HR is sitting on a goldmine of data that has the power to impact not only an organization’s bottom line, but the day-to-day operations. Unfortunately, there’s a precedence of not being able to convey that critical data in a way that influences the C-suite. HR often doesn’t have the tools they need to access, much less interpret, the data.
But that’s exactly what needs to happen. After reviewing proprietary data from nearly 3,000 Paycor clients, we found the most successful HR teams are able to map people management metrics to business outcomes. To help your clients measure what matters, CFOs need HR to become more data driven. Here’s a look at some of the questions your clients need to ask in order to measure the metrics that matter most to the C-suite:
The loss of productivity resulting from vacant job roles is quantifiable, which makes your “time to fill” metric critical. The “time to fill” tracks the number of days it takes to fill a job, from job requisition to offer accepted. It can reveal the effectiveness of your recruiters and your overall process including if your process is taking too long and if you’re using the right channels to advertise the position.
Finding skilled talent has never been harder. In fact, a recent Robert Half International survey revealed the CFO’s toughest challenge this year is finding and hiring talent. The good news is, the solution might be right under your nose. If you don’t have an employee referral program—where your current employees refer candidates for job opportunities at the company—it would be worthwhile to start one. Employee referrals are the top source of new hires, according to SHRM, and can reduce the time it takes to fill open positions while providing top talent that sticks around longer.
Nearly half of HR teams don’t regularly meet with finance leaders—that’s a problem. Labor costs are probably your organization’s biggest expense and focusing on how to optimize the spend should be a priority for both departments. Everything from the absenteeism rate to compensating employees based on market rates needs to be considered. Accurate labor costs allow you to identify trends and make adjustments where necessary.
If your overtime costs have been unusually high, you’ll only be able to uncover the cause with accurate, easily accessible payroll data. From there you can derive insights into when the most overtime hours are logged, which departments or employees are working overtime and whether a similar peak occurred in the past. The best data analytics tools should allow you to customize and filter information to fulfill your unique needs.
Voluntary resignations are at an all-time high, so it’s crucial to understand when and why your employees are choosing to leave your organization. Keep in mind seasonality and industry type can leave an impact, but generally speaking, you calculate turnover rate by dividing your total number of employees by the number of those who left (during a given period of time). If your turnover rate is higher than the industry average, it can indicate deeper issues within your organization.
People are job hopping faster than ever before. One in five Millennials say they switch jobs every year, according to Gallup. That’s a lot of time, money and effort spent on recruiting, hiring and training just to have an employee leave for greener pastures. Which makes the insights of your turnover rate all the more important. Dig deeper into trends by locations, departments or managers. This can help identify problem areas like bad managers or burnout before they become real issues.
How Paycor Technology Helps
Paycor Analytics takes the complexity out of workforce analysis and planning by empowering HR leaders with high-impact, easy-to-consume, real-time data insights. We provide answers t a host of pre-built questions about your workforce and display trends and predictions, so you can take action by making complex, business-critical decisions every day. To learn more, visit Paycor’s HR Reporting & Analytics.
*Source: Society for Human Resource Management
**Source: U.S. Bureau of Labor Statistics
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