by Donn Rappaport
It’s hard to write anything about the year 2016 without at least touching on the election. Shocking. Game-changing. Disappointing. Encouraging. Frightening. Empowering. Toxic. I could go on…but let’s just say, there was something for everybody. And even now that it’s over, it’s not over.
We’re all still talking about it. Trying to come to terms with it. How did it happen? What does it mean? How in the world did he do it? How in the world did she blow it? And mostly, how in the world did the polls, the pundits, the experts get it all so wrong?
We all have our theories. Mine, I guess, can be summed up in the title of a speech I gave a couple of years ago: Big Data is Dumb Data. The point of which was that the value of data, is simply a function of the intelligence, expertise and humanity of the individuals who are gathering, applying and interpreting it.
In the case of the election, the pollsters and data analysts missed the critical distinction between the message and the messenger.
Where Trump was concerned, a great many people found him personally objectionable on many levels. But they responded, nevertheless, to his message—if not the style or even implications of his delivery— about the need for immigration and tax reform, about creating jobs and keeping the jobs we have in this country, about dealing with terrorism and threats to our security in a more forceful and unambiguous way.
On the other hand, a great many people were pulling for Clinton, felt a kinship with her, wanted to see her be the first woman president of the United States. But at voting time, her inability to communicate a clear, compelling, resonant and inspiring message did her in.
They may have preferred her more as the messenger, but ultimately were drawn to his message.
And the data, in the hands of those who should have known better, failed terribly to make the distinction between the message and the messenger. If you go back and look at the polls, you will invariably see them focusing on questions like honesty, integrity, and suitability for holding the office of President. You will see very little, if any, effort to separate those personal qualifications (or lack thereof) from the critical issues that ultimately influenced votes—especially in the formerly reliable democratic-leaning swing states and rust belt.
It was as if a marketer tried to project campaign performance based on audience identification and market segmentation alone, without taking into account the message, the offer or the creative. It can’t be done.
As Steve Jobs once said, “It’s not the tools that you must have faith in—tools are just tools. They work, or they don’t work. It is the people you either can or cannot put your faith in.”
And not only in politics. Quite often, however, we see businesses fall into a similar trap. We see otherwise smart, successful organizations downplay the role and necessity of smart, talented, experienced people in the hopes that the data, or technology, or system automation will save the day. It rarely does. It’s only when you put smart data, proven technology and objective-oriented automation in the hands of smart, experienced and capable people that the result is reliable data analysis.