With January right around the corner, this is the time of yearwhen employers need to be proactive with their employee retention strategies. Recent data from Glassdoor specifically calls outJanuary as the month when more employees are likely to leave.

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Now is the time to find out which of your best performers may be calling it quits in thenew year. Data-driven organizations use workforce analytics toidentify the employees who are most likely to resign and moreimportantly, why, so the right levers can be pulled to stemthe tide of employees rushing for the exits.

The cost of employee turnover

Employee turnover is the single most prevalent HR metric.PricewaterhouseCooper’s 2017 annual surveyfound 77 percent of CEOs are concerned that key skills shortagescould impair their company’s growth. It’s also a very costlyproblem.

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According to Bersin by Deloitte research, the averagevoluntary turnover rate is 13 percent. If, for example, anorganization has 30,000 employees and an average voluntary turnoverrate of 13 percent, the potential cost to the organization is astaggering $427.7 million in one year.

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It’s important to note that not all voluntary turnover is bad —like the loss of the employee with a negative track record forproductivity or the team member who clashes with the workplaceculture. Rather, turnover becomes a problem when organizationsstruggle to retain their very best talent and this negativelyimpacts the bottom line.

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More than ever before, business leaders need strategic insightand the ability to model how turnover trends impact revenue andprofits — quickly and accurately.

It’s not always a question of pay

Glassdoor cited low salary as the top reason employeesleave, and indeed, I’ve heard countless stories of line managersasking for pay raises for their team in an effort to combatresignations.

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In one case, the HR team knew from past experience that anacross-the-board pay raise was the wrong thing to do. It was anexpensive way to fix the problem, and worse, it was unlikely tolead to fewer resignations. The problem was that HR had no data toprove it.

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The same Glassdoor study also found that people don’t alwaysleave because of pay. Dissatisfaction towards their managers or alack of sense of connection and meaningful contribution towards thecompany are also key reasons voluntary turnover occurs.

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Because of all the different factors that affect turnover, it’simportant to look at your resignation metrics in-depth so you canfocus on the right areas and not just to see what happened, butunderstand why it happened, what will happen next, and how to adaptyour retention strategy to align with company objectives.

How to reduce employee turnover

So what should companies be looking for to reduce voluntaryturnover? Here are few telltale data points that all companiesshould be measuring.

  1. Take stock of the damage: Determine what’sleading to higher turnover by first assessing what damage hasalready been done. It’s not uncommon in a single organization forturnover to be calculated a number of different ways — meaningthere is a lack of ability for meaningful comparison across theorganization. Companies should start by calculating resignationrates the same for all departments and locations.

  2. Identify who is resigning: It’s important forbusinesses to take stock of who is actually resigning. Is it topperformers? Senior managers? When many of the employees who leaveare the best and brightest, they take all their skills, knowledgeand connections with them, putting the organization at adisadvantage.

  3. Analyze the causes of turnover: Rather thanjump straight into giving raises across the board, dig deeper todetermine how resignations are affected by factors such ascompensation ratio, promotion wait time, tenure, performance, andtraining opportunities that employees may be seeking. This insightsupports better decisions around changes to pay, benefits, andprofessional development in order to manage costs, while retainingthe right people.

  4. Determine who can be saved: Once you havedetermined which general groups are experiencing high rates ofturnover, implement a retention program targeted at the keyemployees with the highest-risk of exit.

Data demystifies employee churn. The patterns vary: it could bea bad manager, a remote department that feels disconnected, oremployees who have a long commute time. Workforce data identifiesand addresses the biggest patterns we hadn’t previously consideredthrough advanced AI and machine learning.

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If companies aren’t able to look at their workforce through adata-driven lens and accurately predict employee behavior such asvoluntary turnover, they’re at a disadvantage in terms of retainingtop performers, as well as keeping people-related costs to aminimum.

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By combining these identified patterns with the basic knowledgeof organizational behavior, companies can implement systems andprograms that truly incentivise employees to remain at theirpositions come January and beyond.

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