The Coping Zone – Why does utilization affect field engineering performance?
A few years ago, I had the pleasure of managing a UK-wide field service operation with around 100 engineers and some sub-contractors providing IT hardware break-fix services to corporate customers. Typical engineering activities would range from replacing a failed monitor, through to restoring the service of a failed network server or router. The work was all reactive, with response times, fix times, and first-time completion rates being primary success factors. Daily measurements of the service operation were holistic – not just focusing on engineer utilization but also on productivity (how many jobs completed per day), efficiency (time taken to restore versus the norm), first-time completion, parts per event, and the number of visits per event. This way, monitoring how the performance of one measurement affects the others is transparent.
What was interesting to note was how the engineers’ workloads directly affected the total service quality. It’s easy to imagine that engineers with an excessively high utilization may generate a deterioration – too many jobs, engineers rushing to get through the workload, more parts used than necessary to save time but increasing costs instead of accurate diagnostics – and this is visible through the metrics. For example, high utilization (busy engineers), high productivity (busy engineers), low efficiency (not fixing the fault), increased parts per event (replace everything to get the customer restored instead of diagnosing the cause), reduced first time fix rate (engineers rushing to get through the workload and not resolving the fault correctly), and an associated downturn in customer satisfaction. The engineers are not coping with the high workload.
There’s probably no surprises there so the aim is to try and plan the number of engineers, their availability, and geographic dispersal so that a reliable, regular, and good level of service is delivered.
That’s easier said than done. Now consider this, you have planned for a certain volume of work (remember, it’s all reactive work so forecast accuracy is another challenge that’s thrown in here) but today you have enough work for just half of the engineers. So there’s low utilization, the engineers have time to operate without the pressures of being overloaded. But the same thing happens – service quality suffers because now the engineers can take too much time to resolve a simple fault, there’s no adrenalin to ‘get it done’ and move on to the next job: “I only have one more job today, so what’s the rush”? The engineers are coping too easily with the low workload – are they becoming lazy?
So how do we manage this? Too-high and too-low utilization can both harm service quality – there’s a happy and efficient medium to be found. But where and how? Let’s discuss…