Data scientists are among the most in-demand professionals in the US right now, as more and more industries look to harness the power of data to drive productivity and innovation to new heights. Demand is high and supply is short, so these experts command remarkably high salaries. However, recent research has suggested that many companies’ data isn’t sufficiently high-quality to produce the kinds of insights managers are expecting. This is particularly true in the emerging field of talent analytics, where companies are making major investments but most aren’t seeing them pay off.
In addition to the data quality challenge, Data Quality Solutions President Thomas C. Redman suggested in a recent Harvard Business Review article that senior managers at many organizations are mismanaging their data scientists: placing them in the wrong part of the organization, not focusing the data science program on business outcomes, and not facilitating a transition to a more data-driven culture. He offers some suggestions for how companies can get more out of their data scientists:
First, think through how you want data scientists to contribute, and put them in spots where they can do so. The worst mistake a company can make is to hire a cadre of smart data scientists, provide them with access to the data, and turn them loose, expecting them to come up with something brilliant. Lacking focus and support, most fail. Instead, clearly define the opportunities you want to address using data science, and put your data scientists in places in the organization where they can best pursue those opportunities. …
In its annual survey on office romance, conducted in the lead-up to Valentine’s Day, CareerBuilder finds this year that the number of US employees saying they have dated a co-worker at a ten-year low of 36 percent, down from 41 percent last year and 40 percent in 2008:
Thirty-seven percent of men say they have dated a coworker compared to 35 percent of women, while one in five male workers (20 percent) say they have dated someone at work two or more times in their career, compared to just 15 percent of their female colleagues. …
Of those who have dated at work, more than a quarter of women (27 percent) say they have dated someone who was their boss compared to just 16 percent of men. Additionally, 30 percent of these workers say they have dated someone who was at a higher level in the organization than they were. Thirty-five percent of female coworkers reported dating someone at a higher level in the company than them, compared to 25 percent of their male coworkers.
The shift from a ten-year high in last year’s survey to a ten-year low this year may be related to the unprecedented attention finally being given to sexual harassment and misconduct in the workplace after countless women opened up about their experiences as part of the #MeToo movement over the past six months. Wider awareness of these problems and an increased focus on preventing harassment and punishing perpetrators have reportedly led to anxieties among men in the workplace about the propriety of their interactions with female colleagues, which would tend to result in fewer workplace romances being initiated.
In a breakout session at the ReimagineHR conference hosted by CEB (now Gartner) in London today, a group of several dozen HR leaders came together for a peer benchmarking session to compare notes and discuss common challenges in the field of talent analytics. The attendees at Wednesday’s session had a variety of roles, including some CHROs, some heads of employee experience, HR business partners or other leadership positions within the HR function: Just as in our peer benchmarking session last year, very few identified themselves by title as heads of talent analytics. The diversity of titles and roles in the room illustrates both the breadth of the impact talent analytics is having on the HR function and the fact that many organizations do not have a dedicated talent analytics team.
The discussion centered on several key themes in the sphere of talent analytics and the challenges attendees were facing at their organizations in bringing data analysis to bear on their talent strategies. Enabling the use of talent analytics, making the function more strategic, building analytic capability, and improving data quality were all areas of concern. These are some of the key challenges that came up in Wednesday’s discussion:
Aligning Talent Analytics to Critical Business Questions
Asked where they were primarily focusing their efforts to drive action in enabling the use of talent analytics, a plurality of attendees identified this as their main focus. Some attendees noted that they are gathering robust data but were still struggling to translate that data into actionable insights to solve business problems. Attendees at last year’s session shared the same frustration. To some extent, the degree to which data can be leveraged is a matter of the analytics function’s maturity. One component of solving this problem is ensuring that the data is “clean,” accurate, and helpful in making decisions: As one HR leader remarked, she is often presented with the data that is easiest to gather rather than the data that is most useful.
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At the Harvard Business Review recently, Emma Seppala and Marissa King discussed the causes and consequences of employee burnout and pointed to a strong correlation between burnout and loneliness:
In analyzing the General Social Survey of 2016, we found that, compared with roughly 20 years ago, people are twice as likely to report that they are always exhausted. Close to 50% of people say they are often or always exhausted due to work. This is a shockingly high statistic — and it’s a 32% increase from two decades ago. What’s more, there is a significant correlation between feeling lonely and work exhaustion: The more people are exhausted, the lonelier they feel. This loneliness is not a result of social isolation, as you might think, but rather is due to the emotional exhaustion of workplace burnout. …
In fact, research has demonstrated the link between social support at work, lower rates of burnout, and greater work satisfaction and productivity. After all, the most important factor in work happiness, a UK study showed, is positive social relationships with coworkers. Workplace engagement is associated with positive social relations that involve feeling valued, supported, respected, and secure.
To help build those positive social relations, Seppala and King recommend that employers promote a culture of inclusion and empathy, encourage employees to build developmental networks, and celebrate group successes. This is easier said than done, however, especially with employees that work remotely or away from the central or corporate office, so the big question that comes to mind is how to achieve this while also having a flexible, partly or fully remote workforce.
Two of the most important trends in HR today are the growing importance of technology within the HR function and its increasingly strategic role within the organization. In fact, a new survey from Paychex finds that these trends are closely linked, Nick Otto reports at Employee Benefit News:
According to the inaugural Paychex Pulse of HR Survey, more than two-thirds of HR leaders at small and mid-sized companies say they have grown beyond serving a traditional administrative function to taking on a more strategic role within their respective organizations. And technology is helping to drive that shift. A growing number of HR leaders (41%) are meeting with their CEO or CFO — or both — on a weekly basis, according to the survey, while close to one-third have access to top management when they need it.
Three-quarters of respondents said that HR technology has enabled them to become more strategic and efficient on the job. In addition, 60% of respondents considered their HR technology to be very effective for payroll, retirement and benefits administration, and time and attendance tracking, indicating they feel that technology is allowing them to maximize their effectiveness when it comes to the administration of critical business functions.
These findings are great news for HR leaders, and not at all surprising; new technologies are driving innovation and disruption in every facet of the working world, and HR is no exception. Technology is a key factor driving the increasing pace of change, which challenges HR to keep the workforce aligned. Furthermore, with digital talent playing an ever more important role in shaping the organizations of the future, a strategy-focused HR function is a vital parter in preparing any organization for a digital transformation.
At the Harvard Business Review, John Boudreau, a research director at the Marshall School of Business and Center for Effective Organizations at USC, highlights the fundamental challenge most HR functions have when it comes to analytics: They are making significant investments, but not getting returns from those investments. The work that we are doing at CEB (now Gartner) has found the same result: More than 70 percent of organizations are increasing investments in talent analytics, but only 12 percent feel like they are getting results.
Boudreau offers up a set of push and pull strategies to improve the effectiveness of talent analytics by making it more “user friendly.” Looking at the pull situation, he lays out the following conditions, which he argues must be present for an analytics program to succeed. The HR function, he writes, must:
- receive the analytics at the right time and in the right context,
- attend to the analytics and believe that the analytics have value and that they are capable of using them,
- believe the analytics results are credible and likely to represent their “real world,”
- perceive that the impact of the analytics will be large and compelling enough to justify their time and attention, and
- understand that the analytics have specific implications for improving their own decisions and actions.
While it’s certainly helpful advice to invest time, energy, and thought into how the consumer of that information will use it, there is still a fundamental problem—alluded to in the third item above—that heads of talent analytics must tackle first, and that’s improving data quality. In fact, poor data quality is the number-one cited reason why talent analytics leaders feel that they aren’t having the impact that they want.
Across the last few years there has been a massive rush by most organizations to make significant investments in talent analytics—in fact, in a recent survey we conducted at Gartner, 74 percent of organizations said they were planning on increasing their investments in talent analytics in the next year.
While there certainly is great potential in the use of talent analytics, Wharton management professor Peter Cappelli argues in the Harvard Business Review that companies shouldn’t simply be throwing money at it with the hope that something good happens. Most HR functions, Cappelli points out, don’t have enough high-quality data to justify a sophisticated analytics project:
As with most of “the next big thing” stories in business, big data is really important in some areas, and not so important in others. As a literal definition, HR does not actually have big data, or more precisely, almost never does. Most companies have thousands of employees, not millions, and the observations on those employees are still for the most part annual. In a company of this size, there is almost no reason for HR to use the special software and tools associated with big data.