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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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