When I was a young man starting out in the world, I was once given an assignment for the marketing people. The job was to gather up and detail the costs of various marketing programs. For some reason they did not track these things in the accounting system. That meant I had to rummage through filing cabinets pulling out invoices and then tabulating the results in a spreadsheet. My guess is I was given the task mostly because I was the only guy who could use Lotus 1-2-3.

I gathered up all the data for the periods in question and put together a report. Out of curiosity, and to be a suck up, I created s chart that showed the impact of various marketing efforts on sales. I even factored in things like the number of peak sales days in a month and adjusted the results to reflect these variances. What jumped out to me was that marketing did nothing for sales. I then expanded the data range to include previous years and it was more obvious. Our marketing was a waste of money.

I was young, but I was not an idiot so I gave the VP of marketing the numbers without my analysis. He then used them in his presentation, in which he claimed to be the key to the company’s success. I sat watching it waiting for someone to point out that he was full of baloney, but no one did. What I realized was everyone believed in these types of marketing schemes. They had to work because everyone did them. The VP of marketing liked his job so he told everyone what they wanted to hear.

The point of this walk down memory lane is that people have been using data to lie to one another long before we had cheap database software and Chinese quants cranking out reports. My bet is the first modern humans to migrate out of Africa had a meeting where Grog held up a skin, with marks on it, that he claimed was proof that slow food and fast women were just over the horizon. Data analysis is often just another form of magic that we use to grease the wheels of life.

This always comes to mind when I hear political types talk about their data operations. Reince Priebus is running around saying it was the GOP data operations that got the Trump vote out on Tuesday. He was on the radio claiming that his team “knew what people ate for lunch, when they went to work and how they voted in the past” so they could target these voters and get them to the polls. He made it sound like they had studied all of us since birth so they could maximize their vote.

This is nonsense. Trump had none of this stuff in the primary and he poleaxed everyone in his way. His “ground game” was to go on TV and radio and be interesting. Then he went on Twitter to give reporters something to ask him. In the general, he preferred the old fashioned whistle stop tour. Instead of a train, he flew around on his plane and did stadium shows near airports. His campaign was lean and mean, avoiding the trap of hiring an army of experts. Trump was outspent something close to 5-to-1 when including outside groups.

The fact is people buy stuff because they think they need it. They buy your stuff because they think it is cheaper or they think it has high status. I have a $200 Windows phone because it does everything I would want to do on an iPhone. My friends all have iPhones because they think it makes them look smart and hip. No amount of analytics are going to get me to buy an $800 iPhone nor will it make the cheap mobile phones hip and trendy.

Similarly, people vote for a few reasons, one of which is tribal loyalty. I know people who will never vote for a Republican, even if the Democrat is an ax murder. No amount of data analysis is going to alter that reality. The persuadable, on the other hand, can be persuaded if the candidate is appealing and offers them something they want. Similarly, the loyalists will turn out if they like their candidate and he has something to offer. Again, big data has nothing to do with it.

I suspect Trump’s reluctance to sign off on the big data operations, in his campaign, was due to the fact he has spent his life sitting through presentations in which clever guys tried to baffle him with data. Early in his career, he was the guy doing the baffling, as he convinced bankers and investors that his projects were going to make money.  Over a long career he has figured out that the basics of sales are immutable and the rest if just window dressing.

That’s not to say that all data analysis is nonsense. Steve Sailer has used publicly available voting data to analyze the lunacy of Official Conservatism™. It’s just that big data is not terribly useful in selling a candidate or a political party. Hillary Clinton allegedly had the greatest data team in the history of data teams. She had Google, Faceberg and Twitter working with the DNC to aid her data team. She lost because she is an awful person with nothing to offer.

But, that’s not what the data says, or at least it is not what the quants analyzing the data will say it says. Instead, they will work for the next year building after action reports loaded with jargon from statistics and demography, that will prove she just needed a bigger data operation and more “granular analysis in real time.” In 2020, the one-legged Latina lesbian the Democrats offer up against Trump will have the best data team and ground game in the history of mankind.