by Ian Cook, January 16, 2018
This is the time of year when employers need to be proactive with their employee retention strategies. Recent data from Glassdoor specifically calls out January as the month when more employees are likely to leave.
Now is the time to find out which of your best performers may be calling it quits in the new year. Data-driven organizations use workforce analytics to identify the employees who are most likely to resign and more importantly, why, so the right levers can be pulled to stem the tide of employees rushing for the exits.
Employee turnover is the single most prevalent HR metric. PricewaterhouseCooper’s 2017 annual survey found 77 percent of CEOs are concerned that key skills shortages could impair their company’s growth. It’s also a very costly problem.
According to Bersin by Deloitte research, the average voluntary turnover rate is 13 percent. If, for example, an organization has 30,000 employees and an average voluntary turnover rate of 13 percent, the potential cost to the organization is a staggering $427.7 million in one year.
It’s important to note that not all voluntary turnover is bad — like the loss of the employee with a negative track record for productivity or the team member who clashes with the workplace culture. Rather, turnover becomes a problem when organizations struggle to retain their very best talent and this negatively impacts the bottom line.
More than ever before, business leaders need strategic insight and the ability to model how turnover trends impact revenue and profits— quickly and accurately.
Glassdoor cited low salary as the top reason employees leave, and indeed, I’ve heard countless stories of line managers asking for pay raises for their team in an effort to combat resignations.
In one case, the HR team knew from past experience that an across-the-board pay raise was the wrong thing to do. It was an expensive way to fix the problem, and worse, it was unlikely to lead to fewer resignations. The problem was that HR had no data to prove it.
The same Glassdoor study also found that people don’t always leave because of pay. Dissatisfaction towards their managers or a lack of sense of connection and meaningful contribution towards the company are also key reasons voluntary turnover occurs.
Because of all the different factors that affect turnover, it’s important to look at your resignation metrics in-depth so you can focus on the right areas and not just to see what happened, but understand why it happened, what will happen next, and how to adapt your retention strategy to align with company objectives.
So what should companies be looking for to reduce voluntary turnover? Here are few telltale data points that all companies should be measuring.
Data demystifies employee churn. The patterns vary: it could be a bad manager, a remote department that feels disconnected, or employees who have a long commute time. Workforce data identifies and addresses the biggest patterns we hadn’t previously considered through advanced AI and machine learning.
If companies aren’t able to look at their workforce through a data-driven lens and accurately predict employee behavior such as voluntary turnover, they’re at a disadvantage in terms of retaining top performers, as well as keeping people-related costs to a minimum.
By combining these identified patterns with the basic knowledge of organizational behavior, companies can implement systems and programs that truly incentivise employees to remain at their positions come January and beyond.