Data Science Revitalizes Talent Development


Rawn Shah, Contributor

January 27, 2014

With employee engagement continuing to trend towards all time lows, regardless of the economy per Gallup’s measure, talent management is increasingly important to organizations. In another vein, the upcoming IBM Chief HR Officer study found than only 50 percent of organizations, across 342 CHROs representing 18 industries, are using workforce analytics in this manner.  The significance of talent has been increasing over the past decade, while it seems, most organizations are still not investing enough in its development.

Talent acquisition and recruiting of new employees is certainly improving with the rise of new approaches to candidate engagement and public social media listening to get a better understanding of candidates all around. Yet, talent management, motivation, and employee retention continues to be the real challenge. After all, every employee is an investment over time from the organization’s point of view to develop their understanding of the company culture, operations, methodologies and network. A sense of meaning and purpose regardless of where they lie in the organization, pay grade or job role is what drives engagement.

At the IBM Connect 2014 conference, I came seeking to understand how IBM is applying their knowledge of social networks and behavioral science to this challenge. Their basis in both social network and human resources software research and development puts them at a logical advantage.

On the first day, they unveiled the new IBM Kenexa Talent Suite that combines these two key areas into to provide support for Talent acquisition with recruitment software, social sourcing of talent, and on-boarding development of the hire; Talent optimization of performance appraisals, succession planning, and compensation; Analytics that support both areas; Social networks to increase productivity through peer learning and knowledge discovery; and integration into other HR systems.

It comes at a crucial time harnessing some of the possibilities of both analytics and social graphs. At a mere announcement it is difficult to assess what these data capabilities will look like, or how easy they will be to use for HR staff today. What it suggests is a new role in HR with a basis in data science to be able to work with the substantial data volumes that rise from social interaction. As Alistair Rennie of IBM indicated, “Data is the new natural resource… but just like oil it has to be refined to be put to real use… We need to make those analytics much more accessible to business people.”

In my most recent prior article, I suggested some new approaches to applying data science in leadership development. I had written about ways to detect informal leaders in the organization that influence the employee base independent of their position in the hierarchy. Some have said to me directly that there are organizational leaders who prefer not to know or ignore such informal leaders because it challenges the structure of hierarchical leadership. Yet, I think we all have a sense that there are such leaders out there. What we need are better means to detect them. In that article, I described a very basic approach of understanding centrality in the organizational network through Social Network Analysis (SNA), also called Organizational Network Analysis (ONA).

David Millen of Research Scientist at IBM Center for Social Software noted that I should not only talk about centrality, but also valence—does the person have a positive or negative impact on the network. He suggested looking at energy networks as investigated by Prof Rob Cross of the Univ. of Virginia, and a pioneer of ONA.  The concept was simple, map the relationships, and then ask the people if they felt energized or de-energized working with particular other people in their network—this is done by opinion polling, rather than sentiment analysis of each person. What you end up with is a more accurate view of employees by the energy they give out to others they collaborate with.

Mr. Rennie’s response focused on the simplification of these techniques into tools that HR business roles could use. “The IBM Kenexa Talent Suite is very unique… It will sit on top of Watson solutions… Make it accessible through natural language query… Provide visualization of that data in the right context. Beyond that, you need know what question to ask.” IBM points to the study of behavioral science as the catalyst to get to those insights.

The tools may soon be available but first we still need that drive within organizations to transform their HR operations to provide the enterprise social networks that employees need. Such networks also become the source of the data that they can apply to talent management and workforce analytics. It enhances the role of HR with new capabilities that bring it to modern data-based decision-making. While I will stop short of calling it predictive analytics, it certainly goes further to identify the reality of the complex view of your talent growing, supporting, starving or stepping to leave your organization.

Great ! Thanks for your subscription !

You will soon receive the first Content Loop Newsletter