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Negated turnover risk by reducing burnout: how one large Aussie company did it

Negated turnover risk by reducing burnout: how one large Aussie company did it
This is a case study written under a pseudonym "ALPHA" for the privacy of the customer


  • Retained at-risk employee, saving $60,000 in employee turnover costs
  • Potential annual savings of $25.6m+ when applied across entire company workforce (at a 9.5%** turnover rate)
  • Prevented psychological safety risk of burnout by identifying source of unsustainable workload, then reducing it by 20%


ALPHA’s problem

ALPHA*, a large Aussie retailer, conducted a company-wide engagement survey that revealed an alarmingly high number of people reporting unsustainable workloads - a very common challenge for many organisations today.

Research shows excessive workloads cause burnout, which is likely to lead to employee turnover, decreased productivity and even contribute to mental illness. In fact, research reveals burnout is the biggest cause of high employee turnover. With psychological safety risk now on the radar, addressing workloads has become a top priority for 2023. 

Finding the source of the problem

One proactive division within the organisation introduced Beamible, a work design platform, to help quickly and systematically identify which employees were drowning in unsustainable workloads and why.

In order to accomplish this:

  • The manager used streamlined naming conventions to categorise bundles of work
  • Each employee populated their roles within the platform then applied specific tags to each task, allowing the business to immediately pinpoint the drivers of standout workloads via the Beamible insight dashboard

The data revealed that one employee, Connie*, was spending 3x as long on some work activities than her peers, triggering a deeper dive into Connie’s role design.

Zeroing in on Connie

As a Regional Marketing Manager, Connie had the same job description as several others in her team, however, she was working 9 hours more than every other person. A work analysis revealed that she was spending an additional 7 hours on reporting, and additional 2 hours in one meeting per week. Why? Was it a performance issue? A capability issue?  

Connie’s manager, Zoe*, took the data and insights to a key stakeholder, Bryan*, who is the General Manager for Connie’s assigned region, to investigate. Zoe found it wasn’t a performance issue at all. In fact, there was a process which was being run differently for Connie in comparison to how it was run for her peers, resulting in a spike in workload for her. Upon even further digging into similar teams, they discovered the same inconsistent process was increasing the workloads of several other individuals on different teams. It was awork problem, not apeople problem. 



Presented with the Beamible team view of work priorities and time allocation, Bryan could see clearly that his expectations were quite different to the other regional GMs and wanted to find a solution. He decided to maintain the current process rather than changing his process, but also valued Connie’s partnership and didn’t want to risk losing her. 

Together, Zoe and Bryan were able to find a solution. Bryan reprioritised his own support resources to provide Connie with a shared resource 1.5 days per week. The shared resource would now do the bulk of the reporting, allowing Connie to focus on the reporting insights and meeting, and returning to a reasonable workload. Bryan incurred no disruptions to his work outcomes at all and Connie stayed with ALPHA company rather than resigning from burnout. This was a critical outcome, as Zoe reflected that the previous two people in Connie’s role left due to burnout and she’d never understood why, until now!

In this Beamible team view, you can see the difference in time spent on two specific tasks was increasing Connie’s overall workload by 9 hours in comparison to her peers.


By reallocating the overflow of work to a shared support resource, Connie was able to stabilise her workload without impacting team outcomes - and without incurring extra costs.


Small change, big impact

Connie was an attrition risk. She had been struggling with workload and was at a tipping point, ready to resign. We’re happy to report she’s still working for ALPHA and confident she’s performing well, confessing the turnaround was directly as a result of this inquiry. 

Remarkably, finding a shared resource who had some capacity to support another area saved this company $60,000 in recruitment and onboarding costs for a replacement had they lost this employee to unsustainable workloads. 

It also saved emotional cost to Connie, as she was able to avoid being pigeon-holed into the assumption of poor performance, work ethic or another label that could have hurt her career progression. With the impacts of burnout on top of this, ALPHA company is a shining example of psychological safety risk being identified and reduced through role analysis.  

The power of objective data, and a visual representation like Beamible to diagnose drivers of excessive workloads is enormous. Using the Beamible pilot and successful work redesign for Connie, a taskforce is rolling out this approach across other at-risk teams and individuals in the division, and eventually across ALPHA company. 

It’s hard to ignore the potential savings at scale if every organisation could identify burnout risk before it results in disengagement, mental illness or attrition. For ALPHA, it has the potential to save a whopping $25.6m every year, based on an average 9.5% turnover rate**. 



Pilot Beamible with your own team

Keen to see the impacts Beamible analysis and problem solving can have on your team? We can help your business identify risks before they become costly consequences, and take action for your people. Ask our sales team today about starting on a pilot program - a bit-sized commitment with big benefits.

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* Pseudonyms used to protect the privacy of the individuals involved.

** Average turnover rate in Australia in 2022 used in the absence of real turnover rates at ALPHA for privacy reasons

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