In the field of human resources, predictive analytics is a growing trend. High-performing employees are predicted by recruitment tools, and firms are increasingly able to forecast which employees are likely to depart. We will discuss what HR predictive analytics are and how they may be a game-changer for HR departments in this article.

Human Resources Predictive Analytics: How Does It Work?

Predictive data analytics can be seen everywhere. It is, at its core, a technology that learns from previous data and forecasts individual behavior. As a result, forecasts are extremely precise. 

So, how exactly do these predictive analytics function? Predictive analytics is a collection of statistical (data mining) approaches for analyzing past data and results. These methods then attempt to develop a formula, or algorithm, that most closely resembles these past outcomes. This program then uses current data to forecast future events.

Human Resources Predictive Analytics In Action

Let’s pretend you live near a playground. You’ve been keeping track of whether or not there were children on the playground for the past two weeks. You also noted if the weather was sunny, wet, or cloudy, as well as the temperature and humidity. Would you be able to forecast whether or not kids would be playing on the playground on a given day based on the data you collected?

This is a difficult question to answer. Obviously, the weather has an impact on whether or not children choose to play outside. If the weather forecast calls for rain, it will almost certainly rain, which means that children will be less inclined to play outside. When it’s hot outside, kids are more likely to play outside.

But do you have enough data in your spreadsheet from fourteen consecutive days to make an accurate prediction about whether or not kids will play outside?

Using a Decision Tree To Make Predictions

The decision tree is a frequent and very basic approach to generating a predictive model. A decision tree is a tree-like construct that contains decisions and their potential outcomes. Every node in the decision tree represents a test on a specific property, and each branch represents the test’s various outcomes.

How Might Human Resources Predictive Analytics Be Used In Practice?

What role does predictive analytics play in HR now? HR has a lot of information about people, which is normally stored in a Human Resources Information System. HR may become a strategic partner who depends on established and data-driven predictive models rather than subjective opinion and soft science by applying predictive analysis to this data. Human resources predictive analytics allows HR to foresee the impact of people policies on employee well-being, satisfaction, and bottom-line results. The role it can play in minimizing costly staff turnover is one example.
Only a few firms, however, are capable of developing HR predictive models. Only 17 percent of firms worldwide had access to and used HR data, according to Deloitte’s 2018 People Analytics Maturity Model.

This is an increase from 8% in 2015 and 4% in 2014.
Only 2% of the 17 percent in 2018 qualified as having business-integrated data, which means they collect, integrate, and analyze data in real-time using advanced AI-aided tools. The remaining 15% is able to perform campaign-based predictive analytics.

As a result, many businesses still have a long way to go before they can use predictive people analytics. Regardless, early adopters have already produced some intriguing results. Let’s check some of them more closely.

1. Predicting Hire Success At Google

Laszlo Bock, Google’s Senior Vice President of People Operations (HRM), states in his book that statistics is the most significant tool in Google’s People Operations. In Google’s hiring process, all of the interview questions are totally automated, computer-generated, and fine-tuned in order to select the best candidate.

Furthermore, Google uses HR predictive research to assess the likelihood of employees leaving the organization. Google discovered that new salespeople who do not receive a promotion within four years are substantially more likely to quit the organization.

You should keep track of a variety of other key metrics in recruiting to check if you’re hiring the correct personnel. Advanced indicators such as time to productivity and the cost of reaching peak production are among them.

That’s one of the reasons company culture at Google is often talked about.

2. Using Engagement Data To Forecast Revenue

Employee engagement is commonly considered as HR’s holy grail. Employees who are engaged work harder, produce higher-quality work, are less absent, and are less likely to leave.

Best Buy, an electronics retailer, sought to determine how customer engagement affected store revenue. They discovered that a 0.1 percentage point boost in interaction leads to a $100,000 increase in sales per store after analyzing their data.

Best Buy chose to monitor engagement numerous times a year after discovering this incredible impact. This also allowed them to track the factors that influence engagement. This supported the development of HR interventions that would boost employee engagement and, as a result, store revenue.

3. Using Facebook To Make Better Hiring Decisions

Do your recruiters look at applicants’ Facebook pages? Perhaps they should. According to a study, a person’s personality and future work performance can be predicted based on their Facebook page. A number of participants in this study submitted hirability evaluations based on their Facebook accounts. These evaluations predicted 8% of these people’s manager-rated work performance.

It may not appear to be much, but 8% is a significant amount. When compared to looking at someone’s Facebook profile, a normal personality test offers a better predictive value for performance. The literature, on the other hand, repeatedly reveals that the best prediction models for future work performance integrate many variables such as IQ tests, structured interviews, and personality tests.

Examining a Facebook page could be another way of checking prospects.

4. Never Hire Toxic Employees

Employees who are more inclined to participate in toxic behavior are referred to as toxic employees. Fraud, drug or alcohol abuse and sexual harassment are examples of these behaviors.

These individuals are not only harmful to the organization, but also to the overall work atmosphere. According to a previous study, just one toxic individual in a team can reduce productivity by 30 to 40 percent. Furthermore, when good individuals are forced to work with toxic coworkers, they are more likely to leave.

With the help of a dataset of 63,000 employees the organization  identified which employees were involuntarily fired due to workplace aggression, document falsification, drug, and alcohol misuse, and other policy infractions in this dataset. Using these criteria, around 4% of all employees may be categorized as ‘toxic.’
Cornerstone found a number of important features of toxic personalities after reviewing the data.

Toxic people are:
1. self-described rule-followers
2. have low attendance and dependability
3. don’t consider themselves a bad performers and don’t have a will to improve and change the approach

Surprisingly, the study found no evidence of the previously reported high levels of short-term productivity loss. It did, however, discover that harmful behavior is contagious. People who work with toxic coworkers are more likely to leave their jobs.

Toxic coworkers, according to the study, contribute to long-term stress and burnout among other employees.

In the end, Cornerstone demonstrated that recruiting a toxic employee costs an average of $12,800 vs $4,000 for a non-toxic person. This does not account for the long-term (and costly) loss of production due to burnout and other undesirable consequences. Companies may avoid employing toxic people by fine-tuning their hiring process, resulting in a healthier working environment.

Predictive Analytics: A Game-Changer In HR

The effects of using predictive people analytics can be remarkable, as these past examples demonstrate. HR departments have the power to save (or earn) millions of dollars for their companies. HR may also assist managers and executives in making better decisions by utilizing predictive analytics and the appropriate HR indicators.

These business cases (and other HR analytics case studies) highlight the potential of predictive analytics, indicating that predictive HR analytics are here to stay. They’re the game-changer, allowing HR to not only assess how workers perform but also predict and maximize the impact of people policies on both employees and the company.

Also read:
How To Help Your Employees Succeed
Behavioral Observation Scale: How Does It Work?