The Human Side of Analytics
The Human Side: Analytics Require Tact
Let me tell you a little story about a guy named Steve.
Academically speaking, Steve had been successful throughout his entire life. Long a straight-A student, in particular he loved numbers and always excelled at math.
Steve graduated from a top-tier university and was eager to make his mark in the corporate world at Acme—not to mention pay down his considerable college loans. How much harder, he thought, could the white-collar world possibly be?
It didn't take long for Steve to start skinning his knees at work. His first performance review hit him like a bucket of water. Yes, he was smart, but his personal skills inhibited his progress and represented a major liability. He often knew “the right” answer, but most of his colleagues weren't too keen on working with him. He tended to ignore the input of others and minimize divergent opinions.
Pretty soon, Steve was on the outs at Acme and he soon accepted a position at a new company—only to have his first performance review there manifest many of the same issues with his people skills.
Steve learned several key lessons the hard way. First, book smarts often don't equate with street smarts. Second, not everyone likes numbers and analytics. Third, a little tact goes a long way.
As this anecdote demonstrates, the person with the “right” answer doesn’t always win, especially if that person doesn't communicate it well.
This may run counter to your understanding of the “real world.” After all, isn't our era marked by Moneyball, Big Data, and ubiquitous connectivity? Haven't the geeks inherited the Earth?
Yes, but foolish is the soul who minimizes the import of communication skills. They are more important than ever, especially for the new breed of “quants” entering the workforce. In our rush to disrupt everything and redefine industries with analytics, it’s high time to take a step back. In this post, I'll describe a side of business that's all too frequently forgotten in our increasingly data-driven business world: the human element.
The Old Realities of New Workplaces
You might think that people such as Steve are anomalies. Surely, everyone else in Corporate America is on board with new, better, and more analytical ways of doing things.
And you'd be wrong. Very wrong.
A few years ago, I wanted to test different combinations of titles, covers, and subtitles of my then-forthcoming book Too Big to Ignore. After all, how did I know if I had nailed it? Why not test that hypothesis by gathering data and measuring the results? What could be lost from such an exercise?
It's not as if this was a radical idea, nor was it expensive or time consuming to implement. Exhibit A: Lessons Learned by Eric Ries, author of the best-selling book The Lean Startup. Ries used A/B testing to convince his publisher that some of its covers and titles just didn’t work. The proof: demonstrably higher click-through rates.
Against that backdrop, I pitched my editor Tom (a pseudonym) the idea. Sensitive to their workloads, I carefully framed my request as follows: Neither he nor his colleagues would have to do anything—other than “listen” to results of my experiments.
Tom emphatically put his foot down and, in hindsight, I understand why. He had spent more than 20 years establishing himself as a publishing authority. Tom didn't want the data to prove his judgment right or wrong.
And make no mistake: the workplace is rife with people like Tom—those who strongly prefer to make decisions based on gut feelings (theirs), not data and analytics. The question isn't if you'll encounter dataphobes in your careers. The question is when.
Tips for Getting Started
This begs the question, “How can the analytically minded be as effective as possible in their jobs?” Based on nearly two decades of strikes and gutters, here's my best advice.
Brush up on your people skills.
E-mail isn't a panacea. Pick up the phone once in a while.
While it may be easier for you to rattle off a torrent of e-mails, recognize that that approach is often ill advised. In fact, as considerable research has shown (PDF), e-mail lacks the subtle emotional cues that are part and parcel to effective communication. Yes, smartphones still make actual phone calls. With Skype and Google Hangouts, it's never been easier to see the person talking to you.
Dial up and down the technospeak as needed.
In Message Not Received, I advise people to tailor messages to individual audiences as needed. To wit, the CEO typically needs a bottom-line answer, not the step-by-step detail of how a problem was solved. This goes double when dealing with “old-school” technophobes who have considerable stature.
To paraphrase Cool Hand Luke, some men you just can't reach.
Some people don’t want to make “better” decisions no matter how tactful you are. You can bring them definitive proof that your method is the superior one and they will still find reason to ignore your recommendations.
You can lead a horse to water (but you can't make it drink).
Politics exist in all organizations; it's just a matter of degree.
Remember that organizations are far from meritocracies. Even organizations with very quantitative cultures (re: Google) suffer from internal politics and icky personnel issues. The difference between Google and [insert name of stuffy, bureaucratic organization] is a matter of degree.
Listen more than you talk—especially at first.
Going into a new organization like a bull in a china shop is almost always professional suicide. Take some time to learn nuances of perhaps an organization's most critical and finicky element: its culture. As Tony Hsieh of Zappos has said, ”Our number one priority is company culture. Our whole belief is that if you get the culture right, most of the other stuff like delivering great customer service or building a long-term enduring brand will just happen naturally on its own.”
Simon Says: “Data” and “technology” don’t make decisions by themselves; people do.
As I look into my crystal ball, the most successful employees of tomorrow won’t necessarily be the smartest or the most analytical. They will, however, be able to adapt. Cue Darwin quote.
More specifically, they will be able to ask insightful questions, solve problems, and back their suggestions up with data. Perhaps less obvious to you, though, is that they will be able to alter the way in which they explain their answers. They will understand that different audiences require different approaches. And, yes, sometimes those audiences will include those with zero knowledge of—and interest in—analytics.