Path: utzoo!attcan!uunet!samsung!zaphod.mps.ohio-state.edu!tut.cis.ohio-state.edu!usenet.ins.cwru.edu!mephisto!udel!rochester!kodak!doering From: doering@kodak.UUCP (Paul F. Doering) Newsgroups: comp.society.futures Subject: Re: Retrospective Forecasting Message-ID: <2378@kodak.UUCP> Date: 28 Feb 90 14:28:53 GMT References: <5473@bgsu-stu.UUCP> Reply-To: doering@kodak.com (Paul F. Doering) Distribution: na Organization: Kodak Research, Rochester NY Lines: 28 In <5473@bgsu-stu.UUCP> Bruce Klopfenstein writes that he finds little evidence that technology forecasters critique past efforts to refine the forecasting process. I earn my living as a forecaster of technological developments, and I would cite two explanations: I believe that most successful forecasters are unknown to the public or even to their peers. They live inside organizations that rely on their services. Possibly they can be detected only by their employer's knack for good decisions. "Famous" forecasters rise on their own successes and fall precipitously on their first obvious misstep. That's a consequence of being "employed" by the public. Private employers are more likely to accept a satisfactory batting average instead of perfection. What all this means is that the kind of post-mortum Bruce is seeking probably goes on quietly in scores of places, with the results hoarded for competitive advantage. Additionally, I find that I spend much of my time qualifying the data, not the technique. Any good algorithm fed bad information will give unreliable results. Clearly, I don't mean to belittle the need for good algorithms; but it's disappointing how many sources are in business merely to publish bad data. ... All of which makes my signature block a little ironic -- -- ========================= =============================== Paul Doering (for self) We shall walk together doering@kodak.com as seekers toward the Future. ========================= ============= -Carl Sandburg ==