Human Resources Management Meets Big Data in Devising Systems to Identify Star Employees

"2009 Leonid Meteor", Image by Ed Sweeney

“2009 Leonid Meteor”, Image by Ed Sweeney

Have you ever seen a clearly talented colleague at your workplace who was not fully recognized for his or her potential?

Today there is a raft of sophisticated data-driven software products being marketed to Human Resources departments (HR) to assist companies in finding possible star employees. However, some of these systems are not living up to their own, well, potential. Employers are still struggling to identify people on their staffs who have might be likely to excel in their future career paths.

This modern workplace quandary was the subject of a very interesting and informative feature in the June 17, 2015 edition of The Wall Street Journal entitled Are Companies Any Good at Picking Stars?, by Rachel Feintzeig.  I will sum up some of the main points, annotate, and ask some additional questions.

Businesses today have a wealth of data about their employees’ performances and productivity. Nonetheless, identifying who among them have the greatest potential to assume leadership roles in the future is still “more art than science”.  Assessments by humans as well as software algorithms are both still lacking in some respects.

As a result, companies including Nokia, American Express and SAP are turning to new means to measure employee potential. These include new forms of metrics and classifications, as well as games to identify leadership characteristics.

No firm has yet constructed a truly breakthrough HR system to accomplish this. Furthermore, a survey entitled Potential: Who’s Doing What to Identify Their Best? to conducted by Talent Strategy Group LLC indicates, among its other findings, that much of the approximately $70B to $75B US spent on corporate training has been “misspent”.

Tom Rauzi, Dell’s Director of Global Talent, will soon be launching a research project to assess employee data including “education, trajectories and performance” in an effort to identify candidates who might be best qualified to move up in the company.

Generally, when managers have workers with high potential, they have a tendency to choose people “who are like them”.  In another survey, this one by US-based management and advisory company CEB Inc., 25% of 9,500 manager surveyed reported that they “reply on gut instinct” when choosing potential future leaders. This might suggest why some businesses are so challenged in locating “fresh thinkers and diverse hires”.

Christopher Collins, “an associate professor at Cornell University’s School of Industrial and Labor Relations and director of its Center for Advanced Human Resource Studies“, reports that workers who sensed their work is being tracked and evaluated for advancement, often stay with their companies longer and work harder.

Conversely, those workers who are not tracked for future leadership may become resentful. As a result of this, SAP North America ended its high potential categorization.

Carie Davis, who until March 2015 was Coca-Cola’s Director of Innovation and Entrepreneurship, sensed that the company’s high potential program was made up mostly of “Type A employees” with common backgrounds. During some meetings, she found that the discussion ended up being more about “jostling for power” than the intended purpose of innovation.

At a management consulting company called Development Dimensions International Inc., a vice president named Matt Paese reported that companies are now using executive level assessment tools to test thousands of employees throughout their companies. His firm is set to soon start offering a “cheaper, lighter version” of their existing executive-level products for this purpose.

Some HR software vendors are devising their own new tools to illuminate potential. Their algorithms draw from a series of metrics including, among others, an employee’s 401(k) contributions, promotions and network connections within their firms.

For example, a system called UltiPro High Performance Predictor from Ultimate Software Group Inc., measures workers on the probability of their performing well, as distinguished from their potential, into future months. Currently, they are extending their research on “predictors of potential”.

Another suppressant of potential leadership in the workplace, rude and disrespectful behavior by management, was covered in a very insightful opinion piece in the June 25, 2015 edition of The New York Times entitled No Time to Be Nice at Work, by Christine Porath. I highly recommend reading this for its many piercing analytical insights as well as an adjunct to this terrific WSJ article by Ms. Feintzeig. I found that these articles overlapped on some points and can be seen as two sides of the same coin in their effects upon today’s workplaces.

My own questions are as follows:

  • In addition to all of the testing, training, metrics collection and analysis that goes on by HR departments, what if any role does the opinion of an employee’s peers have in spotting potential? While there are many businesses that engage in peer evaluations, I wonder whether on a more informal basis, are co-workers also asked to identify which of their colleagues could be future stars?
  • What are the results of follow-up validation studies in those who were promoted along a path to leadership? While the WSJ article explores the faults in these systems, what about the successes? If John and Mary have been vetted for a leadership track, do they more often than not meet such expectations? Are they more or less inclined to change jobs or departments along the way?
  • As companies, consultants and academics continue to experiment with and fine tune their algorithms, what is the relationship between and among data establishing a correlation as opposed to actual causation in identifying leaders? (This issue has also previously been visited in these five Subway Fold posts.)

Finally, for a hilarious take on a completely unqualified and unmotivated fictional employee failing his way up the corporate ladder, I very highly recommend checking out Season 2 of Silicon Valley on HBO. Here is an interview on Tumblr with the actor Josh Brenner, discussing his role as this character named “Big Head”.

Book Review of “More Awesome Than Money”

The rapid rise and ubiquity of Facebook during the last ten years has been a remarkable phenomenon. The figure currently used to express the company’s breadth is that they have more than 1.3 billion user accounts. They have successfully monetized their social platform using a variety of means including, among others, advertizing, networking, communications, and harvesting vast amounts of user data, on their site and elsewhere online, to make the users’ experience more “personal”.

Nonetheless, while most users have become highly dependent on their regular use of Facebook, there are many others who still feel somewhat uncomfortable with its privacy policies and intensive data gathering and analytics.

In 2010, four NYU students heard a presentation by Eben Moglen, a law professor at Columbia University, about the lack of online privacy and overall invasiveness of all of the data relentlessly vacuumed up across the web and used for a multitude of largely invisible purposes. This was the inspiration point for them to join together and try to create a privacy aware and fully decentralized social networked called Diaspora. Most importantly, users would own their individual data and be able to take it with them if they chose to leave. They established it as a non-profit entity that operated on an open source basis for its dedicated global corps of  developers.

The compelling story of the founders and Diaspora has been now been deeply and dramatically told by author Jim Dwyer (the About New York columnist for The New York Times and the author five other books), in his latest book entitled More Awesome Than Money (Viking, October 2014). With their full access and cooperation, he followed these four young men during every phase of Diaspora’s founding, funding and construction and implementation. They were driven by their desire to make a difference to like-minded social network users who wanted true ownership of their own data, rather than many of today’s other typical startups who are looking to strike it rich.

Their noble quest, with its many high and low points, has been very poignantly captured and told here. This not just another geeked out tome about a tech startup that struggles and then hits the jackpot. Rather, this text operates on multiple levels to very skillfully present and weave together, with much pathos and insight, the lives and motivations of the founding four, their rapid relocation and education in the startup culture of Silicon Valley*, and the complexity of achieving their objectives.

Despite their goal to assemble a true technological and philosophical alternative to Facebook and the support they received in their Kickstarter funding campaign, open source coding support, and the goodwill of many potential users seeking something utterly new like Diaspora, there were many obstacles along the way. These included differences that emerged among the core four, overly ambitious release dates and correspondingly high user expectations, funding challenges, and a tragic personal issue of one founder.

Dwyer recounts, with great internal consistency and engaging prose throughout the text, the complex trajectory of Diaspora. Readers will very quickly be drawn into the narrative and the multiple challenges encountered by the young company. As well, for anyone currently involved in a startup or considering taking the leap to launch one, More Awesome Than Money should be considered required reading. Its cover price alone, consider it a form of nominal seed capital if you will, is certain to yield valuable insights into the unique world of the startup.

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*  For another very high quality piece of journalism about a completely different startup in Silicon Valley, see  One Startup’s Struggle to Survive the Silicon Valley Gold Rush, by Gideon Lewis-Kraus in the April 2014 issue of WIRED.