top of page
Working with Laptops

Orderboard Blog

Using Data To Reduce Attrition

Attrition Spikes

2021 continues to shape up as the year of “The Great Resignation,” with record numbers of Americans voluntarily leaving their jobs as the economy continues to move out of the Covid slowdown.

The Department of Labor just announced that 4.2 million people quit their jobs in October. While this was slightly down from September’s total of 4.4 million who left their workplaces, it was still close to the record. At the same time, the number of open and unfilled jobs rose to 11 million, also close to a record high.

It may be fun to debate why this is happening. Conservatives blame government benefits for discouraging work. Liberals see a correction about four decades in which the wages of most Americans stagnated. Lifestyle gurus credit Covid for inducing a national re-examination of the role work should play in people’s lives and happiness.

Fun as that debate might be, for most business managers that debate is unimportant. Business managers have teams to run, teams that need people with specific skills, teams that need enough people to shoulder the load. And arguing the causes of The Great Resignation, when those causes are things like macro-economic trends and government checks that managers cannot control, does not help managers lead their teams, get the work done, or retain their employees.

That’s where OrderBoard comes in, with a novel data-based approach to helping managers deal with retention now.

OrderBoard is a Big Data/AI company that helps find people with hard-to-find skills for hard-to-fill jobs. To do this, OrderBoard has built a database with information on the American workforce – 160 million strong. That’s a lot of data, and with that data you can do a lot of things. What OrderBoard has done lately is focus on predicting How Likely Is Any Employee To Leave Their Job.

Using all that data, and looking at who leaves their employer and when they do it, OrderBoard’s AI can assess all the people in an organization for their relative likelihood to move on.

Every experienced manager has had the awful moment when a valued employee announces they are planning to leave, and then the week-long scramble to try to assemble a counteroffer that as likely as not is too late. But what if you could see who was most likely to leave before the employee starts crafting their “I quit” email? What if you could do something in advance to change the odds?

Can You See Who Is Likely to Leave?

Why do people decide, in Johnny Paycheck’s immortal lyrics, to “take this job and shove it.” Anyone who has ever heard that song has heard the chorus in their mind at some point in their working life.

Now in the song, Paycheck was leaving because of marital problems, which is unlikely to be the number one reason why most people leave a job. There are a lot of possible reasons: comparison of one’s own position with how others are being rewarded, how well a company is doing in its industry, time in job, lack of opportunity, lack of growth opportunities (so valued by younger generations). There is an old adage that still holds true, “People join a company but leave a boss”. Even Paycheck was on to that one, as he sang, “Well that foreman, he’s a regular dog/The line boss, he’s a fool.”

By using AI, OrderBoard has been able to put a lot of those factors together and extract the patterns associated with resignation or retention. (Admittedly, we cannot measure whether the foreman is a regular or irregular dog, but we can access a lot of factors and we are working to access more.)

What comes out of analysis is a number that represents the likelihood a person will leave their position in the next six months. Higher numbers = more likely. Lower numbers = less likely. Now you can look at the people who work for you and see who is more or less at risk. You can look at your highest-rated (and most important) contributors and see which ones are most likely to go. You can look at the ratings today and the ratings six months ago and see whether the urge for going is increasing or decreasing.

As a result, you can create a much more targeted approach to retention.

Without the view OrderBoard provides, programs to curb retention either target everyone, in which case the same level of effort is going into retaining your weakest contributors as is going into retaining your best contributors, or the program is focused on your top-rated performers, in which case as much energy is being focused on people who are not even thinking of leaving as on those who are at risk of going.

With OrderBoard’s data, you can find patterns in retention risk. Is it concentrated in specific specialties, in people with a certain profile (Gen X employees, Gen Y) for example, is it associated with one or two managers, does it spike at particular points in people’s career?

And you can focus your energy on the people most likely to leave.

Let’s talk about how to focus that energy next.

Three Things You Can Do to Improve Retention

OrderBoard’s retention metrics can identify the employees in your organization who are most likely to resign in the coming year. Are these predictions perfect? No. But they are backed by good data and analysis, and OrderBoard is working with its clients and their real experiences to improve the prediction model going forward.

So you have predictions, but that won’t matter unless you do something. Here are three ideas you can put in place:

1. Rehire your employees

Think about hiring a person. You have made the person an offer; you want them to join your company. What do you talk about? Mainly, why that person should join. What will your company do for the employee? What does that employee want and how can they achieve their goals through working for you? How can the company accommodate the employee’s needs?

Once the employee joins the organization, the conversation shifts 180 degrees. Now the question becomes what contribution is the employee making to the company? What progress is the employee making on goals and targets that are set to help the company reach its goals and targets? The company is no longer wooing, it is evaluating.

Every employee you want to retain should experience a re-hiring meeting at least once a year, where the focus shifts back to the goals of the employee – both long- and short-term – and how the company can work with the employee to help them reach their goals. You can be sure that anyone else trying to recruit one of your valued employees is having those conversations with the employee. You should have them too.

2. Move people around

People join a company but leave a boss. Of course those bosses make every effort to keep their best performers, even as the employees are thinking how tired they are of their manager. What if you set up rotations for high-performing retention-risk employees, where people were able to work for a different boss, without the employee taking the risk of raising the issue? As employees put increasing value on having the opportunity to enhance or broaden their skills, changing jobs provides those growth opportunities that a younger generation of workers, attuned to the speed with which skills go obsolete, look for.

A manager may resist giving up a strong performer, but if the choice is between letting that employee be strong somewhere else within your company or having that employee be a strong contributor somewhere else, the choice is obvious!

3. Re-think evaluating managers

Peter Drucker taught us management is the art of getting things done through other people. How many managers are evaluated for that, though, as opposed to being evaluated for hitting financial or productivity metrics. This does not have to be a large-scale “balanced scorecard” program, where every manager is evaluated for people development that is going to turn into yet another “let’s do the minimum to meet the metric” exercise.

Rather, look at your HR system data over the past three or five years. Which managers develop people – measured by which managers promote people within the organization from their group? Reward those people. Which managers, if any, have the highest rates of voluntary attrition… in particular, attrition of performers you don’t want to lose? Focus management development on those people because that is where an improvement is needed.

Recent Posts

See All
bottom of page