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Clinton wins, how analytics cost Trump the election

Rob Enderle | July 25, 2016
Columnist Rob Enderle takes a look into the future, a future in which Hilary Clinton became president and Donald Trump didn’t. It all came down to analytics.

president clinton ts

During the last presidential election Barack Obama’s IT team shouldn’t have outperformed Romney’s team as massively as it did. At the heart of the Romney loss were three, as Donald Trump would say, huge errors.

The first mistake was using analytics services that didn’t understand elections, the second was using multiple services that didn’t coordinate with each other and the third was not questioning the data because it told them what they wanted to hear. This last has been a recurring cause of project and even company failure. The last mistake is not only being repeated by Trump, but he appears to be overt about it.

It would seem ironic that after giving Romney so much grief for losing, Trump is setting things up so that Romney will be able to say, after Trump loses the election, that at least he didn’t lose THAT badly. Clearly that is the outcome Ted Cruz just bet his political career on.

Trump don’t need no stinking analytics

When you read this coverage out of AdWeek that is the conclusion you walk away with, but I think it speaks to a far more common problem. When numbers agree with an executive’s view, they like them and when they don’t, there must be something wrong with the numbers. Don’t get me wrong, given the problems we’ve had with analytics that could well be the case. I recently reported on a KPMG report that basically said the majority of CEOs didn’t trust their numbers, which suggests Trump is in good company but it is still a stupid conclusion. The right path is to either better understand the numbers and/or make sure you can trust them.

Romney vs. Obama

What seems strange to me about this is here you had a guy who runs big businesses and a guy who was basically a teacher with slight political experience, and it was the teacher who used analytics better. Obama had a better team, made far better use of the systems it put in, were far more cost effective, and the results assured Obama’s second term.

Romney, however, was convinced he was going to win because the numbers told him what he wanted to hear. As a result, his team pulled back, thinking its candidate would coast to a win. So, in this case, Obama trusted his numbers, they were right, and in executing against them he won. Romney also trusted his numbers, but they were wrong, and he lost. So answer should be to ensure that the numbers, the analytics, are accurate not distrust the numbers.


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