Last month I was invited to the Pentagon to talk about the adoption of new technology. It was part of the government’s effort to (once again) “transform” the way it does business.
My role was to help them think about how to introduce new technology to old problems, processes and decision-makers. I agreed to go because I wanted to draw some distinctions among technology concepts, emerging technologies and technology clusters. I also thought I’d get a chance to influence some heavy hitters. More on that later.
So what is grid computing? Is it a technology concept, a real technology or a whole technology cluster? What about voice recognition technology, semantic understanding and the Segway? Are they concepts, emerging technologies are part of larger technology clusters?
I got to thinking about all this because I recently did a “content analysis” of a number of technology trade publications and turned up no less than 30 “technologies to watch.” Content analysis is a technique that identifies trends by counting the frequency of mention: if something’s mentioned a lot — like Web services — then it ranks high in the analysis. Lots of technologies get mentioned a lot — which is why there are 30 or so “to watch” — but let’s be honest: There’s no way all of them deserve our attention — or our money. What are the technologies that matter?
I segmented technologies into concepts — ideas like “real-time computing,” emerging technologies, like wireless networks, and technology clusters that include real technologies plus infrastructure, applications, data, standards, a developer community and management support.
I then made the argument that technology impact was related to concepts, technologies and clusters, that concepts are wannabes, prototype technologies have potential and mature technology clusters are likely to have huge sustained impact on the way to do business.
I then mapped a bunch of the technologies-to-watch on to an impact chart and discovered that many of the technologies about which we’re so optimistic haven’t yet crossed the technology/technology cluster chasm — indicated by the thick blue line that separates the two in Figure 1. Technologies in the red zone are without impact; those in the yellow zone have potential, while those in the green zone are bona fide. The chasm is what separates the yellow and green zones.
Figure 1: Technologies, Impact & the Chasm
The essence of all this is that technologies will have limited impact until full clusters develop around them consisting of all of the things necessary for technologies to grow, all of the applications, data, support, standards and developers that keep technologies alive and well over long periods of time.
Figure 1 also suggests that it’s too early to tell if many of the technologies-to-watch will become high impact technologies, that is, will cross the chasm. Real-time synchronization, business process modeling, grid computing and utility computing, among others, may or may not yield successful prototypes — which may or may not evolve into full-blown clusters.
So how did I do with the heavy hitters at the Pentagon? A few of them thought I was Geoffrey Moore, the co-author of the now-classic Crossing the Chasm. Some others thought I worked for the technology vendors who had actually crossed the chasm, and a lot of them thought that the whole notion of clusters was too restrictive, that technologies — even if they were bogus — needed nurturing. When I said that I thought such an approach could prove to be very expensive, they reminded me that their job was to invest in high risk/high payoff technologies, not to invest in technologies that were definitely going to work.
On the train back from Washington I finally figured out where all the money goes — and how companies can save some of the money the government spends:
Or put another way, unless you’re in the technology business, don’t be an early adopter, a pioneer or live on the bleeding edge. It’s too expensive (unless you work for the government).
Is this a good way to segment technologies? I think it helps categorize the phases technologies go through and helps us avoid investing too early in technologies that haven’t proven themselves. Stay in the green zone, and if you have to wander don’t leave the yellow zone. The red zone’s a money pit: track the returns here on other people’s money.
Steve Andriole is the Thomas G. Labrecque Professor of Business at Villanova University where he conducts applied research in business/technology convergence. He is also the founder & CTO of TechVestCo, a new economy consortium that focuses on optimizing investments in information technology. He is formerly the Senior Vice President & Chief Technology Officer of Safeguard Scientifics, Inc. and the Chief Technology Officer and Senior Vice President for Technology Strategy at CIGNA Corporation. His career began at the Defense Advanced Research Projects Agency where he was the Director of Cybernetics Technology. He can be reached at firstname.lastname@example.org.