Diversity, new interviewing tools, data, and artificial intelligence are the four trends set to have the biggest impact on recruiting in the coming year, according to LinkedIn’s latest Global Recruiting Trends report. Based on a survey of over 9,000 talent leaders and hiring managers worldwide, along with a series of expert interviews, the report underscores the growing role of technology in shaping how companies meet their hiring goals, of which diversity is increasingly paramount. Nonetheless, while many HR leaders see these trends as important, the number of organizations fully acting on them lags far behind.
Diversity was the top trend by far, with 78 percent of respondents saying it was very or extremely important, though only 53 percent said their organizations had mostly or completely adopted diversity-oriented recruiting. In recent years, diversity has evolved from a compliance issue to a major driver of culture and performance, as more and more organizations recognize its bottom-line value. This shift was reflected in the LinkedIn report, with 62 percent of the companies surveyed saying they believed boosting diversity would have a positive impact on financial performance and 78 percent saying they were pursuing it to improve their culture. Additionally, 49 percent are looking to ensure that their workforce better reflects the diversity of their customer base.
Diversity was the only top trend identified in LinkedIn’s survey that wasn’t directly related to technology, but technology is definitely influencing how organizations are pursuing it. In the past year, we have seen the emergence of new software and tools to support diversity and inclusion. The aim of these tools is to remove the human error of unconscious bias from the recruiting process, but it’s important to be aware that automated processes can also develop built-in biases and end up replicating the very problem they are meant to solve. This is an issue we’ve been following in our research at CEB, now Gartner; CEB Diversity and Inclusion Leadership Council members can read more of our insights on algorithmic bias here.
The development of new interview tools and techniques was identified as the second most important trend, with 56 percent saying it was important. The LinkedIn survey found that the most common areas where traditional interviews fail are assessing candidates’ soft skills (63 percent), understanding candidates’ weaknesses (57 percent), the biases of interviewers (42 percent), and the process taking too long (36 percent). The report highlights five new interviewing techniques, all enabled by technology, that aim to address these problems:
“Digital solutions ninja” may sound like a more exciting job than “tech support,” but do quirky job titles like these attract or repel candidates? Fast Company’s Lydia Dishman highlights some research that suggests the latter:
According to jobs platform Indeed, the top five are genius, guru, rockstar, wizard, and ninja. The winning titles were identified as the most common “weird job titles” as calculated by the share of postings containing them over the last two years. Rockstar, in particular, has grown in frequency by 19%, followed closely by guru, although the latter has lost some steam as it’s declined by 21%. Ninja itself is experiencing a slow assassination, declining by 35% since its peak in March 2017. But does the quirkiness really result in surfacing qualified candidates?
Paul Wolfe, senior vice president of HR at Indeed, thinks they just serve to confuse people. “When you do your [job] search,” he contends, “you’re not going to put ninja” in the search box. “Companies use these to express what their culture is like,” Wolfe concedes, “but there are other ways to get that point out.” Career pages on a website that contain videos, photos, and other descriptions of what it’s like to work at the company are a better vehicle than a cutesy title.
A 2016 survey by Spherion came to a similar conclusion about these too-clever-by-half job titles, finding that many employees consider them unprofessional and not descriptive of what they actually do. Even more ordinary titles like “specialist” or “project manager” are often seen as too generic.
According to a recent study by the Perception Institute, one in five black women feel social pressure to straighten their hair for work, and though all women worry about about how their hair is perceived, black women are much more likely to feel anxiety over the issue than white women are. That anxiety is apparently warranted: the Perception Institute also found that, irrespective of race, the majority of the more than 4,000 people who participated in the study demonstrated an implicit bias against black women’s (naturally) textured hair, rating it less professional than smoother hair. As the study concludes, be it overall perceptions of professionalism, first impressions during an interview, or general ideas about health and beauty, “attitudes toward black women’s hair can shape opportunities in these contexts, and innumerable others.”
Bias against black women’s textured hair can play out in a number of ways in the workplace, from everyday cultural slights and comments regarding these women’s hairstyles, to more concrete challenges such as misguided hiring decisions. And while banter in the break room surrounding a black colleague’s new hairstyle may seem like an otherwise innocuous conversation point, it may actually contribute to, or be a symptom of, a workplace culture in which black women are professionally judged over their hair.
High-potential employees, or HIPOs, are supposed to be an organization’s future. However, correctly identifying which employees have the most potential is often a difficult task, due to ambiguity surrounding the term HIPO and the fact that most managers don’t seem to believe their organizations’ criteria for high potential are accurate. Moreover, HIPO selection is easily “politicized”: In a recent Harvard Business Review post, Tomas Chamorro-Premuzic and Abhijit Bhaduri discussed six ways managers often play politics in identifying, promoting, and developing HIPOs, namely the politics of intuition, self-interest, avoidance, favoritism, ageism, and gender:
In short, the politics of potential can prevent organizations from upgrading their leadership talent and make data-driven decisions an anomaly rather than the norm. Too many times we have seen the CEO’s favorite candidate be put through a formal assessment simply as a way of confirming a decision that has already been made in advance, not for merit.
Our research at CEB, now Gartner, has touched on all of these political dynamics, and fortunately we’ve found some straightforward and practical solutions to the problems identified here. Organizations using best practices are ensuring their HIPOs are managed as enterprise assets and not held captive to the whims of a manager. Here are some real-world examples of how organizations are overcoming the six political barriers Chamorro-Premuzic and Bhaduri identify (and CEB Corporate Leadership Council members can click through the below links for more information on our research):
The politics of intuition occurs when managers “follow their gut” when nominating HIPOs based on their own judgement of employee performance and future capability. Instead, all managers within an organization should have standardized, clear, and business-relevant criteria to identify HIPOs. CEB recommends evaluating employees for potential against three key characteristics: Ability, aspiration, and engagement. Critically, managers need to be involved in validating the details of these criteria to ensure that HIPO they are not an abstract HR concept. Our recent study on high-potential employees shared a real-world practice Black Hills Corporation uses to align HIPO identification to changing business needs, in order to identify the best HIPOs to fill emerging leadership opportunities.
One of the key takeaways from the diversity reports US tech companies have been putting out over the past few years is that it’s one thing to recruit more women and underrepresented minorities, but quite another to retain them, develop them, and enable them to succeed in your organization. That’s why companies like Intel have been exploring ways to help these employees address the obstacles that might otherwise compel them to quit.
GoDaddy has chosen to focus its diversity and inclusion efforts on another specific challenge: the promotion gap between men and women. The company’s latest diversity report shows that its ratios of women in the overall workforce and in leadership roles both increased modestly in the past year, but CEO Blake Irving tells Fortune’s Valentina Zarya that the numbers don’t tell the whole story about how GoDaddy is working to improve women’s promotion trajectories:
Irving’s team noticed that women were not getting promoted at the same rates as men (a phenomenon that is not unique to GoDaddy). At that time, promotions happened on an ad hoc basis, with employees who felt they were qualified raising their hands for open jobs. Yet, because men tend to believe they are qualified for jobs much more readily than women do—remember the statistic that men apply for a job when they meet 60% of qualifications, but women apply only if they meet 100%?—more men were asking to be promoted (and hence being promoted) than women.
Organizational culture is critical to business outcomes and more than 80 percent of organizations hire specifically for culture fit. Seeing an opportunity here, tech startup Bunch wants to help companies bring more analytic rigor into how hiring managers assess job candidates for culture fit. Steve O’Hear recently profiled the startup at TechCrunch:
Specifically, by mapping company culture data against that provided by a job applicant, the idea, Bunch founder and CEO Darja Gutnick tells me, is to be able to highlight any potential cultural fit issues that can be teased out during a subsequent interview…
The way Bunch works is as follows: A company signs to the Saas and its teams take a 5-minute culture assessment, based on the O’Reilly model. Then, using the data provided, Bunch creates a culture profile for the company and each of its teams, mapped onto 6 key dimensions: Results-orientation, Adaptability, Collaborative, Detail-orientation, Principles and Customer-orientation. Every new applicant is tasked with taking an automated culture quiz that Bunch checks against the team and company profile.
Bunch’s push to put a quantitative lens on hiring for culture fit is well-intentioned. Taking a more “gut feel” approach to culture fit, as many managers currently do, can open up the organization to unconscious biases that threaten workforce diversity. There’s just one problem: Hiring for cultural fit is both more difficult and less effective than Bunch’s platform makes it look. Beyond the significant issue of bias, our research at CEB (now Gartner) shows that common strategies to change or strengthen culture by bringing in certain types of people don’t usually work.
Here are three main reasons why tools like Bunch’s are unlikely to produce the results organizations are looking for:
Numerous technological tools are promising to automate recruiting with the added bonus of helping to eliminate bias from the candidate sourcing and hiring process by using artificial rather than human intelligence to make hiring decisions. AI projects like the Mya chatbot or Project Manager Tara, along with more established companies like Atlassian, SAP, and Hirevue are optimistic that their technology can remove bias, but, as Simon Chandler of Wired points out, “AI is only as good as the data that powers it,” and right now that data is filled with flaws.
There is a great risk in training algorithms with human-generated data because it could program them with the same biases they are hoping to correct. If an algorithm screens applicants based on the traits and characteristics of a company’s current high-performers, the end result will simply be an automated version of the existing biases in the recruiting process. The Atlantic profiled an illustrative example of this where tech startup Gild created a software that helped companies find programming talent. The software collected a lot of publicly-available information to determine a candidate’s likelihood for success, but some of the variables, such as an affinity for a specific website frequented by men, instilled a bias into their rankings. Though it was an indicator of success, using fans of that website as a predictive measure unfairly penalized women.
Our Diversity and Inclusion research team at CEB (now Gartner) has been looking into this challenge of algorithmic bias. Our position, which CEB Diversity and Inclusion Leadership Council members can read in full here, is that the burden of removing this bias is on the people developing the technology, not the end users on the recruiting team.