Geeks rule in a world saturated with data.
With each passing year, the data we generate grows exponentially. At the same time, the bodies of knowledge that data feeds are growing broader and deeper. There was a point in the not too distant past where it was possible for the essential elements of our knowledge and history to be housed in a library.
No longer. If there’s one clear trend from the last few years, it’s that the tech-savvy are the ones who hold the power. The statisticians, data analysts and computer scientists who craft the models, methods and programs that collect and unlock those bits and bytes are today’s superstars.
Ask someone to put together a list of the marquee companies today and it’s likely they’d put Google, Apple, Microsoft or Facebook near the top of the list — all founded by young math or computer science students (or dropouts).
You don’t have to look far beyond the rise of tech companies to the top of corporate America to see the significance of big data. Online and off, our lives are increasingly governed and shaped by algorithm.
Trying to remember the name of that one actress in that one movie? Google stands ready to deliver. Internet search visionaries one day hope to be able to predict what you are looking for before you are even able to articulate it.
Looking for a good book or movie? Amazon and Netflix provide accurate recommendations based on your past searches and buying behavior. Type your favorite band into Pandora and it analyzes that group’s unique “music genome” to serve up a slate of similar songs.
Companies such as Facebook and LinkedIn, not to mention online dating sites, have even boiled down how we meet new people to a formula that finds people of like mind or background and serves them up without any effort on our part.
Data science has also made significant inroads into human resource management. Industrial organizational psychologists have developed sophisticated assessment and measurement instruments to sift through and identify high-potential job candidates based on a robust range of cognitive, behavioral and personality indicators.
Sophisticated network analysis tools sniff out the digital trail of emails, instant messages and intranet posts to pinpoint those key employees who are holding the organization together. HR software companies have tapped into the trend with an impressive set of products to collect, synthesize and analyze the data generated by employees daily and translate it into meaningful workforce action.
It’s not just the HR software vendors who see the opportunity. Online matchmaker eHarmony is reportedly retooling its dating software for the workplace. In addition to helping the lovelorn find a date, the company aims to help employers and employees find that perfect match.
But as anyone who has been through the dating game knows, what looks good on paper doesn’t always fulfill its promise in person. For every successful date, there are scores of potential matches that fail to light a spark. Like dating, talent management is both formula and insight.
Therein lies a danger. As big data gets bigger, science takes a more prominent management position and HR departments sharpen their analytical skills, the art of talent management risks losing something valuable.
Data does not equal knowledge, and knowledge — not to mention the insight and ability to translate it into action and advantage — is more art than science. It’s almost more like alchemy than an algorithm.
Take leadership. We try to boil it down to an easy-to-follow formula to hire, develop and promote high-potential talent into corporate leaders. That formula likely includes some ratio of skills, intelligence, authority, competency and charisma. Yet, despite all our efforts, leadership is more often than not a function of something inherent and intangible — a combination of vision, purpose, persistence and energy.
The challenge is how to take all the valuable data generated by the science of what we do and combine it with the art of talent management. Success requires a scientist’s eye for data and an artist’s feel for emotion.
