One of the most amazing and frustrating things about this year’s U.S. presidential race is that no one learned Obama’s lesson on how to make effective use of technology to win an election. It was a powerful lesson, too.
Largely using a mix of analytics and social networking, a young inexperienced politician was able to roll over the anointed candidate for his party. Four years later, he was able to overcome a negative approval rating to do it again — schooling Mitt Romney, who should have known how to use those tools better.
In the current election, the woman he defeated the first time didn’t learn this lesson and now is losing again. The one candidate who actually ran a technology company didn’t learn this lesson either, and what should have been a huge advantage never materialized. Are these people idiots?
I’ll offer my views on that and close with my product of the week: a set of high-tech morphing dark glasses that use smart glass to adjust for lighting changes automatically.
How Analytics and Social Media Can Win an Election
One of the most interesting lectures I’ve ever attended was one EMC hosted a few years back — a talk by the man who served as CIO in Obama’s election and re-election campaigns. He walked us through how the campaign staff used technology to beat the pants off Hillary Clinton, John McCain and Mitt Romney — all far more experienced politicians.
The first two evidently couldn’t spell “analytics” and put up no credible technology defense. While business expert Romney got that he needed a response, he executed it so badly you had to wonder how he was successful in business.
Granted, some argue that the quid pro quo for this with Obama was that Google basically owns him now. Still, the fact is he showcased that hiring a competent analytics team (Romney forgot the “competent” part) can result in a huge advantage.
What analytics and social networking provide is the combination of knowing what resonates and a low-cost model for delivering the related message. In effect, as I’ve noted before, social media gives someone who has natural manipulation skills a massive scale. Analytics is a force multiplier, because it identifies what voters want to hear.
It is an obvious lesson, so why didn’t Fiorina, who used to run HP, learn it?
One of the things that you learn if you follow CEOs is that each one has self-created blind spots that let others repeatedly stab them in the back. Fiorina’s are an unwillingness to acknowledge and learn from a mistake, and an inability to build loyalty with the folks most critical to her.
There were two key reasons Fiorina failed at HP, according to insiders. One: She obviously never understood the technology, so the folks who reported to her took many of her orders as ill-advised suggestions, not directives. Two: She wasn’t loyal to her people, so they weren’t loyal to her. This is often a problem with executives who overuse layoffs as a financial management tool. It builds disrespect, disloyalty and outright hatred.
Fiorina never understood the power of analytics, and the people who used to work for her who did understand how to use this technology for the most part either hated her, thought she was incompetent, or both. In any case, they never would be an asset — only a liability. Her tenure at HP is perceived as a failure, so it didn’t even set a good foundation for the argument that she would be a qualified choice for president.
As a female politician, she had a huge potential advantage over the folks running against her for the nomination — particularly against a female candidate from the opposing party — but only if she was solid on women’s issues.
Instead, she picked as her pivotal issue Planned Parenthood selling baby parts, which was discredited.
Planned Parenthood is a pro-women’s rights organization and by taking that position, Fiorina was at odds with much of what could have been her core constituency. Standing up for women’s equality in the workplace would have been a far more legitimate issue and one that was far more deeply connected to the female demographic, with no real potential downside.
Put another way, she made it easy for women to choose Clinton as the one who would best represent them. This is something a combination of analytics and simulation should have showcased easily, but it looked like Fiorina shot from the hip instead — and shot herself in the foot as a result.
Analytics vs. Confirmation Bias
I’m a strong believer that as a race, we are more likely to be wiped out because of some screwy political or scientific decision than any natural disaster. (Our last word as a race easily could be a scientist saying “oops.”)
At the heart of this is the concept of confirmation bias, or the hard-wired behavior we all have that inclines us to pay attention only to facts that support our pre-existing position.
Global warming contrarians are an excellent example, but there are folks who believe that the moon landing was a hoax, that the world is actually flat, and that electric cars are more inefficient than gas cars. (By the way, all are untrue.)
While you most often notice this when people take political, religious or racist positions, the fact is we all have this trait to favor information that agrees with what we already think. Analytics, done right, provides a data-rich tool that can refute a stupid and self-destructive position we have taken. Some of us likely need this as a defense against choosing dates unwisely (something very personal to me, because my mother died as a result of a bad choice like this).
Even though analytics can keep executives from doing stupid things, many refuse to use it because it also can be used to showcase they are wrong — and many, if not most, would rather believe they were right than ever admit they weren’t.
Apply that to scientists or politicians (the WMD Iraq war for instance) and you see the potential for a race-ending “oops.”
For example, much of the analysis on whether the Hadron Collider would end the world was done after the effort was funded and people were committed to its success. (Oh, and much of it also was wrong.) That should make you sleep soundly tonight.
Wrapping Up: The Lesson
The unspoken lesson is that it is far better to learn from others’ mistakes than make them yourself. Fiorina lost a lot of her money and a lot of money that was invested in her, both as HP’s CEO and as a failed candidate in two elections, because she didn’t learn from her mistakes or from the successes of the sitting president.
In the end, she didn’t prove her firing from HP was wrong — she proved she likely shouldn’t have been hired as CEO in the first place.
Maybe this showcases a set of questions boards should, but don’t, ask prospective CEOs. Do you understand, and can you demonstrate the proper use of analytics to make decisions? Can you point to a key group of competent people who are both loyal and will follow you into the new job? Can you show you can learn from your mistakes and the mistakes of others? Do you understand the industry and business you are being hired to work in and manage? Fiorina’s performance suggests that boards don’t ask those questions nearly enough.
By the way, as a side note on confirmation bias and the news — if you want to see how often news channels leave out contradictory information, Cracked does a regular series on how often we miss the story behind the story. One of its latest disclosures is that while the European petition to ban Trump for calling for a ban on Syrian refugees has around 560K Signatures, the UK petition to do nearly the same exact thing has nearly 430K signatures (it is No. 5 on the list). Pot meet kettle.
This is one of those products that is just cool.
CTRL Eyewear has used an Indiegogo campaign to successfully launch a product — in this case, smart glass-based dark glasses.
Smart glass is a technology that uses electrical current to change the state of glass — in this case from clear to dark. Unlike the auto-adjusting glasses of old, the change is instant. This technology has been used by fighter pilots and astronauts to protect against blindness.
This is especially cool in sports-oriented glasses, because the adjustment is so fast that your vision isn’t as compromised by rapidly changing light conditions.
Eventually the glasses will cost US$300 a pair, but they remain available on Indiegogo for $200. (I bought two myself).
They charge like a smartphone or Bluetooth headset with a micro-USB cable, and you can order the glasses to take prescription lenses. They also have a special version that has a blue lens for $25 more. That didn’t come out until after I’d ordered mine, unfortunately, but the black lenses work just fine.
So, because CTRL Eyewear is just cool, its new smart glass sunglasses are my product of the week.