We’re Already Living in the Future of Talent Analytics

We’re Already Living in the Future of Talent Analytics

Recently at the Harvard Business Review, management professor Thomas H. Davenport asserted that HR “is right up there with the most analytical functions in business—and even a bit ahead of a quantitatively-oriented function like finance.” Davenport backs this claim with findings from a global survey of senior managers, directors, and VPs at large companies by Oracle, on which he collaborated. The survey found that many HR leaders are well-versed in using data and predictive analytics to make talent management decisions:

  • 51% of HR respondents said that they could perform predictive or prescriptive analytics, whereas only 37% of Finance respondents could undertake these more advanced forms of analytics.
  • 89% agreed or agreed strongly that “My HR function is highly skilled at using data to determine future workforce plans currently (e.g. talent needed),” and only 1% disagreed.
  • 94% agreed that “We are able to predict the likelihood of turnover in critical roles with a high degree of confidence currently.”
  • 94% also agreed that, “We have accurate, real-time insight into our employees’ career development goals currently.”
  • When asked “Which of the following analytics are you using?” “artificial intelligence” received the highest response, with 31%. When asked for further detail on how respondents were using AI, the most common responses were “identifying at-risk talent through attrition modeling,” “predicting high-performing recruits,” and “sourcing best-fit candidates with resume analysis.”
  • These findings suggest that the analytics transformation in HR is farther along than you might have thought, with the caveat that the survey respondents were from companies with $100 million in revenue or more, and are thus more likely to have the capacity to deploy new techniques and technologies that may be out of reach for smaller organizations. It should come as no surprise that more and more companies are adopting AI and analytics into their HR functions; what’s new in this survey data is that HR functions are becoming increasingly confident in the maturity and capability of their analytics programs.

    In terms of where companies are deploying talent analytics, Oracle’s findings track with what we have seen elsewhere: The lowest-hanging fruit is in predicting turnover, while there’s also a lot of promise in AI-powered recruiting, predicting performance, and career pathing. The focus on attrition makes sense, as employees who quit often time that decision to leave around predictable life and career events and drop lots of hints about their plans beforehand.

    If you can use data to detect these warning signs and head off unwanted departures, that can save your organization considerable amounts of money. IBM CEO Ginni Rometty made headlines earlier this month when she told attendees at CNBC’s @Work Talent + HR Summit that IBM’s AI technology was able to predict which workers were planning to quit with 95 percent accuracy:

    IBM HR has a patent for its “predictive attrition program” which was developed with Watson to predict employee flight risk and prescribe actions for managers to engage employees. Rometty would not explain “the secret sauce” that allowed the AI to work so effectively in identifying workers about to jump (officially, IBM said the predictions are now in the 95 percent accuracy “range”). Rometty would only say that its success comes through analyzing many data points.

    “It took time to convince company management it was accurate,” Rometty said, but the AI has so far saved IBM nearly $300 million in retention costs, she claimed.

    But predicting turnover with enough accuracy to add value may not require IBM-level AI capabilities. A new study from Peakon finds that employees begin showing clear signs of wanting to quit a full nine months before they pull the trigger on their resignation. A big-data study drawn from over 32 million employee survey responses in 125 countries, the Peakon report points to several key indicators of attrition that show up months in advance: declining engagement and loyalty, as well as dissatisfaction based on unchallenging work, an inability to discuss pay, an unsupportive manager, and the lack of a clear path to advancement in the organization.

    In a recent interview with David McCann at CFO, data scientist Jon Christiansen notes that it’s much easier to predict who will stay than who will leave, but highlights a few indicators that consistently point toward a greater likelihood that an employee will quit, such as whether the employee feels that their performance is evaluated fairly or that they have control over their workday. Other signs include an employee avoiding conflict, siloing themselves, focusing excessively on rewards over the common goal of the organization, and facing either too much or too little pressure at work.

    The advantage for a company like IBM, which continues to invest heavily in AI, is that it can delegate the detection of these patterns to an algorithm. Predicting quits was the first area the tech giant’s HR function focused on when deploying AI, IBM’s chief human resources officer Diane Gherson explained to Jena McGregor at the Washington Post:

    IBM had already been using algorithms and testing hypotheses about who would leave and why. Simple factors, such as the length of an employee’s commute, were helpful but only so telling. “You can’t possibly come up with every case,” Gherson said. “The value you get from AI is it doesn’t rely on hypotheses being developed in advance; it actually finds the patterns.”

    For instance, the system spotted one software engineer who hadn’t been promoted at the same rate as three female peers who all came from the same top university computer science program. The women had all been at IBM for four years but worked in different parts of the sprawling company. While her manager didn’t know she was comparing herself to these women, the engineer was all too aware her former classmates had been promoted and she hadn’t, Gherson said. After the risk was flagged, she was given more mentoring and stretch assignments, and she remains at IBM.

    IBM is also using its Watson AI for other talent-related purposes, such as learning and development or career pathing, Carrie Altieri, IBM’s vice president of communications for people and culture, noted in a recent interview with Riia O’Donnell at HR Dive:

    AI has been a driving force of innovation for IBM’s HR team. Cognitive talent alerts mine for patterns; it searches for employees who’ve been in a job longer than usual (which could signal flight risk) and can determine whether they need more training to move up. …

    AI also can personalize learning and development for each job role and lead the way in making learning a central aspect of a company’s culture. Altieri said that more than 45,000 learners are visiting IBM’s learning platform every day and 98% of employees access it each quarter. While the company requires 40 hours of learning per year, staff average around 50 hours, regardless of tenure. Learning is a huge part of the culture at IBM, she explained, and the new system gives managers the tools to have more intentional discussions with staff.

    And like other tech companies experimenting with these technologies, IBM is not only deploying its AI capabilities internally, but also selling them as a service to other organizations. Last November, the company announced the launch of IBM Talent & Transformation, a new business venture offering AI skills training in addition to services that “harness the power of AI personalization to guide employees in developing skills and pursuing opportunities to grow within the company.”

    Global Talent Monitor: Discretionary Effort Continues to Fall in US as Employee Confidence Dips

    Global Talent Monitor: Discretionary Effort Continues to Fall in US as Employee Confidence Dips

    In the past three years, the number of US employees willing to go above and beyond their employers’ expectations at work has fallen by 10 percent, from 27 percent in the second quarter of 2015 to 17.8 percent in Q2 of 2018, the latest data from Gartner’s Global Talent Monitor shows. Globally, employees’ confidence in business conditions has fallen for the first time since Q1 of 2016.

    One possible driver of employees’ declining levels of discretionary effort is a lack of satisfaction with opportunities to grow and develop in their careers. Nearly 40 percent of employees in the US and globally ranked a lack of future career opportunities as their main source of dissatisfaction in a previous job, displacing compensation as the number-one driver of attrition both in the US and around the world. Over the past few years, we have seen development opportunity grow to be an increasingly critical element of the employee value proposition, both as a driver of attraction for new employees and, in its absence, as a reason for quitting.

    “With recent U.S. reports showing little growth year over year in real earnings, workers hope to achieve more satisfaction in their jobs through better titles and opportunities to advance and grow in their current careers,” Brian Kropp, group vice president of Gartner’s HR practice, said in a statement. “To prevent further reduction in workplace effort and to retain top talent, employers should pay closer attention to employee dissatisfaction about the lack of career opportunities, particularly if wage growth remains stagnant.”

    “Leading organizations are able to use their employment brand to illustrate why their career opportunities are better than their competitors,” he added. “A company’s EVP directly correlates to employee engagement levels, as workers are more likely to work harder and stay in their current positions if they are highly satisfied with their company’s EVP offerings. Gartner data shows that organizations with high levels of employee engagement report financial outcomes three times higher than firms with lower engagement levels.”

    Read more

    Google’s Latest Diversity Report Features Data on Attrition, Intersectionality

    Google’s Latest Diversity Report Features Data on Attrition, Intersectionality

    Google’s 2017 diversity report, released last week, expands on the information included in previous reports to cover the retention and attrition of underrepresented talent, as well as an intersectional analysis of race and gender at Google. Overall diversity figures were little changed from last year’s report and showed limited progress since 2014, when Google first began making this data public. Men make up 69.1 percent of the tech giant’s workforce, while its racial makeup is 53.1 percent white, 36.3 percent Asian, 2.5 percent black, 3.6 percent Hispanic or Latinx, and 4.2 percent multiracial. In 2014, the Googler community was 61.3 percent white, 30 percent Asian, 1.9 percent black, 2.9 percent Hispanic/Latinx, and 3.6 percent multiracial.

    The company has made some progress in improving the gender balance of its leadership over the past four years, with its the percentage of women in leadership globally rising from 20.8 to 25.5 percent. Google’s US leadership is 66.9 percent white, 26.3 percent Asian, 2 percent black, 1.8 percent Latinx, 0.4 percent Native American, and 2.7 percent of more than one race. Black and Latinx representation in leadership have improved slightly since 2014, while the report highlights that 5.4 percent of new leadership hires in 2017 were black.

    The attrition data included in this report touches on an issue that tech companies struggling with diversity and inclusion have discovered to be of critical importance: not just recruiting diverse candidates but also retaining those employees for the long term. Based on an index of US attrition, Google’s report shows that attrition rates are highest among black and Latinx employees, at 127 and 115 compared to an overall index of 100. “Black Googler attrition rates, while improving in recent years, have offset some of our hiring gains,” Google acknowledges, “which has led to smaller increases in representation than we would have seen otherwise.” On a global index, attrition was slightly higher for men than for women, however, at 103 compared to 94.

    Read more

    What Microsoft Learned About Onboarding from Analyzing Its New Hires’ Experience

    What Microsoft Learned About Onboarding from Analyzing Its New Hires’ Experience

    Effective onboarding often makes the difference between a successful hire and an early quit. To better understand the causes of attrition among recently hired employees, Microsoft created a survey that was given to new employees after their first week and again after 90 days to find out about their experiences and first impressions of the company. The tech giant’s workplace analytics team also compared anonymous calendar and email metadata with engagement survey data from around 3,000 new hires.

    At the Harvard Business Review last week, Dawn Klinghoffer, Candice Young, and Xue Liu revealed what this investigation uncovered and how it shaped Microsoft’s decisions about how to improve new hires’ experience. One thing the survey revealed was that having a working computer and access to the building, email, and intranet on day one was important for new hires to be productive and engaged from the very beginning, making an important first impression that colored their overall experience. Their more complex analysis produced another insight: New employees who had a one-on-one meeting with their manager in week one were more successful than those who didn’t:

    First, they tended to have a 12% larger internal network and double network centrality (the influence that people in an employee’s network have) within 90 days. This is important because employees who grow their internal network feel that they belong and may stay at the company longer. For example, employees who engage internally intend to stay at a rate that’s 8% higher on our intent-to-stay measure. They also report a stronger sense of belonging on their team while maintaining their authentic self.

    Read more

    PayScale Study Highlights Engagement Value of Appreciation, Company Outlook

    PayScale Study Highlights Engagement Value of Appreciation, Company Outlook

    Chris Martin, Director of Research at PayScale, showcases the findings of a recent study his company conducted based on survey responses from more than 500,000 US employees. The study sought to gauge the impact of various criteria on employee engagement and intent to stay in their current jobs:

    Two variables stood out from the pack for both outcomes: whether an employee feels appreciated at work, and whether they feel their organization has a bright future. Employees who feel unappreciated or who think their organization isn’t going anywhere are less likely to feel satisfied at work and more likely to plan on seeking a new job in the next six months.

    Although they don’t align precisely, PayScale’s findings here underline a key insight from our Global Talent Monitor at CEB, now Gartner. This quarterly report provides workforce insights on global and country-level changes about what attracts, engages, and retains employees, based on data from more than 22,000 employees in over 40 countries. (CEB Corporate Leadership Council members can peruse the full set of insights from Global Talent Monitor.)

    What our latest global data show is that while compensation is the most common driver of talent attraction both worldwide and in the US, other factors are nearly as important to employees in deciding whether to take a job, including stability (related to the future prospects of the organization) and respect. Indeed, respect has been growing in importance as a talent attraction driver over time, especially in the US, Southeast Asia, and India. When it comes to drivers of attrition (what compels employees to quit), compensation is outranked both globally and in the US by future career opportunity, while people management problems and a lack of opportunities for development are also common factors in employee attrition.

    The other interesting finding Martin highlights from PayScale’s study concerns employees’ perceptions of pay practices:

    Read more

    When a Job Is ‘Just a Job,’ Are Employees More Likely to Quit?

    When a Job Is ‘Just a Job,’ Are Employees More Likely to Quit?

    A new survey from CareerBuilder claims that a 55-percent majority of US employees feel that they have just a job, not a career, and that 38 percent of these workers are likely to change jobs in the second half of 2017:

    Almost three in 10 workers (28 percent) tolerate or hate their job. Of those who tolerate or hate their job, some of the top reasons for staying in a current position are the need to pay the bills (74 percent), its proximity to home (41 percent), needing the insurance (35 percent), it pays well (30 percent), or the job market is too tough (27 percent).

    This survey picks up on something that we at CEB (now Gartner) have seen in our latest Global Talent Monitor data: Most US employees across a number of industries cite their future career opportunities as a leading reason for leaving their organization. Given this fact, it is easy to assume that this is a reflection that there is simply a lack of career opportunities available to employees, leading to disengagement and attrition. However, our data shows that this is not the case. We find that 12 percent of US employees we surveyed were actively dissatisfied with future career opportunities at their organizations and only 31 percent reported they were satisfied. The remaining 58 percent are somewhere in the middle—that is, neither satisfied nor dissatisfied, but rather neutral or ambivalent.

    This finding suggests that while future career opportunities are a key part of employees seeking a new job, the claim that lack of future career opportunities is driving attrition at organizations is overstated. When we look at how an employee’s satisfaction with future career opportunities at their current organization affected their engagement levels, we do not see nearly as strong as a connection as CareerBuilder reports in their survey.

    Read more

    The Business Lessons in Taco Bell’s Turnover Equation

    The Business Lessons in Taco Bell’s Turnover Equation

    In a session at last week’s WorldatWork Total Rewards Conference and Exposition, Taco Bell Vice President of People and Experience Bjord Erland discussed how the fast food chain has handled turnover—a major challenge in its sector—in recent years. At HRE Daily, David Shadovitz passes along some insights from Erland’s talk:

    Leadership was hearing that pay was a major reason people were leaving. But in order to come up with the right game plan, HR knew it needed more data. So it brought in global consultancy Mercer to better understand the key drivers behind the high turnover and identify ways to address it. When it looked at why workers stuck around, Taco Bell, a unit of Yum! Brands, found that a flexible work environment and strong culture were major drivers. As to why people were leaving, factors such as a high level of stress, lack of training and better opportunities elsewhere emerged as a big contributors. …

    Well, the big “Aha!” for Taco Bell was learning that earnings were far more important to workers than their rate of pay. Were they working enough hours, including overtime, to bring home a bigger paycheck? (Erland noted that Taco Bell’s pay was competitive with others in the industry.) In light of these findings, Erland said, the company began to increase its use of “slack hours” to increase the amount of employee take home pay. “Turnover improved when employees were able to bring home more earnings,” he said.

    Read more