You give me fervor: dSt/dt = a(C, P, ...) [St/Ut] * [1 - St/Ut]

Having made stuff up conducted trend analysis and flipped coins integrated qualitative research for about 30 years, this generation of nets and boxes begins to rock in pretty disruptive ways. In this new place, massive networks of storage, more consumer driven than ever, connected by faster networks and wicked magic small tech.We've only hadaspirin around for 110 years. Modeling complex systems with itty bitty Reverse Polish Notation in the hallowed HP-45's ten or so registers and 49 programming steps.Writing decision support programs in Lotus 1-2-3 with 5 inch floppies.... and that dreamy IBM PC XT with what, 10 or 20 droolworthy Megabytes of storage. Then HyperCard and hmmm.... I think it was Mac with 6.something used to model Automatic Teller Machine user interfaces with real live consumers pointing and clicking.... And these kids today: so many tubes!Adoption curves (usually s shaped, often tied with knowing marketing hosers arguing either for or against the adoption of the Next Big Thing depending upon whether said hoser has (or can assert ownership of) the Next Big Thing) apply, but do the curves start to point ever more upward?More people. More networks. More transparency to the tech. Better abstraction and generalization of interfaces (none dare call it commoditization). Like whoosh? Potentiated equilibrium? Chicxulub?

Andy S. Kydes for the US Department of Energy provides a concise review of how capital budgeting decisions occur in the context of changing technology. (The model best applies, I believe, to infrastructure decisions which tend to be big lumps of capital and concurrent retooling of skills, but is nonetheless useful in exposition of the dynamics of market adoption.)The "dSt/dt = a(C, P, ...) [St/Ut] * [1 - St/Ut]" bits concern, essentially, the rate at which an infection moves through a population. Technology adoption follows this kind of logic. A few try it, they like it, they tell their community and the new drives out (or back) most (sometimes all) of the old.NB: Experienced technology managers will recognize that for early releases the infection model truly speaks truth. Although the DOE's exposition of tech adoption does involve energy components (coal, nukes, etc.) but the principles of how one generally assesses and then opts to adopt a new technology inform the supply side of storage componentry and the demand side of direct storage consumers (thumbdrives) and service providers employing storage as a means to an end (Google, Carbonite, HuLu, yadda yadda).What continues apace: Acceleration Interesting to see the delivery of high capacity spinning media, high density flash media (Gb), and emergent nanotech promising huge efficiencies and availability in something like 18 months (mid-2009) in terabytes.Well, interesting in the sense of wonks, not interesting like "the promise of moonlight in a martini", as Mr. Shanley noted.Curious as to how the Technology Adoption Life Cycle morphs. Do we all become Early Adopters? Seems that time to market becomes the critical success factor.... I mean.... like really really vital on the supply side (sell 'em) and the demand side (buy 'em for the benefits). Hmm.... so let's say I can abstract the command and control systems in some stable overlay that permits rapid change out in underlying components, thereby reducing the friction of changing out the So Last Year blinkenlights for the So Happening new blinkenlights. Doodling time. Time for coffee. Or moonlight.