Service Benchmarks Across 5 KPIs
Aquant, has recently published the 2022 Service Intelligence Benchmark Report, now available at Field Service News, which offers an in-depth analysis of field service performance and customer satisfaction in a year of talent shortage, COVID service pivots, and shifting customer demands…
In the Service Leader’s Guide to Workforce KPIs, we examined why workforce measurement is more critical than ever, and we defined best practices for measurement criteria.
For the 2022 Service Intelligence Benchmark Report, we went a step further.
We analyzed service data to understand service performance beyond KPI measurement. We found that knowing your KPIs—by number or average performance—is not the same as understanding what those numbers reveal about customer satisfaction, employee skill level, or overall service performance. Averages don’t disclose the specific details you need to make critical service decisions.
Service KPIs by the numbers
Here’s the breakdown of how service organizations measure up against other organizations and the industry as a whole.
FTFR – First Time Fix Rate
First Time Fix rate is one of the most popular metrics for workforce measurement. It indicates how often someone is able to fix an issue on the first try. In this report, we are measuring the FTF rate of field visits, in a 30-day window.
FTF rates have hovered around 75% for more than a decade—and remained stagnant for all but a handful of top-performing companies. Additionally, FTF rates should never be measured in isolation. On average, a failed first visit leads to 2.5 additional visits and 20 days for MTTR.
CPS – Cost Per Success
The total amount required to successfully close a service ticket is known as the Cost Per Success (CPS). This is a bit different from other similar-sounding KPIs, such as Cost Per Truck Roll, since total CPS may include multiple visits, multiple truck rolls, a variety of parts, and other labor costs.
Some organizations may measure Cost Per Work Order, but that metric leaves out cases that include always assigning experts to the most complex (and expensive) jobs. Additionally, it does not account for cases where multiple work orders are related to the same core issue.
MTTR – Mean Time to Resolution
The Mean Time to Resolution KPI measures the time it takes to resolve a customer issue.
Typically, it’s the time between the case creation date and the closure date. Similar to the pain of staying on hold when trying to resolve a personal issue, minimizing MTTR is a key factor in increasing positive customer experiences and reducing service costs. In the last year, we’ve seen a growing divide in this metric.
MTBF – Mean Time Between Failures
Mean Time Between Failures quantifies the average time between customer issues. Service organizations try to maximize this metric because a higher rate represents excellent service quality and maximum uptime.
Individual pieces of equipment may have differing life cycles, but service leaders need to understand underlying patterns—in both their machines and workforces. When visiting a job site, experienced service heroes know how to use their time wisely and ensure that assets are working properly before leaving. This can significantly extend the time between failures.
MTBV – Mean Time Between Visits
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