Search all the business literature you can and you’ll never find data analysis compared to romantic love. But, hey, why not? Love’s trajectories might hint at what the business world’s newly enabled generation of data analysts can expect.
These data analysts tend to be independent, are often creative and at least partly self-trained. They’re strapped to rockets from Tableau, Lyzasoft, Predixion, and others, tools that are at first deceptively toy-like. Aren’t they analogous to the garden variety teenager? Bothg groups revel in newly discovered tools, while both pursuits are fundamentally social — as Lyzasoft CEO Scott Davis observes about data analysis. His blog post got me thinking about this.
Everyone shows up ready to rumble. They’re fascinated with the possibilities, they experiment in private, later they have a blush of quick results followed by a long trail of self-training on finer points.
Each group’s toolset is potent and designed for early success but never early mastery. They make lots of mistakes. In love and analysis, people fall for the wrong data, mess up good data and dates, do all kinds of things they wish they hadn’t.
Without realizing, they face danger. I’ve noticed that behind most good trends comes a rotten sibling right behind it. Think of the history of other social events: Hippies begat the Summer of Love and then came Altamont. We celebrated “free love” and then came a surge of sexually transmitted diseases. Baseball begat the World Series and then came batters on steroids. PageMaker begat self-publishing but then came the ugliest lost-cat posters ever tacked on a telephone pole.
You may already wish that bad analysis would go away. Pete Warden, for one, warns of some fabulous ways people trip over new data. We could easily call this stuff “data porn” and ignore it.
But there are even more treacherous pitfalls. These potent tools can change everything in a flash (at the “speed of thought”). One minute you’re in orbit, and the next minute you wish you were dead. With sex comes the hazard of a painful breakup, and with data analysis comes the danger of unwanted speech that’s too hot for any public platform. Oops!
We have ways to deal with all that, but it’s never pleasant. The rejected lover picks up and leaves, and the analyst just finds his creative viz zapped off the cloud — by those who are themselves learning a new role.
The lover and the analyst both feel hurt, perhaps betrayed. Wasn’t each playing by the rules? Wasn’t each part of the group? Suddenly each one feels rejected for reasons that a hasty explanation doesn’t quite calm the hurt feelings.
In hindsight, we realize we shouldn’t have been surprised. Social pursuits can be like this.
By the way, who said good tools were the end of the story? Well, most vendors did. Some teenagers think so, too. But even slightly more advanced users know that technical proficiency is only the price of entry. We do the real work in many long conversations and collaborations with words, data, gestures, misunderstandings and reconciliations, and on and on.
Here the analogy breaks. The tools will keep getting better while the bodies fall apart. But the lesson’s the same: Tools enable, but conversation — better known in the business world as collaboration — is really at the heart of our work.