Imagine if you could leverage your own internal data, as well as data available from third-party sources, to predict:
- Candidates for a specific job posting who are most likely to succeed in that position.
- Who are the top executives most likely to jump ship in the near future?
- What performance of high-potential employees could deteriorate.
- The impact that employee demographics will have on revenue over the coming months.
- Which departments are likely to experience above average turnover.
All of these things and more are now possible. In fact, companies are already leveraging data to produce this type of critical insight into future HR trends.
Predictive Analytics in Action
Dave Millner is the founder and consulting partner of HR Curator and co-author of Introduction to People Analytics: A Practical Guide to Data-Driven HR (Kogan page; 2nd edition, 2023). It provides an example of how a UK company used predictive analytics to improve their business performance by analyzing performance management data and performance trends.
The main questions explored were:
- What determines the critical success metrics for the business?
- How do business-critical roles impact these key metrics?
- What is the difference between the top 10 percent and the top performers?
The analysis resulted in the identification of personality traits that were more predictive of higher performance. This information was used to create a refocused recruitment process emphasizing the identified characteristics.
“The biggest reason to use data, some with AI platforms, is to make better people decisions,” Millner said. “This allows for a more objective assessment of talent potential, as well as personalized development, so that ultimately the organization can identify methods, processes and techniques that improve the quality, performance and engagement of Workforce.
Powered by increasingly powerful technologies like artificial intelligence and machine learning (ML), HR professionals are using predictive analytics in a more strategic and integrated way to gain insights on an ongoing basis.
Go further with predictive analytics
Firstup, a San Francisco-based intelligent workplace communications platform, uses its own communications platform to visualize and collect employee engagement data in real-time, then automates and orchestrates personalized communications through a template advanced machine learning.
“While many organizations gather information about their employee experience from sources such as (human resources information) systems or annual engagement surveys, this data is often not sufficient,” said Sabra Sciolaro, Director of Human Resources at Firstup.
“By relying solely on performance reviews or infrequent check-ins from your manager, you’re missing crucial signals about an employee’s experience at every touchpoint throughout their journey, whether they’re big or small, who really matters to him. » She says a deeper understanding of the key moments that impact the employee experience through AI and ML enables immediate action to improve those experiences in the moment.
Ed Barry, national director of the human resources benefits technology practice at Gallagher, an insurance, risk management and consulting firm headquartered in Rolling Meadows, Illinois, believes that “one One of the best uses of predictive analytics is to help employers make the connection between employee behavior and retention or attrition. For example, he said, it is possible to link different types of data to employee dissatisfaction and low engagement, including time and attendance, compensation, commute time and what employees think about their work.
Additionally, Barry said, predictive analytics algorithms can perform sentiment analysis, analyzing business emails for changes in sentiment such as increased frustration, anger or boredom. “While it is easy to ignore a single factor, when multiple factors are combined, predictive analytics provides high accuracy rates for predicting an employee’s future loss, giving the employer a chance to intervene and modify the planned action plan,” he said. However, he noted: “By itself, predictive analytics will not improve employee satisfaction. » Once an organization has identified that an employee is at risk, human intervention is necessary.
Staying at the cutting edge of technology
Technology, of course, plays a vital role in using predictive analytics to gain insights throughout the employee lifecycle. But, while there are many predictive analytics tools on the market, Barry said that “in my experience, many employers are not aware of them.” He suggests HR leaders attend the annual SHRM Conference & Expo and other HR technology events to talk with vendors, watch demos and ask questions.
“Before long, every CHRO will have a predictive analytics dashboard as they must manage the ongoing competition for talent,” Barry said. “The only way to know what’s happening with your talent pipeline is to pay attention to the signals employees are sending. Predictive analytics can help HR managers read these signals.
Moving forward, Barry said, “the HR technology industry needs to move beyond predictive analytics to prescriptive analytics to help determine the best course of action. This is where true innovation will come from, connecting the insights identified by predictive analytics into a response that maximizes results and mitigates risk.
However, there will always be an important place for people, particularly in HR circles. “Organizations that use predictive analytics software without human involvement risk making poorly informed decisions that can be costly to the organization’s human strategy and brand,” Barry said.
Lin Grensing-Pophal is a freelance writer in Chippewa Falls, Wisconsin.
