating models, and finally to sophisticated aggregations, happens repeatedly. As a technology matures, it triggers potentially large value destruction and creation opportunities, redirecting existing profit pools to those best able to exploit the technologies, infrastructures, etc.
Before a technology matures, it doesn’t make sense to look for opportunities in marketplaces and aggregations. Instead, entrepreneurs should be looking for opportunities to develop the raw technology. Then, as use cases for the new technology emerge at scale, entrepreneurs should look for infrastructure plays. When the infrastructure is in place for larger scale, entrepreneurs can look for marketplace, operating models, and new aggregation opportunities. The lesson for innovators is to make sure that they are aware of where a particular technology is in this pattern and make investments accordingly.
The likelihood of success ultimately comes down to timing. This is particularly true for our corporate innovation partners. Inventing some new technology may well be outside the core business of most corporations, but building new products and services on top of new or emerging tech can make a lot of sense, especially if the corporation can bring its characteristic assets to bear on the scaling, customer acquisition, or access to capital.
Take data. Most publicly available consumer data, such as Facebook’s social graph and Twitter’s and Instagram’s interest graph, are already behind significant moats in the form of giant user bases and massive market demand. The vast majority of enterprise data, however, remains locked up behind corporate firewalls, sensibly hidden away from the global data monopolies, and thanks to the antibodies against enterprise innovation, often out of reach of corporate initiatives as well.
For example, I could build another social network, photo-sharing app, or fitness tracker, but it’s safe to assume that I would have serious trouble getting people to use any of them instead of Facebook, Instagram, or FitBit. Similarly, if I wanted to build a service that predicted motor vehicle traffic, I could probably hack together a tech stack that could recognise and classify vehicles, but only with an appropriate volume of training data. Getting accurately tagged data for this would be vastly difficult and expensive for a startup working out of an attic, but access to that kind of data isn’t difficult if you are a large infrastructure provider with cameras and live video feeds across all of your motorways.
And this is precisely DV’s sweet spot: in the application of emerging yet production-ready technologies with one or more unique corporate assets, powered by the hack-and-hustle mentality that comes from building software like a startup. That is where the opportunities to build something truly disruptive arise.
Timing plays a big part in startup success, so understanding how tech transitions through that innovation pattern is a key insight for savvy entrepreneurs; they know when to tackle which type of opportunity, and when and where to deploy their strengths to drive the most significant innovation impact.
Regards,
M@
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References
[1]: “You Need an Innovation Strategy” — HBR.com
[2]: “Innovation Case Studies: How Companies Use Technology To Solidify A Competitive Advantage” — Forbes.com
[3]: “Enabling Technology-Enabled Innovation” — BCG.com
[4]: “Anti-antibodies” — Matthew Sinclair, Medium.com
[5]: “Is the Second Artificial Intelligence Winter Just Around the Corner?” — NetApp.com
[6]: “Crypto’s most devout believers are suffering a crisis of faith” — FinancialTimes.com
[7]: “The single biggest reason why startups succeed” — Bill Gross, TED
