Evidence-Based HR

Forecasting The Future

Using predictive analytics instead of past statistics for HR decisions creates business benefits.

By Michael Beygelman

Meaningful HR analytics speed the data-to-action cycle, reducing the traditional time lag to realize business benefits by helping companies “Identify, Intervene, and Intercept” – let’s call this I3. However, according to SAS, a pioneer in statistical analysis systems, “Predictive analytics is the use of data, statistical algorithms and machine-learning techniques to identify the likelihood of future outcomes based on historical data.”

If this sounds confusing, you are not alone! Predictive analytics has become a catch-all for vendors and HR buyers alike, given its meteoric rise in its prominence. However, in reality, predictive analytics goes beyond descriptive statistics and reporting by helping companies make evidence-based recruiting and talent-related decisions.Here is a handful of practical examples of implementing predictive analytics and the business benefits.

Effectiveness of Talent Attraction Channels

Most companies have multi-pronged strategies for addressing their recruitment advertising and talent attraction channels, but not all channels are equally effective. Implementing predictive analytics to identify the most effective channels can help a company save money, which appeals to the company’s CFO. Even more importantly, this will help attract more relevant candidates and reduce time to fill open vacancies, which is a multiplier in terms of positive real-world business impact.

Success of New Hires

An IT analyst supporting HR at a top Wall Street firm recently shared one of their attempts at integrating predictive analytics into the recruitment process. This firm has defined a reference profile of a successful internal employee for every job description, and each new applicant is automatically benchmarked against the reference profile when they apply for the same job.

This predictive model scores the likelihood of the new applicant being a top performer in the new role based on the historical performance of the benchmark profile in the same role. Based on this score, the applicant is prioritized into the recruitment funnel. The net business benefit is that recruiters are talking first to the candidates recommended by the predictive model, and, so far, the results have been encouraging.

Employee Engagement

The reality is that most employee surveys are on the verge of becoming obsolete. Just how reliable is a self-reported survey anyway? Ask employees how they feel about their company or their boss a week before performance bonuses are to be paid, and you will get a fluorescent green scorecard. Ask the same question a month later and you will get a very different answer.

While self-reported surveys might produce really nice graphs and charts, or infographics, what actionable business value do they really create, and most importantly what do you do next? Measuring the intensity of employees’ job-seeking activities outside of your company is probably the single biggest proxy for engagement. If employees are looking for work outside of your company, clearly they are not engaged.

Absenteeism or Workplace Accident Likelihood

Historical data about absenteeism and workplaces accidents is readily available in most modern HRIS systems, so predicting absenteeism or the likelihood of accidents is almost the lowest hanging fruit, in terms of ease of implementing predictive analytics in the workplace. The benefits are dramatic cost savings, improved employee morale and productivity, and a safer working environment.

Contingent Workforce Utilization

Utilization of contingent workers has become a necessary business practice for most organizations, yet nearly all companies struggle with knowing the ideal timing or scenarios in which to deploy contingent labor or the right balance of their workforce blend. This is a business function that has mountains of data sitting in VMS and HRIS systems, which could be mined to train predictive models and provide procurement and operations leaders with actionable insights.

It’s important for organizations to differentiate between predictive analytics and the descriptive statistics and reporting on what happened in the past. Both offer their respective business benefits, but implementing predictive analytics provides organizations with a unique assessment on what might happen in the future. While the benefits of business reporting and descriptive statistics edify and educate organizational leaders on past successes and failures, the end result of predictive analytics is to streamline future decision making and produce new insights that lead to better actions.


Michael Beygelman is CEO of Joberate®, an HR analytics platform that helps companies make evidence-based recruiting and talentrelated decisions. He can be reached at michael@joberate.com.

Tags: April-2016

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