- The HR data analytics process empowers HR professionals to make data-driven decisions
- Predictive algorithms help organizations act before it's too late, such as proactively retaining top performers flagged as flight risks
- Combine data from various HR systems, such as coupling satisfaction survey scores with performance data, allows you to draw relationships between HR initiatives and business performance
Data is now the most valuable currency in the world. But in contrast to the murky ethics of sourcing and selling consumer-driven data, leveraging internal HR data analytics to make better workforce decisions has been a key Human Resources best practice for decades. As technology has improved, so has our ability to analyze employee-related factors and improve business outcomes.
But what exactly is HR data analytics and how can HR leverage it to achieve organizational goals?
HR Data Analytics Definition
While data and analytics are often used interchangeably, data is the source of information and analytics is the process of applying statistics, modeling, and analysis to make sense of the data’s insights. HR analytics may be referred to as people analytics, workforce analytics, or talent analytics depending on the context of the data.
HR professionals can gather data points from a wide variety of internal sources, including employee surveys, salary and promotion history, demographics, geographical locations, recruitment processes, and other tools housed within Human Capital Management (HCM) solutions. Then, HR professionals analyze this data–often with the help of advanced technological tools—to understand holistically how data points work together and pinpoint opportunities for improvement.
When applied effectively, the HR data analytics process empowers HR professionals to make data-driven decisions rather than relying on gut instincts or personal biases. The analysis reveals how to best attract, manage, and retain employees—improving employee satisfaction, productivity, corporate culture, and ROI.
From Data Reporting to Prediction: A Retention Case Study
Thanks to much better technology and infinitely more data, today’s HR leaders are able to move from reactive reporting to proactive prediction.
Consider the actionable insights gleaned from the following three retention metrics. Which of these reports would be most valuable for your team?
- Last year’s annual employee turnover
- Percent of high performers lost
- Specific high-performers at risk of attrition
All of these metrics are determined through data and analytics, but each is more complicated (and actionable) than the last. Even an organization without a computer system would be able to determine annual turnover by simply dividing the number of lost employees to total company size. Particularly when measured year-over-year, this provides useful insights about company trends. But looking at this metric alone, it’s impossible to know for sure why your turnover increased/decreased, whether these losses ultimately helped or hindered your organization, or what steps you should take to improve outcomes.
The second metric provides slightly more insight. By comparing performance management data with HRIS data, you can learn how much of this attrition came from high-potential, high-performance team members—a.k.a., your organization’s movers and shakers. Attrition is a normal occurrence in every industry (some with higher benchmarks than others), but if you’re consistently losing your best people, your organization’s health and culture will be affected. This is a clear signal you need to be doing more to strategically retain your high performers.
And this is where the third metric comes in, showcasing just one example of the incredible value of predictive analytics. In an effort to help organizations analyze metric #3, Ultimate’s data scientists developed an algorithm powered by 50 key indicators that, when taken together, can dramatically predict an employee’s intent to stay or leave the company. In talent-dependent businesses, where the cost of replacing key employees is considerable, this Retention Predictor gives managers and HR leaders a head start when it comes to retaining top performers and moving from simply reporting to actionably predicting.
Maximizing the Impact of HR Data Analytics
The ability to make data-based decisions and predictions is a complete game-changer in the HR space, especially with comprehensive solutions that can combine data from various HR systems. By reviewing engagement survey scores with performance data, you can draw a relationship between employee engagement and financial performance. Cross-reference high performer learning and development opportunities and retention to determine whether these initiatives motivated your top performers to stay.
Forget the stereotype of boring math and statistics—HR analytics provide an exciting and challenging opportunity to drive strategic, meaningful changes in your organization. When you know what’s driving your people and business, you can improve employee experience while safeguarding long-term success. You can take the guesswork out of succession management and workforce planning.
When applied effectively, HR data analytics can help you predict the future of your workforce. It is the most powerful way for HR to increase its strategic influence and earn that coveted seat at the table.
Learn more about the HR metrics you should be tracking now, and how to harness them for the most tangible benefits.