Big data can be defined as data that are too big, too unstructured or too diverse to be stored and analyzed by conventional means, processes or tools. Such data come from consumer mobile devices, product and component real-time logistics, online advertising, Web portals, and financial and other news feeds.
According to Gartner, big data is expected to generate $3.7 trillion in products and services and 4.4 million new jobs by 2015. But according to Deloitte, only 6 percent of HR departments believe they are excellent in analytics, and more than 60 percent feel they are poor or behind.
Regarding the role of big data in HR, a few months ago my colleague Ian Ziskin and I conducted a Center for Effective Organizations survey of more than 300 HR leaders in 11 companies. We found 59 percent rated big data as important or very important to HR’s work. We also found 60 percent of these same HR leaders felt that HR’s ideal role is a “leader” or “key expert,” but 58 percent rated HR’s current role as “no role” or “occasional role.”
I’ve written about the potential impact of big data on HR processes such as talent management, performance management, rewards and recruitment, and how HR can learn from the advances in disciplines such as marketing and consumer psychology. Equally intriguing is how big data may disrupt the HR profession and entire HR industries. The history of big data in other areas suggests important lessons for today’s HR leaders.
Consider the evolution of financial and commodities trading. The world’s first stock exchange began in Amsterdam in 1602 with the issuance of shares in the Dutch East India Co. We traditionally think of trading floors based on the traditional “open outcry” system, filled with shouting traders chosen for their mathematical and risk-assessment skills. However, trading is now largely the province of algorithms, software and millisecond decisions made by automated systems.
An Economist article titled “Dutch Fleet” notes that the advent of trading algorithms in ultra-fast computer systems means that Amsterdam firm that formerly relied on traders and saw large bid-ask spreads now occupies a “high-volume, low-margin industry in which market-makers take a sliver of revenue from lots of transactions.” One firm saw a peak of 3,000 trades in 60 seconds.
The potential for big data to change employee hiring is well-documented. A New York Times article, “Big Data, Trying to Build Better Workers,” from April 20 discussed IBM’s $1.3 billion acquisition of Kenexa, saying, “Kenexa’s corps of more than 100 industrial organizational psychologists and researchers was one attraction, but so was its data: Kenexa surveys and assesses 40 million job applicants, workers and managers a year.”
Those psychologists and researchers bear a striking resemblance to the algorithm writers and system programmers in the financial and commodity trading industry. Those Kenexa data bear a striking similarity to the data in the millions of trading transactions per second. Is recruitment and search destined to become the kind of algorithm-driven fast-trade industry that commodities have become?
If talent assessment and selection go the way of commodities trading, what will be the role of today’s recruiters, search professionals and talent acquisition experts? In the future, will the “trader” in talent management and acquisition be anachronistic? Will former search firm executives and recruiters wax nostalgic about the good old days where you actually met and interviewed candidates and employers?
Before you say, “people aren’t commodities, so we’ll always need those insightful humans who can sense the intangible value in fitting the right candidate to the job or development opportunity,” consider the recent New York Times article, “Solving Equation of a Hit Film Script, With Data,” describing how algorithmic analysis chooses which screenplays will draw big movie audiences.
Did you know that a cursed superhero never sells as well as a guardian superhero, and that your box office gross is higher if your movie has a demon that targets humans rather than being summoned by them? One producer observed, “The only people who are resistant are the writers, who claim, “I’m making art.” Is the art of recruitment, succession and candidate search less algorithmic than the art of movie writing?