How to Reduce Workforce Turnover (and Improve Employee Retention) with Training Simulation

“The best employers have the best employees.”

Years after COVID-19, companies in all sectors, including logistics, are still struggling to hire (or re-hire) employees. Indeed, according to [1]:

While the statistics themselves are a bit fuzzy, by some industry estimates, the typical turnover rate for warehousing is around 37%. This means that during a 12-month period, 37% of a DC’s or warehouse’s workforce will have exited for greener pastures. And the larger the warehouse, the higher the turnover rate.

The “best in class” performance target? Just 5% or less, according to [2].

Why so much workforce turnover? According to [3], there are three main “drivers”:

• “better” employment nearby e.g. at a more convenient location
• a “better” employer nearby e.g. that offers higher pay
• “better” work/life “fit” nearby e.g. more flexible shifts

The Costs of Workforce Turnover

The fact is, replacing someone can cost 30% of that worker’s annual salary [4], to take into account

• recruiting, and then hiring, someone new
• training that new person to become safe and productive
• paying everyone else overtime until that new person contributes properly

These, of course, are the “tangibles”, but there are “intangibles” too: one person leaving can often “encourage” others to leave too. And in that way, over time, the company’s reputation as a “destination” employer suffers.

More generally.

Having a workforce with more longer-tenured operators also “means” better lift truck operations as measured by greater efficiency and fewer disruptions, compared to a workforce with “a significant share of inexperienced operators”. [2]

The Trainee Selection Problem

Some Simlog customers have reported that most trainees (up to 90%!) don’t “work out”, for these three reasons:

• they drop out before the training ends, because the work wasn’t what they thought it would be
• they’re obliged to leave before the training ends, because they’re not learning well enough
• after the training ends, they’re just not doing well enough

In each case, the training investment is “lost”. If only you could chose a “better” person at the start, before training begins!

And that’s why it’s important to make better trainee selection an integral part of your training program [5].

For example, as described in  there, a company in the food distribution business stopped looking for people who had previously worked in a warehouse or distribution center.  Instead, they sought out people with other kinds of professional experience e.g. in the “fast food” and the construction industries.

But now, without “relevant” prior employment , it’s especially important to evaluate operator “aptitude” before hiring. And that’s why HR departments are increasingly working with Operations, and Environmental Health and Safety (EHS), to improve recruiting efforts.

The Key is Better Trainee Selection

The fact is, you need aptitude and attitude to become a proficient lift truck operator. And that’s why you want to be able to

• choose people to train who are truly “ready” to learn
• train those people better, in a way that helps them develop the necessary skills and self-confidence

Fortunately, simulation can help on both counts, to ensure that they will

• have the “ability” to do well
• continue to improve (without supervision) to reach the desired level of performance

“Self-Managed” Training Simulation

But even when someone has enough attitude and aptitude, you still need to train them properly.

And that’s because the consequences of improper training are costly (equipment is damaged, merchandise is lost, people are injured, sometimes tragically).

Indeed, according to some Simlog customers, newly-trained operators are responsible for two-thirds of equipment-related “incidents”, and three-quarters of those incidents occur within their first six months of work.

Luckily, the importance of simulation for training is now well recognized and at Simlog, we believe that should be self-managed:

1. I’mby myself, so I need to have Instructional Videos to “explain” what to do.
2. My simulated work is evaluated (“scored”) in a comprehensive way, thanks to Performance Indicators that measure working carefully and working productively.
3. I monitor my own progress, by comparing my simulation results with target values (“benchmarks”).

Now performance evaluation is truly objective, because

• everyone faces the very same training simulation scenarios
• everyone’s simulated work is “scored” in exactly the same way.

Just as important, training staff now work exclusively where they can most contribute, i.e. with people who have learned to do simulated work well enough, to help them “top up” in the real world.

The Bottom Line

The fact is, you need attitude and aptitude and the right kind of training to address the employee “retention” problem that’s at the heart of the workforce turnover problem.

And although technology can “threaten, inspire, and empower”, it can also provide a “competitive advantage” when it comes to workforce development [6]

To comment on anything you read here, please write to “info@simlog.com” with “blog” in the Subject, to direct your message to me.

References

[1] B. McCrea, “Unpacking the Future of Warehouse Talent”, Material Handling Magazine, March 6, 2024.

[2] “Benchmarking and Improving Distribution Center Metrics”, YALE White Paper, September 10, 2024.

[3] Rubenstein, A., Eberly, M. Lee, T., Mitchell, T., “Surveying the forest: A meta-analysis, moderator investigation, and future-oriented discussion of the antecedents of voluntary employee turnover”, Personnel Psychology, 2017.

[4] R. Bowman, “Is There a Solution to the Supply Chain Worker Shortage?”, Supply Chain Brain Blog (https://www.supplychainbrain.com/blog), November 8, 2021.

[5] D. Ash, “Workforce Turnover Can Be Improved With Detailed Analysis”, PROMAT 2025 presentation, March 19, 2025.

[6] G. Schoppman, C. Burger, “The Influence of Technology on Workforce Development”, Construction Business Owner magazine Webinar Series, 2020.