Close

Thank you for your comments. Our team will moderate and please expect it to show up on the page within 72 hours. Thank you.

What Every Employer Should Know About Top Performers

21 percent of American workers plan to change jobs in 2014, according to a Harris Interactive survey conducted for CareerBuilder. That’s right – one out of five of your employees could be looking for a job right now.

On top of the recruitment burden this creates, it’s important to consider another crucial point: volume turnover is predominantly higher among those who have the option and confidence to pursue other opportunities – and these people tend to be better performers.

When many of the workers who leave are your best and brightest, they take all their skills, knowledge and connections with them, putting your company at a competitive disadvantage.

That’s why it’s crucial to know which of your top performers are at risk of leaving and why. Avoid the temptation to look at turnover in general. This isn’t necessarily the best approach, because what you’re actually trying to do is understand how well the organization is retaining the talent that it needs to be successful now and in the future.

This type of analysis takes more than one or two metrics to understand, and is a compelling reason to make sure your workforce analytics are delivering results for your business. Once you have determined who your top performers are (which you can discover through areas like performance rating, goals achieved, manager and peer recognition) you can use these 4 key analytical approaches to help your business build a better employee retention strategy:

  • Risk of exit: It is easier to stop an employee from leaving than it is to bring them back. This type of analysis is invaluable. You may not stop everyone, but if you retain even a hand full of key employees over a year then it provides a positive return to the organization.
  • Resignation drivers: This analysis builds on the resignation rate, using a clustering algorithm to determine what factors increase AND decrease resignations. This data allows you to effectively target and fine tune your retention strategies based on data (and not intuition or anecdote).
  • Resignation correlations: Instead of reporting single metrics, it is straight-forward to correlate resignation with things like compensation ratio, promotion wait time, pay increases, tenure, performance, and training opportunities. This insight supports better decisions around changes to pay, benefits, and employee development in order to manage costs while retaining the right people.
  • Resignation segments: Comparing how resignation rates vary across locations, functions, tenure, age group, diversity group, performance level, potential, etc. provides insight into how different employee populations are responding to their work experience. This insight is valuable in delivering a strategic approach to retention ensuring program investments are targeted where they will deliver the biggest results.

From a competitive perspective, it is clearly not sufficient to only know who has left your organization. With data that reveals insights about resignation drivers, correlations and segments, you can help your team build a solid retention program that is linked to business results.

Author Photo
Ian Cook |
Curious about the differences between gaussian and pareto distribution? Ask Ian. Want to know what it’s like to kite ski North of the Arctic Circle? Ask Ian. Not only is he an expert in statistical analysis and HR metrics, he’s also an avid cyclist, skier and runner. At Visier, Ian helps customers drive organizational change through linking workforce analysis to business outcomes. He is responsible for the workforce domain expertise within the Visier solutions.