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.”

    Online Recruiting Market Set to Heat Up in 2019 as Key Players Expand

    Online Recruiting Market Set to Heat Up in 2019 as Key Players Expand

    The marketplace of online recruiting platforms has become increasingly competitive over the past few years, as both big tech companies and startups alike have sought to establish themselves as the platform of choice for both candidates and employers. This week brought news that three of the most-watched competitors in this field are growing, adding new features, or expanding their geographical reach.

    LinkedIn announced on Tuesday that it was moving all of its core talent solutions — Jobs, Recruiter, and Pipeline Builder — onto one platform, which it calls the intelligent hiring experience. This consolidation will enable recruiters to “to see all their candidates … in one unified pipeline,” no matter which of these three tools they came from, John Jersin, VP of Product Management at LinkedIn Talent Solutions, explained in a blog post on Tuesday. The company is also “releasing more than 15 new product enhancements for LinkedIn Recruiter and Jobs over the next few quarters,” Jersin added.

    In addition to the single pipeline, LinkedIn’s new features include new AI capabilities, which will enable its tools “to talk to one another and leverage machine learning to simplify the hiring process”:

    The more you interact with candidates within a project, the more our tools learn about what you like — and don’t like — and then we can surface better candidates for your open role. Based on the applicants, leads, and search results you interact with, the intelligent hiring experience automatically builds a list of recommended candidates for you to consider reaching out to.

    The platform is also adding a shared messaging system that will show all candidate communications in one place, a slide-in profile view to more easily look at candidate profiles in the middle of a search, and a feature called “Closing the Loop,” which makes it easier for employers to send rejection messages to applicants, either individually or in bulk. This functionality is meant to address the lack of communication that adversely affects candidate experience and can discourage rejected candidates from applying to other jobs at the same organization for which they might be more qualified. LinkedIn’s mobile app is also getting a call-to-action feature that will enable anyone at an organization to quickly let their LinkedIn network know about a job opening there.

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    Amazon Abandoned AI Recruiting Tool After It Learned to Discriminate Against Women

    Amazon Abandoned AI Recruiting Tool After It Learned to Discriminate Against Women

    Amazon canceled a multi-year project to develop an experimental automated recruiting engine after the e-commerce giant’s machine learning team discovered that the system was exhibiting explicit bias against women, Reuters reports. The engine, which the team began building in 2014, used artificial intelligence to filter résumés and score candidates on a scale from one to five stars. Within a year of starting the project, however, it became clear that the algorithm was discriminating against female candidates when reviewing them for technical roles.

    Because the AI was taught to evaluate candidates based on patterns it found in ten years of résumés submitted to Amazon, most of which came from men, the system “taught itself that male candidates were preferable,” according to Reuters:

    It penalized resumes that included the word “women’s,” as in “women’s chess club captain.” And it downgraded graduates of two all-women’s colleges, according to people familiar with the matter. They did not specify the names of the schools. Amazon edited the programs to make them neutral to these particular terms. But that was no guarantee that the machines would not devise other ways of sorting candidates that could prove discriminatory, the people said.

    The company scuttled the project by the start of 2017 after executives lost faith in it. By that time, however, it may have already helped perpetuate gender bias in Amazon’s own hiring practices. The company told Reuters its recruiters never used the engine to evaluate candidates, but did not dispute claims from people familiar with the project that they had had looked at the recommendations it generated.

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    CareerBuilder Launches New Mobile App with AI and AR features

    CareerBuilder Launches New Mobile App with AI and AR features

    The job search website CareerBuilder has rolled out a new mobile app that uses artificial intelligence and augmented reality to help job seekers apply and employers find candidates more quickly and easily, VentureBeat reported last week:

    The mobile app has some attention-grabbing features. It can build your resume, apply to jobs on your behalf, and show augmented reality views of job openings at the businesses you walk by. It also helps you develop the skills needed for a better-paying job.

    And for [employers], the mobile app shows the real-time supply and demand trends for talent you need. It instantly builds your job descriptions, automatically matches your job openings to candidates who are more likely to respond, and runs campaigns to engage them.

    CareerBuilder’s mobile app is the latest in a series of new technological innovations search engines and job boards have unveiled in the past year to simplify and streamline the job search process and to provide prospective applicants with additional information about organizations and roles. Google’s built-in job search function was launched in the US last year and has since expanded to India, Canada, and the UK. The search giant has also developed new tools for recruiters, including an AI-powered candidate discovery feature and its Cloud Talent Solution product, which it made publicly available last month. Facebook has also added a dedicated job search functionality, which it has rolled out in 40 countries. The Japanese HR conglomerate Recruit Holdings, which owns Indeed, made a deal to acquire Glassdoor earlier this year.

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    HR Business Partners Aren’t Afraid of Technology Changing Their Role

    HR Business Partners Aren’t Afraid of Technology Changing Their Role

    According to Gartner research, the adoption of AI is poised to grow rapidly in the coming years. This and other emerging technologies like robotics are bound to fundamentally change the way we work, largely or completely automating many of today’s jobs. While this technological upheaval is generally expected to create more jobs than it destroys, the transition will be disruptive and challenging for many professionals accustomed to working in a pre-AI world. The most dire projections anticipate widespread displacement or the radical transformation of current jobs due to AI and robotics, potentially affecting tens of millions of workers in developed countries.

    The effects of automation will be challenging for the clients of many HR business partners, and HRBPs will be called to provide increasing support for those impacted, such as ensuring they have access to retraining opportunities. In addition, HRBPs see themselves as part of the population affected by automation: Ten years from now, HRBPs expect nearly half of their current day-to-day responsibilities to be automated. HRBPs are optimistic, however, about the impacts that technology and automation will have on their role. Our research at Gartner finds 68 percent of HRBPs agree that automation is an opportunity to prioritize strategic responsibilities. To capitalize on this opportunity, however, HRBPs need to anticipate what work will be automated and what work will be augmented.

    At a recent meeting with 70 HRBPs in New York City, we discussed predictions for the future of their role and asked them how technology has changed or will change it. Several attendees mentioned employee data collection: Previously, this was an onerous monthly or quarterly process of manually pulling together data from various sources to populate dashboards for stakeholders. Technology has made this process easier and quicker, with the use of pulse surveys and other tools. It also creates opportunities to collect data in larger quantities or more precisely, and to use it in new ways, though HR still has a lot of work to do in convincing the C-suite of the value of talent analytics.

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    Google Opens Up Its ‘Cloud Talent Solution’

    Google Opens Up Its ‘Cloud Talent Solution’

    After successfully piloting its AI-enhanced job search technology, Cloud Talent Solution, with select customers including Johnson & Johnson and CareerBuilder, Google made the product publicly available last week, VentureBeat reported:

    Cloud Talent Solution, which launched as Cloud Jobs API in 2016, is a development platform for job search workloads that factors in desired commute time, mode of transit, and other preferences in matching employers with job seekers. It also powers automated job alerts and saved search alerts. According to Google, CareerBuilder, which uses Cloud Talent Solution, saw a 15 percent lift in users who view jobs sent through alerts and 41 percent increase in “expression of interest” actions from those users.

    Alongside the public launch of Cloud Talent Solution, Google introduced a new feature to the toolset: profile search. It allows staffing agencies and enterprise hiring companies to, using natural phrases like “front-end engineer” or “mid-level manager,” sift quickly through databases of past candidates. Profile search is available today in private beta.

    Organizations can try Cloud Talent Solution out for free (pricing kicks in at over 10,000 queries per month) directly through the Google Cloud platform, or request access through one of Google’s talent acquisition technology provider partners.

    The public rollout of Cloud Talent Solution is another sign of Google’s extensive investment in AI and machine learning and the rapidly growing application of these technologies to talent acquisition and management. It is just one of several avenues through which Google is moving into the recruiting market.

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    VCs, Entrepreneurs See Midwestern Cities as Potential Startup Hubs

    VCs, Entrepreneurs See Midwestern Cities as Potential Startup Hubs

    Once the industrial base of the US, the Midwest has struggled in the high-tech era to capture the talent-driven growth enjoyed by coastal cities like Boston and San Francisco, but the region’s fortunes are changing fast. In the past year or so, a burgeoning Midwestern tech scene has begun attracting more attention from venture capitalists and Silicon Valley giants, with many local startups and big-company expansions focusing on the middle-skill roles for which the tech sector’s demand is insatiable, but that are still in short supply nationwide. These “mid-tech” or “new-collar” jobs are described as a 21st century analog to the factory jobs of the past—and as such, a promising path to revival for the industrial Midwest.

    High-tech industries including major international firms have been making some big bets in the region: The Indian IT services and business process outsourcing giant Infosys is planning a sprawling campus near Indianapolis, which aims to create 3,000 new jobs within five years, while the Taiwanese multinational Foxconn Technology Group made a deal with the Wisconsin state government last year to build a display panel factory there, which will see the company invest as much as $10 billion and hire as many as 13,000 people. Several midwestern cities are on the list of finalists in the competition to host Amazon’s second headquarters, though Detroit, for example, didn’t make the cut, partly due to a lack of readily available talent.

    Yet “mid-tech” companies and regional outposts of tech giants are just one side of the Midwest’s high-tech renaissance. Over the weekend, VentureBeat reporter Anna Hensel took a look at the growing community of AI and machine learning startups in the heartland:

    “The real benefit of artificial intelligence is the application to traditional problems and products that the world needs, and the really successful companies have that domain knowledge that they can understand how to apply this technology,” [Chris Olsen, a partner at Columbus, Ohio VC firm Drive Capital,] told VentureBeat in a phone interview. “We see more of those domain experts in these industries [with] massive chunks of GDP that exist here in the Midwest.”

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