It’s no secret we are living in a job seeker’s market. With unemployment at a 16-year low, the risk of employees considering other job opportunities is high. In fact, the ADP Workforce Vitality Report found that job switching in the U.S. during the 3rd quarter of 2017 was 27%– an all-time high. Additionally, nearly two-thirds of the global workforce is actively or passively seeking new job opportunities, according to the ADP Research Institute’s study, The Evolution of Work 2.0.
HR and business leaders see this firsthand as they fight to keep innovative, eager talent engaged and on their teams and are leveraging their people data to improve the hiring and talent retention process. How? Benchmarking.
Benchmarking is the process of comparing your organization’s own processes and operations against those of your competitors. Benchmarking tools utilize internal and external data to generate insights that will help businesses understand how they stack up against competitors in terms of salary, retention and a host of other factors that can lead to increased engagement.
However, as the world of work evolves, so are benchmarking tools. In the past, benchmarking was done very broadly—for example, by comparing managers in retail against other managers in retail. But today’s tools include a vast array of job classifications, regions, and other demographics to benchmark against.
Now, companies can drill down from the broad category of retail to focus on average wages for a sales associate at a women’s clothing boutique in the Midwest. As businesses seek to remain competitive in hiring and retaining unique employees with specific needs, this level of functionality is important—especially as the job market becomes more complex and job titles mix, merge, and blur.
But as any talent management professional knows, providing competitive salaries is only half the battle. Benchmarking can help with a host of concerns. For example, is your business at risk of losing employees? Does a team of developers in Tallahassee, Florida have a turnover rate higher than the industry average? That’s a signal for action.
Do managers need to improve engagement, decrease absenteeism, or increase the amount of time spent on training programs? Identifying and acting on these concerns can help to increase employee engagement and drive retention.
Across an organization, benchmarking can also be used to understand how competitive an organization’s HR policies are. Are people being underpaid? Are people receiving the training they need? Are people being promoted at a similar rate to others with the same job? Identifying these areas can predict hotspots for turnover.
Benchmarking can also help employers hold on to talent by focusing on retention where retention lives—on teams. And what are the biggest factors driving the culture, operations, and success of a team? The team leaders. The ADP Research Institute’s study Fixing the Talent Management Disconnect revealed that the top reason employees choose to leave a job is due to a poor relationship with their direct manager.
Although benchmarking was once firmly in the province of HR and recruitment, these tools can also be used by team leaders to help identify issues and address them quickly. By bringing these insights directly to frontline managers they can strengthen their relationships with employees by efficiently addressing issues directly with them while they continue to focus on doing good work, incentivizing top talent, and moving the business forward.
No business wants to miss out on their next great leader because of an inaccurate job description, below-average salary, or inability to keep them engaged compared to their competitor. At the end of the day, companies missing the benchmark are just plain missing out.
|Marc Rind is vice president of product development and chief data scientist at ADP. He is an experienced software and system architect responsible for bringing emerging technologies to enterprise readiness, with a focus is on database solutions and the strategic and tactical approaches to leveraging large amounts of data.|