In the ongoing furor over the dearth of data scientists it is easy to forget that data-driven decision making doesn’t occur just in the analytics lab. Analytics is proliferating from the backroom to the boardroom and all the crevices in between. Making the ability to consume and apply analytic results critical. As organizations extend the analytic umbrella – inviting business and technologists to actively collaborate in analytic insight centers and labs – contributions from the non-quantitatively inclined are more imperative than ever. An analytic orientation and critical thinking is not just for the data scientist anymore (if it ever was).
In that spirit, the following checklist is a good test of your analytic leaning. Specifically, your propensity for analysis or logical reasoning. Not a quant? Have no fear: there are no questions regarding statistical theory or machine learning methodologies here!
YOU MAY BE ANALYTICAL IF YOU:
QUESTION FIRST, ANSWER LAST. Voltaire famously counseled that one should “judge a man by his questions rather than his answers.” This may very well be the cornerstone of the analytic mind which starts with interrogating the problem space before proposing the answer.
VALUE EVIDENCE OVER SUPPOSITION. This doesn’t discount the value of experience or even intuition. But an analytic thinker is always open to new perspectives on his perspective. The analytic mind relies on data to inform action. Even if it’s counter-intuitive.
ACTIVELY STRIVE TO DISPROVE YOUR OWN HYPOTHESIS. A highly seasoned executive remarked that he learned the hard way to take a timeout when his forehead felt flushed. Or – more tellingly – he was adamantly, absolutely sure his answer was the only right answer. Rendering any adversary dead wrong. Hmm. Great debaters test themselves by arguing the opposing viewpoint. The analytically savvy likewise actively test their own hypotheses. Relentlessly.
AND EVERYONE ELSE’S. The art of constructive debate is, some argue, a lost art. And while that may be overstating the case, analytically-inclined folks apply the same level of disciplined scrutiny and healthy skepticism (no, that’s not any oxymoron – or at least it shouldn’t be) to any discussion. Regardless of the source. But since what’s good for the goose is good for the gander, they also…
ENJOY BEING CHALLENGED. All well and good to be the devil’s advocate. But what happens when you are the one being deviled? Highly successful analytic professionals encourage constructive debate. And if not welcome, at least entertain, challenges from their counterparts. This is a particularly striking attribute of companies with highly performing analytic labs. Analytic leaders recognize that true innovation often lies in the space between the outside-in and inside-out perspectives on data scientists and corporate insiders. Outside the comfort zone of either party.
BELIEVE ANY EXPERIMENT IS A SUCCESS. Overnight successes and visionary leaders have one striking commonality: the number of times they failed or struggled mightily on their overnight or meteoric way to the top. Coupled with their perspective that all learning is good learning. Which, of course, has always been a core tenant of the scientific method. There are no “good” or “bad” results: just results. For many individuals, this means rethinking what “success” means.
RECOGNIZE THAT EVIDENCE IS NOT ALWAYS ENOUGH. OK. You’re right. So? Analytics provides facts and evidence to support and drive decision making. But facts alone are not enough to make people believe or inspire action. Which is why the ability to communicate and collaborate are highly sought after attributes – even for those talented quants.
ARE SENSITIVE TO CONTEXT. In that same vein, analytic decision makers are able to evaluate the evidence in the context of the environment at hand. The ability to objectively assess and ruthlessly separate the interesting from the instructive is critical.
KNOW WHEN TO SAY WHEN. Just like a trip down the internet rabbit hole, the search for evidence can be infinite. Without a deliberate method to come up for air, unmanaged analytic discovery can be long on results, short on action. In the old days, we called this syndrome “analysis paralysis”. The bottom line? Insight without action is moot. Which means that sometimes you have to be prepared to call the game.
APPLY A METHOD TO THE MADNESS. Proposed synonyms for “analytical” include methodical, rigorous and logical. Methodical should not be confused with inefficient. As any veteran of the agile wars can attest, great agility can only be achieved with great discipline.
So, are you analytical? If yes, good news! Great data scientists are a “what” (a team) and not a singular “who.” And they are looking for folks just like you.
That settled, how about the organization you work for? Check in with us for our next post to evaluate your company’s analytic orientation.