It's hard to avoid the term "Big Data" in today's business world. Many corporations seek to mine their data for insights and numerous consulting firms offer practices that can help. As a researcher whose career depends on analyzing data, I am predisposed to embrace this trend. However, I am cautious. So, in this blog I'd like to explore the potential power of big data in HR, but in a later blog I will examine the potential perils of big data as well.
As I study the big data strategies in HR, it seems to me that these offer great potential in terms of insight, connectivity, and personalization.
Economists often refer to "Asymmetric Information" as the situation where one party possesses information that another party (i.e., competitors) does not have, and this information can be used as a source of competitive advantage. The idea is not just of turning data into insights, but turning it into insights that your competitors do not have. If you have read just about every Michael Lewis book, you have seen the theme of asymmetric information. For instance, in Liar's Poker he describes how bond traders have information customers don't, and that information enables the traders to make exorbitant amounts of money. More recently, his book Moneyball described how the Oakland A's used information other teams ignored (On base plus slugging - OBPS) to attract and select better players at below market rates. Or, most recently, The Big Short described how hedge fund managers used information about the relative quality of mortgage-backed securities others were not using to become incredibly wealthy even as the financial markets imploded. Similarly, to the extent that firms can turn their internal data into insights their competitors do not have, they have to potential to leverage that asymmetric information as a source of competitive advantage.
Second, big data strategies can leverage data to increase connectivity by making it easy for employees to interact with people, and do so in way that they want to, not because they are ordered to. Early knowledge based systems allowed people to seek out and find knowledge that was embedded in the system, but this depended on (a) having people input the knowledge and (b) people being able or willing to try to access it through the impersonal system. Second generation knowledge-based systems sought to add on the social component by connecting people to the people who have the knowledge. Psychologists refer to this as "transactive knowledge" or knowing who knows. As companies implement internal social media "Facebook-like" systems, these systems create the connectivity so that people do not need to know who knows until s/he needs to know. In addition, the information shared over these systems may provide even more data to be mined to create asymmetric information advantages.
Finally, big data efforts can enable a personalization to the employment experience through knowing what drives employees and what employees need without them asking. Most HR practices started with one-size fits all approach. The first step to customization came through cafeteria plans letting employees pick the portfolio of benefits that best met their individual needs. Personalized marketing of programs and information now seems on the horizon. For instance, when an employee's status changes (e.g., marriage, baby, adoption, move, etc.) this signals something about a change in their desires, values, and needs. HR functions could immediately propose ways they might change their pension contributions, life insurance, work schedule, etc. in a way that shows them the company knows about them, cares about them, and wants the best for them. Such personalization holds the potential to more deeply engage employees to their firms in a way that creates competitive advantages.