Big data. The subject is inescapable and it’s changing the operations of almost every industry, from hospitality to healthcare to yes, HR. It’s why data scientist–the person that collects, organizes, analyzes and activates big data–is one of the hottest jobs of the moment. (Maybe you’re even recruiting for one right now!) Continuing advances in HR technology mean that HR data analytics are only going to get more useful, sophisticated and omnipresent. These articles shed some light on why HR data analytics are important and how organizations can use them to their best advantage.
“While every ATS out there, by definition, has some sort of resume database, looking at your candidate database as simply a tracking system misses the point. No matter how much your system sucks, there are almost always a ton of great leads and recruiting data simply waiting to be found. And it’s your job as a recruiter not only to continuously grow this database, but continue to mine it, too. These aren’t cold calls–they’re warm leads. Sure, not every resume sitting there in your database is going to be an amazing candidate or even placeable. Most are probably no longer actively looking for a new job or considering careers with your company. That’s cool. The more candidates you interact with, the more relationships you can build, the more notes you can take, the better. That’s the kind of networking that’s truly worth something. By shining a light on the black hole, you’ll never forget a candidate, and always have a pipeline of interested candidates worth engaging.”
Derek Zeller (@)/Recruiting Daily
“For startups and small businesses, manual processes may not seem that problematic. Because these enterprises must remain incredibly conscientious about their overhead costs, purchasing HR automation systems might not be a budgetary consideration. In reality, however, HR analytics software helps smaller businesses save critical funds by facilitating smarter hiring decisions, which bolster return on investment. And as these businesses grow, reliance on manual processes can create more problems than solutions. For companies with a substantial employee base, the troubles only increase.”
Len April (@)/Business 2 Community
“Once your project is up and running, work on building its visibility and impact to ensure its survival and success. The shrewdest way to do this is by identifying and going after a ‘quick win’ within the first 30 days, advises Kieran Colville, a consultant at IBM. The ideal situation is one in which HR data can make an immediate difference while also delivering long-term cost or time savings. ‘Focus on identifying and cleaning HR data relating to critical job families that are disproportionately impacting your chief executive’s key performance indicators (KPIs),’ says Colville. ‘This shrinks the effort needed and fast-tracks your analytics project by showing immediate benefits for the boardroom.'”
Michael Carty (@)/Personnel Today
“The right HR leader can play a vital role in enabling workforce analytics initiatives. Effective sponsorship will ensure that an analytics initiative has the support required to succeed, the resources both people and technology–to be impactful, the support to create & communicate a clear, compelling vision, and the leeway to focus its attention on key business challenges or issues. Conversely, the wrong HR leader can help to kill a talent analytics initiative before its first breath. With the best of intentions, a misguided leader will–intentionally or not–engage in behaviors that virtually guarantee the failure (or significantly impeded the traction) of future workforce analytics initiatives.”
Mark Berry (@)/HR Examiner
“Talent teams today are under pressure to improve retention, especially as the economy improves and baby boomers begin to retire. Recruiting teams want to improve hiring decisions, knowing that a bad decision can cost as much as 5x the annual salary of that employee or more to correct. Training teams want to measure not just attendance and scores of their programs, but correlate that data with performance to understand the real impact of those programs. Despite this, HR teams often struggle with analytics. In fact, according to a recent Deloitte study, 75 percent of HR leaders believe that using analytics in HR is ‘important,’ but only 8 percent believe their organization is ‘strong’ in this area–making it the second largest capability gap for organizations, trailing only the need to build better leadership.”
Rocky Mitarai (@)/Business 2 Community
“A key differentiator in HR analytics is moving from collecting data to producing knowledge that brings insight and informs action. Many organizations collect and present HR metrics such as data that provides information such as turnover rates and associated costs, employee engagement scores and the retention rates of high performers. However, what’s missing is using that data to answer business questions. Querying the data using analytical studies can show trends, impact on current results and predictions of future impact. This insight can enable business leaders to make informed decisions regarding human capital, just as they use data analysis to make financial and other business decisions.”
“The implications of a sociometrically quantified organization are profound. It’s a given that the hierarchical org chart-as-we-know-it doesn’t begin to describe who’s really working together, and how effectively. Hidden in the spaces between reporting lines are informal peer networks that typically manifest themselves in office politics. Efforts to identify, recognize, and promote these networks range from communities of practice 15 years ago to the current fascination with holacracy. With sociometric badges, these ‘invisible colleges’ are plain to see—at least for management, who can scramble to repair fraying ties.”
Greg Lindsay (@)/Fast Company Co.Exist
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