This “ah ha”, that IoT will dwarf big data, is slowly forming in my mind.
You might think that I am comparing apples to trees, but I am comparing them as innovations. Right now we are running full steam ahead with our 2015 Hype Cycle’s so I thought it apropos I explore the idea.
Two weeks ago I was sitting at a keynote at a vendor conference. The speaker, from one of the larger Systems Integrator’s (SI) said something I thought was interesting.
He said (and I paraphrase), “If every big data initiative worked as currently planned, each of us would receive 2,356 promotions.”
I thought his point was really insightful. His point was that so much of big data’s opportunity seems to be focused on discovering insights about customers (mostly consumers, at that) with a view to increasing some sales or revenue oriented angle.
So if all the big data efforts dig up some additional consumer insights, we would get a whole lot more promotions (even if we don’t have a whole lot more money to spend).
This was an anecdote to me however. The main reason I feel that IOT is going to dwarf big data goes back to an idea I had over a year ago. Earlier in 2014 I was doing the same work I am doing now but in relation to the 2014 hype cycle’s.
I was working in various teams trying to agree where and how far developed market hype was for a number of technologies and topics. At the same time I was refreshing my understanding for how innovation permeates an industry.
I re-read, again, all my notes from Utterbeck (Mastering the Dynamics of Innovation, 1996). And as I did this an idea came into my head: not all innovations are equal.
I don’t suppose this is too thought provoking, at least how I wrote it. What I thought however was that how we, Gartner, were reporting innovations wasn’t describing what really was happening in the market place.
I formulated my idea and shared with some analyst big-wigs. They showed mild to low interest in the idea so I figured they were not interested in developing it. However it is back in my head again.
The basic idea is this: some innovations are discrete, even silod, in that they stand on their own.
They “come and go” according to the Gartner Hype Cycle; they may follow the pattern normally; they may re-form midway through, and reappear as a new ‘thing’. This is how the majority of innovations evolve.
But there are other types of innovation that appear to behave in much the same way, but for one major difference: They act as a platform. Such an innovation may move along the hype cycle, perhaps more slowly than other technologies or ideas (memes).
But as platforms, they spin off all manner of other, dependent innovations that could only have emerged from thee preceding platform innovation at a point of maturity.
This has led to an idea that every innovation has an “innovation platform coefficient”, or IPC. Some technologies have a low IPC, and some have a high IPC. Those with low IPC’s operate as discrete, one-off ideas.
Those with a high IPC suggest possibly different behaviour with a high propensity to create new, dependent innovations as spin-off’s, over many years.