Workforce science: The evolution of talent management

Big data promises to transform organizational management. What makes big data so exciting is that web-browsing, location tracking, and social networks can help deliver automated, meaningful measurement (and prediction) of people’s behavior. Our emails, social network interactions and mouse clicks can be mined for “programmatic” insights. For example, life insurers can now learn more from our internet browsing histories than from a blood test. Personality-based assessment tests can accurately measure worker behavior and predict fit and performance.

So, can big data make for a smarter working world, with more efficiently run companies guided by data and analysis? Are there dependable processes for predicting behaviors, skills and preferences? Welcome to the relatively new field of workforce science, which adds predictive analytics to hiring and talent development, an area that’s long been dominated by gut intuition.

Workforce science relies on effectively engaging users, leading to the additional new benefit of inducing them to give up more data. Gathering and leveraging user data feeds a virtuous circle, because when data-driven experiences become more insightful and relevant, they deliver as much value to users as to the companies that deploy them. The need for greater engagement puts new emphasis on digital communication approaches like gamification, which has been gaining attention as a mechanism for improving user experience.

Games are the go-to medium for a generation of consumers for whom the “language of games”—game dynamics, interfaces and interactions—have been with them since childhood. According to Venture Beat, the average gamer in the U.S. is 31 years old. And it’s not just a “guy thing.” Women make up 48 percent of gamers. Half of workers play a game on their phone every day. Video games are not just kid stuff.

Gaming is no longer a solitary pursuit, as the most popular games rely on team collaboration, often among individuals who are strangers in real life. What does this mean for business communication? Leveraging a media platform that consumers celebrate in their everyday lives builds relevant relationships that yield more data.

Game-driven experiences offer competitive training and on-boarding experiences and measure user response. For example, The Road Ahead is an app that uses gamification to attract users and gathers their data. The interactive experience takes users on a journey about their interests in different career paths. Users participate both because it’s fun and because of its perceived value: play for a few minutes and The Road Ahead tells them who they are and provides a list of jobs that fit their personality. Sponsoring employers mine the competency-based assessment output to identify those worth further exploration and build a talent pipeline.

Similarly, UPtick is an enterprise software app that puts sales trainees into a virtual customer role play situation and scores them on the choices they make. The engaging gamified experience keeps them coming back and a leaderboard offers the chance to compete with peers for real-life incentives or bragging rights. UPtick’s built-in assessment system provides an immediate, real-time insight into the user’s selling competencies, serving both the user and the organization. With validated data available, neither party has to solely rely on a résumé to prove their worthiness.

A note of caution: Like other marketing collateral and employer brand messaging, a game reflects on the company that provides it. Besides providing accurate data, the game experience has to be worthwhile for users. Marriott’s “MyMarriottHotel” game on Facebook, which delivered a Farmville-like experience in a hotel setting, was an ineffective effort in this regard. The game wasn’t fun, and so did not catch on enough to attract candidates. It never got much of a chance to extract data about participant job fit.

Perhaps the best role for these tools may be in parsing and prioritizing what we know about the workforce. For now, humans still trump computers at identifying what makes a difference in organizational performance.

Authored by: Jim Wexler. Original Article may be found here.