Eleven votes | Seths Blog

Every year, the Baseball Writers of America vote for induction into the Baseball Hall of Fame.

Eleven of them voted NO when Babe Ruth came up for the first time.

If Babe Ruth gets eleven ‘no’ votes, why are we so worried about the noisy critic in the corner?

Source: Eleven votes | Seths Blog

Seth’s Blog: Some problems are easier to sell

Some problems are easier to sell

In order to solve a problem, you need to sell it first. To get it on the radar, and to have people devote time, resources and behavior change to address it.

Human beings in our culture are wired to pay attention to problems that are:

Visible–right in front of our eyes, not microscopic or far away.

Non-chronic–rationalization is our specialty, and the reason we learn to rationalize is so that we don’t go insane when faced with long-term, persistent issues. We bargain them down the priority list.

Symptomatic–this is a version of ‘visible’. If the problem has symptoms, and the symptoms are painful and getting worse, you have our attention. Symptoms that are stable or getting better feel much less urgent.

Painful–some problems have symptoms that aren’t so bad. And so we ignore them.

In our control–because helplessness is a feeling most people seek to avoid. The more certain the potential solution, the more likely it is people will acknowledge that there’s a problem.

Keep us from feeling stupid–because we don’t like feeling stupid, so we’d rather ignore the problem.

Status-driven–this one might be surprising. It turns out we like to focus our attention on things that will move us up the social hierarchy.

Expensive–problems that cost us money right now are ideal for this culture, because expensive = urgent.

Solvable–see that earlier riff about rationalization and chronic problems. If a problem doesn’t seem solvable, we’re a lot less likely to stake our attention on it.

This explains why cigarette smoking among the youth took so long to (partly) extinguish. It was a high-status activity, with no real symptoms for decades. It’s not painful and the visible side effects (thanks to billions of dollars in culture-bending spending by the tobacco companies) were seen as positive by many who participated. While the anti-smoking cause was definitely helped by the weight of evidence and persistent efforts by the medical community, it was higher taxes and enforced smoking areas that turned the tide. They made the problem expensive and a little shameful. People who didn’t want to look stupid or feel poor didn’t smoke.

Other problems that have a similar set of problems: Selling pre-need funerals. Addressing climate change. Balancing the budget. Bringing your kids to be vaccinated. Getting out of personal debt. Learning science and math. River blindness somewhere else…

If you’re working to sell a problem to your public, it’s tempting indeed to point out how shockingly irrational all of the instincts above are in practice. More effective, though, is to remarket your problem with a story that resonates.

Bad Data and Spaghetti Trees

A recent Manager Tools Email letter discussed the lessons from a very famous April Fool’s day trick in the UK.

In 1957, the BBC ran a clip of spaghetti being made.  It wasn’t being made in a kitchen, instead the clip showed spaghetti growing on trees.  In the 1950’s, pasta was not an everyday food in Britain. It was an exotic delicacy and purchased in cans.  The joke of it growing on trees was perfectly believable, especially when they used a very respected broadcaster Richard Dimbleby for voice over.

At Manager Tools,  they were looking at data around purchases on their site.  They dumped the data from of the website, and started analyzing.  It was all going well, until someone point out the analysis said 80% of the people who bought only one item had bought it for someone else.  That didn’t seem right.

Like the spaghetti trees, since the data came from a respected source – their database, they didn’t initial question its validity.

A respected source though, doesn’t mean you shouldn’t question what is put in front of you.  “If the data doesn’t make sense, then acting on it makes even less sense!”

“There’s two lessons from this.  First, always have someone else look at your data and analysis if there’s the smallest chance it might not be right.  Second, if someone’s data doesn’t look right, say something.  If you Google “bad data”, you’ll find hundreds of examples of companies spending millions based on data that’s just plain wrong, from New Coke to Enron.   You might feel like a little cog some days, but little cogs drive big wheels.  It was someone like you who started it all, and the story ended on the front page of the Wall Street Journal with a headline that read, “Bad Data ….”

This was a nice and timely reminder.  I’m on a portion of the product program’s deliverables that are dealing with “data analytics” at work.