Applying Analytics in the Workplace (Part 1)

Data and talent analytics has the potential to have a significant impact on business results and inform workforce actions in organizations.

Building a better business today starts with data—how you get it, how you analyze it, and how you use it to impact an organization. The problem? As today’s data-driven world gets more sophisticated via mobile, cloud, and Internet of Things devices, most organizations lack the tools and skills to turn their workforce-based data into business insights.

Human Resource leaders are experiencing an enormous amount of pressure to evolve from an operational function to one that contributes to the bottom line and improves business outcomes. HR professionals are looking for ways to expand their business impact. One key to this impact? Data and analytics.

According to an IBM Institute study on talent analytics, however, only approximately 20 percent of organizations have the ability to apply analytics to address important people issues across the workforce due to lack of skills ( Many companies have strengthened their analytics capabilities in marketing, supply chain, and finance, but few have become adept at applying analytics to get the right people in the right place and have them working productively quickly, drive every employee’s impact, and optimize strategic workforce planning.

Here’s where cognitive computing comes into play ( Scientists and engineers at IBM are pushing the boundaries of science and technology with the goal of creating systems that sense, learn, reason, and interact with people in new ways. It’s aimed at making the relationship between human and computer more natural so that, increasingly, computers willoffer advice, rather than waiting for commands through programming.

Advances in cognitive and cloud computing are enabling HR to get to the point of understanding business impact much faster than they’ve been able to do previously. Cognitive computing opens up a new world of possibilities for both employees and organizations via an ability to “democratize analytics,” and make it accessible to a line of business leaders such as HR. A data-driven cognitive system, for example, can help HR recognize attributes, traits, and characteristics in applicants and employees that create a best fit within the organization. Instead of using intuition to select prospective employees over other candidates, cognitive learning can be used to determine how their professional styles mesh with the workplace culture.

Analytics in Action

Some leading organizations are using cognitive analytics across the company to identify the drivers of attrition. Analytics provides an opportunity to see the organization’s most valuable resources in a new, more revealing light. Management can look into potential futures and act to prevent scenarios where top performers leave the organization.

AMC Entertainment, for example, used workforce analytics to identify traits such as social sophistication, initiative, and integrity as the best predictors for good concession workers. The concession stand drives a big chunk of a movie theater chain’s profit. AMC factored the findings into its hiring process, looking for the desired traits through an online behavioral assessment. The results? Despite the fact that mostly high school and college students staff concessions, employee turnover is down almost 50 percent. AMC had 1.2 million applicants in 2014, compared to just a quarter of that four years earlier.

In another example, Hudson Valley Federal Credit Union (HVFCU) used talent analytics to transform the company’s recruitment strategy. To reduce turnover in entry-level positions, such as tellers and customer service representatives, HVFCU analyzed its recruiting data to uncover common patterns in the skills, work experience, and personality traits shared by top performers. The company was able to analyze these trends with visual representations of its workforce data and suggested areas for further discovery. HR teams now can make new discoveries about workforce performance, talent needs, and readiness to capture new business opportunities.

Greater access to data has enabled these companies and others to shift from focusing on specific employee decisions to aligning talent management processes. HR can’t be limited to being a series of isolated silos focusing on staffing, training, compensation, and succession. HR needs flexibility to function as a set of integrated talent management processes designed to ensure a steady supply of high-performing talent in critical job roles.

Developing an Evidence-Based Perspective

As described in the Starting the Workforce Analytics Journey report (, HR leaders are guided to:

  • Focus on business priorities
  • Leverage analytics through storytelling
  • Use analytics to help inform decision-making, not as a substitute
  • Understand that perfect data isn’t required for a successful analysis
  • Have a point of view that not only understands the past but also optimizes the present and attempts to predict the future

Despite the challenges, workforce analytics has the po tential to have a significant impact on business results and inform workforce actions in organizations. It enables leaders to discern previously unconnected patterns and trends and develop an evidence-based perspective of vital workforce challenges and opportunities. Bottom line? Leveraging analytics takes the guesswork out of workforce management, enabling an organization to improve the methods of attracting and retaining talent, connect employee data to business performance, and differentiate the company from its competitors.

Part 2 of this article will appear in the September/October issue and look at how to understand employee needs and company culture / environment quickly.

With more than 20 years of experience in information management, analytics, and big data technologies, Jackie Ryan is the director of Workforce Analytics for IBM’s Kenexa portfolio, and is responsible for the strategy, solutions, and overall workforce analytics business. For more information about IBM Smarter Workforce, visit: