One of my favorite comedic sets is a classic by the comic-social pundit Louis C.K., where he muses on the discontent he observes in people interacting with modern technology that just a few generations ago would have been considered nothing short of a biblical miracle. The concept of people’s annoyance with flight delays, slow internet connections in airplanes and the occasional dropped call are juxtaposed versus the true travel and communication limitations that existed not too long ago in a very humorous fashion, but one that hammers home a point about perspective with respect to modernity. Such is the life of the modern analytics professional.
We are functioning in an era where analytics professionals are the new “rock stars” of business, perhaps tracking towards their own Showtime series like “House of Lies” is for management consultants. What was once considered to be a backroom profession has become front and center in the evolving business landscape. More and more, modern analytics professionals are expected to routinely deliver projects in a matter of days, where just a decade or so ago such projects would have been considered a multi-year research program conducted by leading academics.
The result is the same modern impatience that Louis C.K. observes in society is perhaps even more prevalent in an “I want it yesterday” business environment. What this means is today’s analytics leaders cannot simply be modernized versions of the academic researchers who pioneered many of the methods we still use. Instead, they must be flexible, multi-faceted individuals who bring a mix of talents to balance the art and science of bringing data “big” and “small” to life. As such, the profile for analytic leadership has evolved beyond just being quantitatively savvy.
Being analytic in today’s environment requires the following:
Deep Quantitative Expertise: This is a table stake. To really be functional, useful and quite honestly meaningful, one must understand the tenets of the scientific method, have a broad comprehension of research methodologies and the ability to develop discipline out of perceived chaos. Whether one has studied in a mathematical, business, social or hard sciences environment is of less concern than having developed a discipline of thought and the ability to avoid dogma.
Intellectual Adaptability: The leaders in the analytics and data sciences professions are not necessarily the most quantitatively gifted. In fact, the gifted have a tendency to be most dogmatic because they see their skills as their distinct advantage and miss the value of nuance.
True analytics leaders recognize that that while their quantitative skills are important, their distinct advantage is the ability to adapt, evolve and leverage insights from other people and disciplines. The analytics person that fits in with the sales, marketing and strategy teams is much more valuable than the one that sets themselves apart.
Creativity: A good analytics professional can take data, apply a method and deliver results in a timely fashion that meets the business request of the day. An analytics leader though, is able to do all of the same things except they are also able to show others the implications of their insights and extract significant additional value associated with the discovery journey that they took to drive forth the results.
As an example, one of the most notable mathematicians of modern times is one Charles Dodgson; whose nom du plume, Lewis Carroll, authored Alice in Wonderland, the creativity of which is unchallenged. The point is that analytics leadership is as much about making insights accessible as it is about making them rigorous. The mix of analytic rigor that stimulates the mind with the ability to tell a story that reaches the heart is critical to drive acceptance and action.
Comfort with Ambiguity: One of the toughest outcomes that analytics professionals and their colleagues struggle with the most is the non-result. The market research industry has accelerated the adoption of quantitative analyses in business via the notion that these techniques reveal insights that would have otherwise gone unnoticed. As such, the perceived value of analytics is diminished if there is not a result, and typically diminished even further if the result is not in the direction expected by the key business stakeholders.
An analytics leader is sensitive to the needs of the business for directive insights, but not steered by them. They have the courage and foresight to acknowledge that sometimes there is no cause and effect relationship or that there are data/analytical limitations. But they don’t stop there. This is where the three previous characteristics come together. A true analytic leader takes the non result within the context of the business, their knowledge of other projects and provides their best effort at directive guidance based on their overall expertise and other insights.
The rapid adoption of analytics across the business spectrum has opened up significant opportunities for quantitative professionals, but the growth brings about some challenges as that market attempts to adapt. Lately, I’ve seen more clients and young analysts looking to solve the business issue prior to engaging in the project, which pretty much defeats the purpose of the endeavor. True analytic leaders recognize that the discovery journey is as important as the ultimate insights, and are able to bring others along to really elevate from the experience.
To be clear though, this is not to imply that analytics is only done well when done slowly, quite the contrary. The fifth critical characteristic of an analytics leader is the ability to move at a sometimes frenzied pace (Speed). While this seems to be a paradox with the notion of discipline, it is not. It’s actually the discipline, adaptability and creativity that enables an analytic leader to leverage their unique expertise to move swiftly, adroitly and successfully.
In my next post on analytics within CPG organizations, I plan to discuss how an organization might go about developing a talent pool of analytic excellence.