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Technology Predictor Success Matrix · This is the first in a series of essays on a simple but important question: Which new technologies will make it, and which will fail? The TPSM attempts to approach this question systematically, by figuring out what the key success factors are. The premise is that you use the past to predict the future. This introduction also serves as the Table of Contents. I’ve now posted the samples of “Winner” and “Loser” technologies, the list of candidate predictors, and the matrix rundown on all of the candidates, having saved the best for the last. Next I’ll try to craft some sort of conclusion. I’m getting a lot of email feedback on this series. When I’m done, I’ll go back and dig through it and write up the good stuff; thanks to all and keep it coming ...
 
TPSM-12: 80/20 Point · We all spend time looking for that tasty milestone where we’ve done twenty percent of the work and are enjoying eighty percent of the benefit. Some technologies have this 80/20 feel, some don’t, and around this subject swirl some of our most vituperative debates. The 80/20 Tribe’s offerings are denounced as “Just a toy!”, while they hurl back accusations of pedantry, big-system disease, and so on. Should we be listening with special care to the arguments of one side or another as we try to predict technology futures? ...
 
TPSM-11: Technical Elegance · If you have the misfortune to not be an engineer, you’ve never known the thrill of encountering, for the first time, technology that is beautiiful. If you are, you know what I’m talking about, and if you’re not, nothing I can say will help you (a line invented I believe by Duke Ellington). Other technologies are less aesthetically compelling, and we call them kludges and hacks and pieces of [insert your favorite scatological term]. It’s all very well to drink deep at the well of Existential Engineering Beauty, but does it actually make any real difference to whether a technology succeeds or fails? ...
 
TPSM-10: Happy Programmers · Programmers are the foot soldiers in the technology wars: the closer you get to the big-money decisions in the corner office, the less people actually care about code and coders: get the business priorities right, the thinking goes, and then worry about making the technology happen. I actually have some sympathy with that thinking. But there are a lot of programmers and they make a lot of everyday decisions: do these add up enough to make them important influencers of technology success? ...
 
TPSM-9: Good Implementations · Some technologies bubble to the surface as the purest idea-ware, “Here’s the relational theory; wouldn’t it be great if we could build databases that way?” Others first get noticed when they’re already built into working code, like for example Tim Berners-Lee’s Web prototypes and then Mosaic. Which kind is more likely to succeed? ...
 
TPSM 8: Investor Support · While the Venture Capital community may have come down a few steps from their Bubble-era Masters Of The Universe status, the flow of investment dollars remains a key feature of the technology landscape. Would following that flow be a good strategy for predicting the success or failure of new technologies? ...
 
TPSM 7: Compelling Idea · Some new technologies are exciting; they give geeks and journalists and analysts the feeling that Something Important Is Going On Here, and the urge to tell others. The geeks generate online buzz, the analysts expensive reports, and the journalists, well sometimes something ends up on the front page. Other technologies, while maybe useful, just aren’t buzz-generators. Is the degree of excitement a useful success predictor? ...
 
TPSM 6: Return On Investment · If you’ve been involved with a major enterprise capital procurement recently, you’re probably sick of hearing about ROI. A sales pro who wants to convince a customer to sign on the dotted line for a big chunk of money had better have worked up a convincing financial model showing how the customer is going to reduce expenses or increase revenues by an amount that’s several times what they’re being asked to pay. The same kind of dynamic applies between a line manager launching a project and the corner office; and between senior management and Boards of Directors. These days, people don’t want to hear about synergies and intangibles and brand leverage, they want capital-R, capital-O, capital-I, and they want it fast. So, is ROI potential useful in predicting the success of new technologies? ...
 
TPSM 5: Standardization · Life would be impossible without standards: you couldn’t build houses or cars or electrical appliances; cooking would be a real challenge, and medicine would be driven back to the era of sympathetic magic. Information technology works better when it’s standards-based: today, you can plug pretty well any computer into pretty well any network jack and there’s a good chance it will Just Work; when a computer is attached to a LAN, you can usually mount any of its disks on any other computer in the LAN without much trouble; you can usually click on a music file and sound will start coming out of your computer speakers. And so on. Does this mean that when a new technology comes over the horizon, the degree to which it’s standardized is going to have a major influence on whether it makes the big time? ...
 
TPSM 4: Management Approval · Around 1990, a weird thing happened: IT departments started to experience the momentous soggy “thud” of Enterprise Licenses for Lotus Notes dropping on them from a great height; often procured in a corner office with no involvement by mere technologists. And another weird thing; IT management discovered that signficant jobs were getting done (and well, and quickly) using this weird language called “Perl” that wasn’t taught in any University courses and certainly wasn’t on Gartner’s radar. These can serve as canonical examples of the front-door (with management blessing) and back-door (with management oblivious) approaches to introducing technology. Let’s use our dozen winner and loser technologies to see if the level of management approval would have been much use in predicting their success or failure ...
 
TPSM 3: Candidate Predictors · I’ve already profiled some winning and losing technologies, which I’ll use to build the success matrix for candidate Technology Success Predictors. Herewith an introduction to the nine candidate predictors, plus a challenge to your intuition. Then it’s off to the races ...
 
TPSM 2: Technology Losers · In predicting the future from the past, it would be foolish to look only at past successes. So here is another important basis for the Technology Predictor Success Matrix: a list of technologies that, at one important level or another, are failures. I’m sure that any number of people will protest over one or the other of these, citing their influence on later technologies or people or companies. But consider, for those on the this list, the answers to two questions: Are people using them? Did anyone make serious money based on them? And you’ll generally get two negatives ...
 
TPSM 1: Technology Winners · If we want to predict which technologies are going to change the world, it will probably help if we give some study to technologies that already have. Herewith the first step in building the Technology Predictor Success Matrix ...
 
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