The 3 Dimensions of Disruption
Emerging Technologies, Business Model Enablers, and Exponential Adoption Curves
As excitement (and panic) about the opportunities and threats of emerging technologies spreads into boardrooms across the world, it is worth considering that it is not just the technologies themselves which are disruptive. Indeed the bursting of the tech bubble in 2000 taught us that the technologies themselves are vulnerable to issues of scaling and adoption.
Furthermore, of the key emerging technologies we have identified: 3D Printing, Advanced Robotics, Artificial Intelligence, Internet of Things and Virtual Reality, some of them have been around in some shape or form for some time. What is different now to 2000, and means the impact of technology is truly disruptive on a large and wide scale, is that we now have the business model enablers to drive the technology through a business.
These business model enablers mean we now have access to the funding, platforms, processing power, software, and data to turn the technology into useful, scalable solutions.
These enablers include:
Crowdfunding – The early availability of capital from crowdfunding sites such as Kickstarter and Indigogo offers startups the ability to fund project to the point of Minimum Viable Product
Cloud Computing – Access to flexible cloud services such as Amazon Web Services negating the need for large servers to get a business of the ground
Low Cost Computing – Moore’s Law has seen the cost of computing decrease hugely whilst the processing power has increased
API Economy – Application Programming Interfaces allow disparate computer systems to communicate with each other.
Open Source – Value has shifted from product to data encouraging software vendors to make software open source
Miniaturisation of sensors – Tiny sensors driving innovations in IoT
Freemium – Free business models allowing access to products and services for free – (e.g. Dropbox)
The combination of new technologies together with these new business model enablers is resulting in a significant change in the adoption rates and patterns of new tech enabled companies, products and services. This has become the key factor in the rapid disruption of existing and traditional industries and incumbent market leaders.
Previously, uptake of a new technology was limited by the speed at which target markets were prepared to accept new solutions, and by where target consumers sat behaviourally between “early adopters” and “laggards”
But now, it is no longer about slowly replacing one technology with another within an existing market, but being able to access the data and distribution models to scale a new service to new markets almost overnight.
A great example of this interplay can be seen in the launch of self driving trucks. The economics for autonomous trucks are compelling, but at £250,000 per new truck, the adoption rates are constricted by the economics of requiring purchasers with appropriate levels of free cash flow. Thus the adoption curve will be gentle and shallow.
Then with the arrival of a startup called Otto who have produced a $30,000 retro fit kits for existing trucks, the barrier to entry will be lowered as the technology becomes applicable to existing fleets. This will cause a steep adoption rate due to increased affordability.
And then with Uber (and their massive cash flow) buying Otto for $700m, one can anticipate the adoption curve can become even more steep. . . leading subsequently to a significant disruption in logistics.
It is becoming apparent that the critical driver of disruption is the speed at which consumers or business adopt a new product or service. The ‘perfect storm’ of emerging tech, new business models to distribute it quickly, and subsequent exponential adoption means that organisations must start to get more agile and able to respond and anticipate.