Predictive analytics – looking to the future in recruitment

Predictive analytics, the use of big data to predict future trends and help make decisions, is fast becoming a mainstay of management decision making. And rightly so – a study by Meehl and Grove found that, in all of 136 studies examined, predictive analytics beat managerial intuition.

Predictive analytics takes existing data and, instead of just seeing the face value of patterns, uses algorithms to look deeper into its meaning. It combines data sets, looks for underlying patterns, and so allows accurate predictions about future needs and future performance. Adopted by big players like Google, it looks set to dominate business analysis over the next few years.

Much as HR consultants might like to think in terms of qualitative data and the soft human touch, the need for predictive analytics applies as much to HR as to any other field. So how is this approach applied, and what are its benefits?

Predictive analytics in HR

One of the biggest areas where predictive analytics can be applied is in recruitment. Most of the metrics currently used in this area report not what will happen in the future but what happened in previous years. They show what a company’s growth pattern has previously been, what their seasonal staffing needs were like in the past, which areas of the business have historically had high turn-over.

Similarly, in choosing individual recruits, past performance has been used as an indicator of likely success. But a great middle manager might not do well at a senior level. Looking at historical performance is of limited use.

As long as we keep looking into the past and expecting more of the same, we will find ourselves ambushed by unexpected developments. Predictive analytics focuses on understanding what is about to happen, so that we know what is coming and can act in time to achieve optimal performance, not manage the next crisis.

What can it do?

In HR, predictive analytics is used to look for patterns in performance, employee turnover, training needs and career progression. It can determine the likelihood of particular types of employee leaving, or the set of competencies and skills that will create the best fit for a position. It can foresee future training and recruitment needs. It can even help identify where dissatisfaction is likely to arise, and so help with staff retention.

But what it can do is constantly growing.  An increase in the available data and computing power makes all of this more effective as time goes by. By looking at the big picture, it can allow firms to see the challenges that are coming their way, the workforce they will need to meet those needs, and the metrics that will best allow them to identify recruits for that workforce. Labor opportunities might also be predicted, seeing when there will be a glut of programmers available to hire or a shortage of technical artists that you should prepare for.

Why now?

The growth in computing power and available data has made predictive analytics possible. But as with many cutting edge approaches, it’s its adoption by competitors that makes it vital. Organizations using predictive analytics will gain an edge over those who don’t, and no company can afford to be left behind.

If you would like to read the remaining articles in this series (eight articles) please follow the links below (link to Method3 website).

Article 1: Predictive analytics – looking to the future in recruitment
Article 2: Predictive analytics in HR – looking at the big picture
Article 3: Predictive analytics in HR – smarter recruitment
Article 4: Predictive analytics in HR – training and development
Article 5: Predictive analytics in HR – retention
Article 6: Predictive analytics in HR – getting it right
Article 7: Predictive analytics in HR – barriers to deployment
Article 8: Predictive analytics in HR – the future

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