Organizations today are augmenting Human Resources (HR) intuition with analytics-based talent science. With the proliferation of big data analytics, HR finally has the luxury of aggregating job candidates’ data into sophisticated applications to be measured against the attributes and conditions of the top performers in specific positions. This correlation bolsters instinct and experience and can guide talent management decisions from hiring through exit.
“The concept of talent management is to identify competencies for every role in the organization, as well as the skills, credentials, education, and knowledge needed. It’s difficult to predict a candidate’s success based upon credentials,” notes Tarik Taman, general manager of Human Capital at software applications provider Infor.
Infor correlates the 39 most relevant work attributes (attention to detail, acceptance of authority, etc.) of top, medium, and low performers in every role throughout an organization, using that organization’s key performance indicators (KPIs). Those factors are weighted and used to guide hiring and promotion decisions for itself and its clients.
The result, Taman says, is a better fit between candidates and their jobs. For example, two nurses may have identical credentials, but the one with high “empathy” scores may be happier and more successful working in a hospital’s maternity ward, while the one with high scores for dealing with stress may become a top performer in the emergency room.
As organizations increase their focus on return on investment (ROI) and human capital spending, talent analytics is being used to reduce turnover and solve similar challenges, says Usha Mirchandani, partner in the talent analytics practice at Aon Hewitt. For example, “in call centers and other high-churn situations, the cost of hiring and training has a huge impact on the bottom line. Therefore, HR wants to develop profiles of the most successful call center employees and hire to them.”
The characteristics that determine success in particular jobs may vary geographically, even for the same positions at the same company. For example, the attributes of a top-performing sales manager in New York may be at cultural odds with those of his or her counterpart in Dallas.
Aon Hewitt currently is using its analytics expertise to profile top-performing senior executives. “We can predict the profiles that will succeed with 85 to 90 percent confidence,” Mirchandani says.
Beyond matching people to jobs, talent science also can predict company exits, whether for other jobs or for retirement. Those insights are based upon analyses of employees’ public personas through their social media interactions.
“How individuals interact in social media is a predictor of flight risk,” Mirchandani explains. “Job-hunters become more active on social media,” tweeting more frequently and updating their LinkedIn profiles than employees who aren’t seeking employment elsewhere.
An understanding of employees’ social networks, both in person and online, also can help predict whether they will retire when they become eligible. For example, employees are more likely to retire if those in their social networks also are retiring, according to a study by the Society of Human Resource Management.
Talent analytics also identifies the learning style that is most effective for an individual, as well as that individual’s strengths and weaknesses. “Once you understand their behavioral DNA, you can guide them, and they can guide themselves, because they can compensate for their weaknesses,” Taman says.
OUTCOMES
Talent analytics is credited with reducing turnover an average of 22 percent per year among Infor’s clients, Taman says. Employee performance, he adds, has improved 17 percent, “measured against hard KPIs. Companies say they feel they can shape the culture of their organizations for the first time.
“Being able to place teachers in urban or rural schools can be the difference between keeping or losing them after five years,” Taman adds. Accurately placing sales associates in the right department increased sales by 17 percent at one major department store, he notes.
LAUNCHING A PROGRAM
Incorporating talent analytics into HR decisions begins with defining a business case and then looking at the available data, says Jay Dorio, Ph.D., Product Management – Science for IBM’s Smarter Workforce. “It doesn’t have to be perfect, but you need a sense of what’s there. Clean the data as you go.”
As Mirchandani says, “Perfect data is almost a myth, yet companies are struggling to clean and harness data to get higher degrees of data integrity.”
Rather than focusing on cleaning data, she suggests focusing on the trends by gathering data and identifying patterns that add meaning to raw facts. For example, to correlate rewards with performance, she suggests identifying high potentials, where they are and how they’re rewarded. Identify patterns. Then incorporate data from the performance management system to correlate the reward structure with HR data for high potentials, contrasted with those of colleagues in those roles. Then you can determine whether high potentials are rewarded disproportionately, she says.
Another project may be to identify top performers in specific jobs and the factors that shaped them into the best. That information could become the basis of an assessment tool to screen candidates for those particular jobs. “The goal isn’t to hire copies of employees, but to identify people who thrive in the environment in which the top performers are thriving,” Dorio explains.
Whatever the project, develop a plan to act on the insights. “The details depend on the business question,” Dorio says, but the goal is to help organizations use that information to somehow improve.
NEXT-GEN ASSESSMENT
The appeal of talent science is that “it reduces human effort and builds on experience to predict performance,” Mirchandani points out.
For this reason, Taman calls it “the next generation of behavioral assessment. It looks beyond skills to include behavioral attributes.”
The use of analytics to produce actionable insights is a recurring theme throughout business. The transformation of the supply chain is just one example. Beginning in the 1980s and 1990s, Taman points out, “supply chain professionals spent tons of money to gain transparency to optimize their operations. But they found that transparency alone didn’t add value.” When followed by analytics, however, organizations gained actionable information that enhanced optimization. The analogy is just as appropriate for talent management.
CAVEATS
For all its promise, however, “talent science isn’t a magic wand,” Dorio cautions. “It’s a phenomenal tool,” but it also requires training, development support, and a focus on business performance to leverage its full value. “You need to ask the right questions and know what to do with the answers.”
One of those questions is whether candidates can fool the system. “Algorithms can identify when people are lying during the tests,” Taman counters.
Some professionals also wonder about the validity of the results, questioning the accuracy of the insights compared to those of seasoned HR professionals.
But analytics isn’t an “either/or” proposition. It doesn’t replace deep HR expertise in defining problems and understanding issues. Talent analytics is merely one more tool to increase candidates’ chances of success in their new roles.
Data will drive the next evolution of HR, transforming talent management into an increasingly strategic asset. But to be most effective, Mirchandani says, “be open to what the data is telling you.”
Pipeline or Pipedream?
By Evan Sinar, Ph.D., DDI’s Chief Scientist and Director of the Center for Analytics and Behavioral Research
From shorter ramp-up times to already having familiarity with the organization, the reasons to fill leadership positions from within—as opposed to hiring from the outside—are compelling. While most organizations understand the benefits, many seriously overestimate the amount of talent they have that they can readily promote.
For the Global Leadership Forecast 2014 ǀ 2015 study, which DDI produced in partnership with The Conference Board, we asked more than 1,500 HR professionals this question: “What percentage of your organization’s critical business leadership roles could be filled immediately by internal candidates?” The average response was just 46 percent—or, in other words, a typical organization has the in-house leadership talent to fill less than half of key leadership positions. Clearly, the majority of organizations have clogged or broken talent pipelines.
This dearth of talent leaves organizations with a risky choice: promote internal candidates who aren’t ready to fill the position or make the heavy time and cost investment to hire from the outside, and risk bringing on board a leader who may not be a good fit with the organization’s business drivers or its culture.
Making the situation even worse is the amount of time required for a leader to reach full performance. It can range from 19 months for the average front-line leader, up to 32 months for a senior leader. This means it can take more than two years before the organization knows if it has made the right hiring decision.
While an ineffective talent pipeline is a serious concern, it’s not an inevitable one. While the Global Leadership Forecast reveals the depth of the problem, it also identifies eight talent management practices that differentiate well-prepared organizations, with the strongest talent pipelines, from the rest:
- They use a systematic process to determine the quantity and quality of leadership needed.
- Competencies that underlie leadership success are clearly defined and communicated.
- Competencies are the foundation for multiple (not just isolated) talent management systems.
- Leader performance expectations cascade directly from the organization’s strategy.
- Leaders consistently have up-to-date development plans in place.
- Managers regularly review leaders’ development plans.
- Leaders don’t just learn skills, they practice and receive feedback on them with their managers.
- Formal programs are in place to ensure smooth leadership transitions.
Each of these eight practices was associated with a notable positive shift in an organization’s state of leader readiness. Organizations that engage in all of them (which is rare—only about one organization in seven) could fill 59 percent of their critical leadership positions immediately. On the other hand, those that eschewed all of these practices could fill only 31 percent of their positions.
The message here is clear: Strong, proactive, and development-focused talent management is necessary to fuel a ready supply of leadership talent.
Case Study: Strategic Insight Speeds Up Leadership Assimilation
Challenge: A leader at a Fortune 200 company was moving into a new position with 52 direct reports across seven regions. As part of her executive onboarding, she was expected to develop a 60-day strategic plan to move the business forward. To do so, she needed to rapidly and thoroughly understand the current state of the business. The leader traveled to each of the seven regions to meet her teams in person, but to obtain the level of insight she needed, several additional trips would have been required. Moreover, the leader recognized the difficulty of gaining an accurate understanding of the business through introductory team meetings, as employees are frequently reluctant to share their perceptions with a new leader.
Solution: The leader turned to 9Lenses—an organizational intelligence software that collects, connects, and quantifies insights from stakeholders for better business decision-making—in order to accelerate the onboarding process and help her quickly design a plan that would allow her to make informed decisions to move her teams forward. Designed to capture high-level perspectives on the effectiveness of the department, the 9Lenses interview platform targeted the core components of organizational health such as communication effectiveness, innovation opportunities, and operational efficiency.
Results: Over a period of 12 days, the interview collected more than 11,000 data points from 55 participants at a 95 percent participation rate. Because the interview was anonymous, the leader was able to circumvent political barriers to gain a thorough perspective. The data revealed several immediate focus areas, highlighting tools that were not as useful as assumed and issues around alignment of the organization with other parts of the business.
The leader communicated the results to her executive and the rest of the team to align key stakeholders to her strategic priorities. With the data collected from the interview, she was able to confidently formulate her 60-day plan with hard data and rich insights from her employees.
