The Gartner Hype Cycle and Classification

colin_moden-ns

I love the Gartner Hype Cycle, it’s one of my favorite things about working in the software industry. For anyone who hasn’t seen a Gartner Hype Cycle it looks like this:

Gartner Hype Cycle diagram

Now I’ve never seen any statistical proof that new technologies progress from a “Innovation Trigger” through the “Peak of Inflated Expectations” and the “Trough of Disillusionment” before climbing the “Slope of Enlightenment’ and arriving at the “Plateau of Productivity”. But if you’ve been around a while, and seen technologies come and go, it seems true. Stephen Colbert might claim it has “truthiness”. It’s a lot like that old joke about the 7 stages of a software project:

  • Wild Enthusiasm
  • Disillusionment
  • Confusion
  • Panic
  • Search for the Guilty
  • Punishment of the Innocent
  • Praise & Honors for the Non-Participants

(source unknown)

And yet, over the last number of years, we’ve come to see the Gartner Hype Cycle charts as a realistic evaluation of the maturity of a technology and what to expect from it. It was a happy day at TITUS when Data Classification was recently added to the Gartner Hype Cycle for Enterprise Information Management:

hype-cycle-02

But what can we really conclude from this?

Well firstly that Data Classification is a real thing. There are multiple vendors providing it, of course they all have their unique spin, but at the core there is something that they all do, and it provides enough value for Gartner to recognize it and spend time thinking about it. So that’s good. If you are buying a technology and it’s not on any Gartner Hype Cycle then it must be very niche, or at the bleeding edge of innovation (or I guess obsolete & no longer mentioned).

Gartner gave Data Classification a blue dot, 5-10 years to plateau. That’s the rating that most technologies get, and it’s certainly more comforting for TITUS and our customers than getting the red cross (Obsolete before plateau) or the yellow triangle (more than 10 years to reach the plateau). Should we be concerned that we didn’t get a light blue or white dot (less than 5 years to the plateau)? Maybe not. Another way to look at the Plateau of Productivity is commodity software — how to do it is well established, and there’s not much to pick between the different vendors. Web Authoring software comes to mind, 10 years ago it was an exciting area, now WordPress is free. For vendors, 5 to 10 years to the plateau means that there are still innovative ideas to discover and money to be made. For customers it means that it matters who you buy – there is competitive advantage for you in the differentiation between one vendor and another.

Data Classification is near the “Innovation Trigger”, not near the “Peak of Inflated Expectations”. Realistically not all technologies climb as high up that peak as others. Hadoop is one technology that seemed to reach the dizzying heights of “this will solve everything” and is now crashing back down.

I think it’s a good thing that Data Classification is on a Hype Cycle chart. It’s good for TITUS because it validates that we are building something real and worthwhile, and it’s good for our customers because it means that Gartner, and other analysts, are paying attention to this segment and will be able to provide informed observations and advice going forward. And of course because it means we get to use great phrases like “Peak of Inflated Expectations”, and “Trough of Disillusionment”.

Now, how do I move that software project onto the next phase?

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