Hillary, why couldn’t you see what was in plain sight?

Hillary, why couldn’t you see what was in plain sight?
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“Before Donald Trump won the presidency on Tuesday night, everyone from Nate Silver to The New York Times to CNN predicted a Trump loss—and by sizable margins,” cited Wired.com’s article Trump’s Win Isn’t the Death of Data.

I guess their data was flawed. Since Election Day, there has certainly been a lot of reflection on what happened to Hillary’s election. So why didn’t she, the Democratic National Committee, the press, and most of all, the pollsters see what was coming?

President-elect Trump’s people sure did. They were able to gauge which way the winds were blowing far better than the more traditional forecasters. And all of that tweeting did what it was supposed to do: sway voters his way.

An excellent article in The Wall Street Journal, published the day after the election, suggests that some polls (such as the USC/LA Times Daybreak poll) used algorithms and a grading process to try to accurately ascertain how people were going to vote. These methods suggested that voting was trending toward Trump. Did Hillary’s team miss what was right before them?

Other polls using more traditional data based on historical patterns (which proved inaccurate, given the nature of the campaigns) failed to see what was happening. As Cade Metz writes in the Wired article: “This wasn’t so much a failure of the data as it was a failure of the people using the data. It’s a failure of the willingness to believe too blindly in data, not to see it for how flawed it really is.”

It’s not the data—it’s the stories about the data that make a difference (and sway elections)

Perhaps this is the perfect time to drive home the fact that “data does not exist.”

Anthropology 101 teaches that data, whether soft observational research or cold hard numbers, essentially does not exist when taken out of context.

The U.S. election is a perfect example. The pollster’s brains kept seeing what their mind maps believed was true and discounted data that didn’t fit their own models of perceived reality.

Here is how the “mind map” works:

To make sense of data, the brain converts it into stories so it can visualize it so it can be shared among others. But the brain hates to change! So whatever the brain’s mind map starts out with dominates how humansin this case, pollsterssort and visualize their data. Basically, your brain takes in the information it likes and discards the rest.

Which leads us to the failure of the pollsters.

Were they just looking for what they were expecting to see, ignoring anything that ran counter to their projections?

Or were they looking at the wrong data, and/or using outmoded methods of gathering it (calling people at home on land lines)?

Or did they fail to tap into social media methodologies readily available today to capture the conversations taking place on social media?

My guess? All of the above.

As the graph below from Techcrunch reveals, social media was revealing early on how well Trump was connecting with his audience. Did Hillary and her team not see the patterns emerging?

How a little anthropology could have helped

How different might the outcome have been if Hillary’s team had taken a page from the anthropologist’s notebook and headed out into the field to listen to what people were saying? It was out there, if they had only opened their ears to hear it. I certainly heard it.

As I travel around the country working with CEOs of midsize companies, I don’t have to listen to them very long to hear what is bothering them. Throughout this election season, they weren’t necessarily pro anyone. But they were out of patience with the Obama administration. What were they so ticked off about?

1. The new labor laws

2. The new healthcare costs

3. The new SEC rulings

4. The failure of anyone to care about them and their business, in particular, as well as business in general

5. A feeling that BUSINESS was not at the top of anyone’s agenda in the Obama administration. Or for that matter, in Hillary’s.

They were worried about how to sustain their company’s value, keep it growing and manage the millennial work force while the government piles on more and more regulations. And with the new global economy, they weren’t sure how they could compete in the coming years with our country’s trade agreements.

I also heard from many of our physician clients and hospital leaders who are struggling to deal with the changes coming from CMS, as healthcare shifts from the current payment model (volume) to a new one (value). While healthcare in the U.S. approaches 25% of the GDP, (unsustainable), they didn’t want to have to change to reduce costs and improve the quality of care, nor were they going to vote to support these changes.

While I could share any number of comments, here is one from an anonymous blogger on KevinMD.com. An independent physician who wants someone to help her stay that way, she writes that she is “hanging on by a thread, but still hanging on.” Due to her rising staff costs and reduced revenue from payers — insurance, Medicare, Medicaid — she voted for Trump because she needs a change.

Most tellingly, she remembers being in med school in the 1990s when Hillary was in charge of modifying the healthcare system: “If you remember the HMOs then you remember the fiasco that healthcare became with ‘Hillary care’ with many doctors closing up shop. Our own family doctor retired early and actually warned me not to go into medicine.” Not a rosy assessment.

These are three substantial groups expressing their anger, but did the Democratic campaign bother to listen to them? No!

Sure, NOW we all see what was in plain sight all along: the core of America’s mainstream desperately wanted a change and on November 8th they elected someone they think will bring it to them. If Hillary and her team had tapped into these concerns, she might have connected with these voters. Instead, all she got on November 8th was a loud “no-thanks.”

Are you too missing what is in plain site?

Are you letting your own biases and mind maps filter reality to affirm what they believe to be true, ignoring what is actually happening? Are you looking at old data points while new ones are staring you in the face? If so, you better wake up and fast. Your customers are talking to you. Can you hear them?

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