Many companies investing in advanced talent analytics are seeing the payoff, according to High-Impact Talent Analytics: Building a World-Class HR Measurement and Analytics Function, a Bersin by Deloitte study. Based on a survey of 436 North American companies, the study reveals that advanced talent analytics is helping achieve better talent outcomes in terms of leadership pipelines, talent cost reductions, efficiency gains and talent mobility—moving the right people into the right jobs. Moreover, the same study found that share prices of the 14% of organizations in the study with mature talent analytics capabilities outpaced the S&P 500 by 30%, on average, over the three-year period from 2011 through 2013. Josh Bersin, principal and founder of Bersin by Deloitte, Deloitte Consulting LLP, discusses the study’s findings, the business value of advanced talent analytics and how CFOs can help their companies develop a mature talent analytics capability and benefit along the way.
Q: What business value are companies realizing from talent analytics?
Josh Bersin:Companies with a mature talent analytics function―one that allows human resources (HR) to use advanced statistical models or predictive analytics to improve their business planning and performance―are deriving value from their efforts in nearly every talent area.
Companies in our survey named improvements in recruiting, talent mobility, leadership pipeline and efficiency / cost-reduction as the top benefits gained from investing in an advanced talent analytics capability. For example, in the recruiting function, we found that about 80% of the most mature organizations studied have improved their recruiting efforts through their measurement and analytics efforts—more than twice as many as the companies that are least mature in terms of using analytics for talent purposes.
Sophisticated analytics teams can evaluate the effectiveness of different recruiting sources, assess the quality of hires and use prehire assessments to select better candidates. In leadership development, two-thirds of the most sophisticated teams have improved their leadership pipelines by analyzing data from assessments, leadership promotion rates and successor readiness.
More mature companies along the talent analytics spectrum employ analytics to gather insights for effective talent decision-making. At these companies, HR has strong credibility in providing data analysis and recommendations to decisions. On the other hand, business leaders at companies at the lowest maturity level typically make talent decisions based on their own experience or judgment, with little data-driven input.
As an example, we recently worked with a global company looking to improve its employee retention in China, where turnover tends to be very high in general. Managers were relying on their internal beliefs about how to retain staff, mainly focused around increasing compensation. An analytics project designed to identify the drivers of turnover, however, showed little relationship between compensation and turnover. Instead, the analysis showed other variables, such as the length of time in current position and supervisor tenure, to be key determinants of turnover. These findings led to developing a new, data analytics-based retention program that assigned each individual a departure risk factor and included development opportunities, job rotations, stretch assignments and career discussions with “high risk” individuals.
In the six months following the program’s implementation, the company significantly reduced turnover among its Chinese salesforce, which has positioned the company to meet its growth targets in the region.
Q: The talent analytics study found that only 14% of companies studied have mature talent analytic capabilities. What’s holding other organizations back?
Josh Bersin: A big challenge is that many HR organizations don’t know where to get started, or even what skills they need. I just had a call with a CHRO who told me, “We want to start an analytics project.” I asked what business challenges he wanted to address through analytics, and he didn’t know. That’s very typical. So even though many companies know they should be doing something, they often don’t know how what problem they are trying to solve, or how to go about solving it with the right data, skills and resources.
Q: What can CFOs, who generally have embraced analytics for their financial organization, do to encourage HR to employ talent analytics?
Josh Bersin: The first thing they should do is encourage and support HR in upping its analytics game. CFOs can start by insisting that HR start validating its talent recommendations with data, just as other business functions are required to do.
CFOs can also loan data-savvy people from finance to help HR advance its analytics capability. Finance typically has the most advanced analytics capabilities in a company and these professionals can help HR understand how to analyze talent data in combination with revenue, profitability and other operational data, which is critical to many analytics efforts. Eventually, HR should hire its own people with advanced analytics skills or develop skills internally, but at the early stages, HR can learn a lot from finance staff who are good with data manipulation and analysis.
Q: What are other ways HR can learn from CFOs in developing a talent analytics program?
Josh Bersin: Developing a talent analytics program should start with identifying the top business challenges HR needs to address. As CFOs typically have a view across the organization, they can provide a perspective on what the business needs from HR and where to focus efforts. That information will help determine the data HR will need to collect and analyze. For example, if the challenge is to improve the leadership pipeline at the business units, what are the metrics that the business needs to make decisions around leadership?
Originally published at http://deloitte.wsj.com
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