Data-driven HR: people analytics is your #1 tool for getting organization-specific insights

Over the past decade, big data processing has been making its way into the full spectrum of all business operations units, including human resources. Data insights have been vastly praised in the media and have proved to be valuable in many business cases. And yet just a short time ago people analytics was still the province of only a few pioneering companies.

The data-driven shift, however, has become more evident recently, since data volumes and advanced technology have both grown drastically. Nowadays more and more HR officers are deploying predictive models via data-analyzing software. These algorithms deliver helpful and sometimes counterintuitive insights for identifying, recruiting and retaining the best staff.

People analytics is a new era HR weapon

Deloitte’s 2018 Global Human Capital Trends survey reveals that 84% of respondents treat people analytics as an ‘extremely important’ tool, ranking it second on the list of HR trends to follow in the near future. While a few enterprises are still at the “exploratory” level of analytics adoption, many others are stepping up from basic reporting to analysis of bigger data samples.

In 2018, Oracle report discovered that HR departments use analytics more than any other vertical, surpassing even finance, where data analysis usually guides the way. There are plenty of reasons behind this: according to McKinsey, people analytics may bring an increase of up to 25% in business productivity and a 50% decrease in attrition rates.

Advanced algorithms as practical HR solutions

So how can people analytics actually benefit your HR practice?

• Firstly, it can help with eliminating unconscious bias from the recruiting process. Cutting-edge fact-based technologies nowadays are capable of identifying people with the skills that really match the role. Therefore, it empowers objectivity rather than gut feeling. People analytics can also go through the existing company data and set diversity goals for future employee selection, since algorithms are able to pre-select the non-standard profiles that nonetheless have an expertise close enough to that of the high performers. Software can also aid with comprehending which on-boarding techniques demonstrate a pattern of higher retention. Furthermore, the algorithms predict which new hires are likely to succeed, based on assessing their cultural fit, experience, and particular skills.

• Technology is also of great help if you work on a benefits and compensations policy. Often companies don’t realize how unequal their compensation levels are. These remuneration discrepancies may profoundly upset employees and cause high levels of attrition. This is where data analytics comes in: software provides the insights on the current pay levels and identifies the optimal minimum and maximum compensation rates. Covering salary gaps is a great solution for increasing employee engagement, reducing attrition rates, and boosting overall staff productivity.

• Predictive analysis is widely used to modify the training offering and to estimate investments in reskilling. Based on employees’ professional paths, skillsets and educational backgrounds, predictive analytics engines target the employees that are suitable for the required competencies upskilling. This data application is hugely important for developing a well-defined L&D policy, improving a company’s bottom line, and contributing to employee engagement.

• Moreover, being able to detect previously unseen behavioral patterns, advanced analytics has a myriad of other HR applications: turnover rates interpretation, human capital risk analysis, the search for solutions to absenteeism, and performance and productivity fine-tuning.

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