You have to admit that watching Donald Trump run for president is funny in an incredibly painful way. During the primaries he seemed to be Teflon. I think we can now attribute his win to the fact that no one really took him seriously until it was too late, or as a result of using a strategy that worked for Pat Buchanan and Howard Stern.
Now in the general election it seems he has turned to glue and nearly everything he has done since has caused his poll numbers to go down. I think this is largely because he simply doesn’t believe in hard facts. He admittedly lives on Twitter and appears to not only take what he agrees with as fact, but to pretty much ignore all forms of independent data speaking out against both focus groups and analytics.
I think we can learn from his train wreck because while Trump may seem extreme, his blinders are so common we have a name for them: Confirmation bias.
Confirmation bias is when someone forms an opinion and then will accept only information that agrees with it discounting or ignoring everything else. The biggest example to date was likely the WMD belief that started the Iraq War. There were none.
[ Related: A SWOT analysis of Trump vs. Clinton ]
How IBM almost went under
Decades ago while in IBM I was, along with a considerable number of others, very frustrated because it seemed obvious that IBM was on a managed path to failure yet the top executives seemed completely ignorant of the problem. I cornered IBM’s head of marketing and he spoke to me as if I was a small child explaining that IBM sold the equivalent of air and that customers had no choice but to buy what was sold. Thinking back, it strikes me that if this were the case what did we actually need a CMO for? Who needs to advertise air?
John Akers, who not only was a well-regarded and incredibly smart CEO, was then blindsided by the firm’s slide and remains the only IBM CEO ever fired. I later interviewed one of his aids to discover that over the years the office of the CEO had become effectively surrounded by information translators who told the CEO what he wanted to hear and effectively covered up any problems. Granted there were organizations like internal audit that reported through this barrier, but I know that those that found problems aggressively were discounted in favor of teams that reported favorable results.
[ Related: Clinton wins, how analytics cost Trump the election ]
Even in competitive analysis, where I also served, there were teams that reported accurately the problems with products and teams that reported that IBM’s products were unbeatable. In looking at the performance of our team against the other, we were defunded, and the business the other team supported went from 95 percent market share to 35 percent market. Now, to be clear, both businesses failed. Our information was disregarded resulting in failure and the other team’s information was false resulting in failure.
I recall being told that the executives were going to do what they wanted to regardless and failure wasn’t my responsibility, therefore, the smart analyst reported what the client wanted to hear not what they needed to know. While this still seems insane to me and I disregarded it at the time, in hindsight it was actually very good career advice, but an incredibly horrible way to run companies.
The second time I ran head-on into that buzz saw, apparently I’m a slow learner, was when I left IBM and became an analyst. I took over an operating system service that was on life support. Because I’d helped run a team that had tried to spin out the IBM software division I had massive amounts of market information which indicated that virtually every OS but one was vulnerable. The report not only made me famous, it had CEOs lining up to fire me. It was kind of a race to see if I, or Dataquest’s CEO, would be fired first. To suggest she was not happy would be an understatement.
I remember one call in particular with IBM regarding OS/2 where I suggested that the AR manager give the IBM management team a heads up that I was going to issue the report. Her response was that I was a nobody and no one would care what my report had to say. The next day it was front page news worldwide and repeating what she said later that day would trigger any number of profanity filters.
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