By Sidney Lara

Some leaders of medical device field-service organizations are keeping a close eye on issues involving the consistency of their teams’ service performances. These leaders recognize that the skill gaps across technicians of varying levels of proficiency can prove frustrating to customers who don’t want to put up with the downtime, delays, and the hassles of dealing with an unskilled field engineer.

These leaders are aware of the higher costs that can result from the skills gap. For example, repeat visits from a technician to solve the same problem, or greater parts consumption by technicians who are uncertain of a solution.

The attention brought to the issue becomes all the more urgent amid the ongoing retirement of aging service technicians, which is leading to the loss of knowledge that spans decades.

Top Teams Narrow the Skills Gap

Recent research that analyzed trends among 8,200 medical-device service technicians found strong support for the need to close the skills gap of field-service teams. The best-performing teams feature technicians who have a shared knowledge of skills, allowing them to provide a more consistent experience for customers and keep hospitals running, uninterrupted by downed machines.

For example, let’s look at first time fix rates (FTF), a common measurement used in the field service industry that reflects how often someone is able to repair a medical device or piece of equipment on their first attempt. The organizations that do best by this measurement have a 14% difference in skill levels between their best and weakest technicians. The weakest organizations have a 30% gap.

The gap is even more pronounced when it’s viewed through the lens of other performance indicators:

  • Mean time between failures, which is the average time between customer issues. There’s only a 2% skills gap among workers in organizations that do best by this measurement. At lower-performing organizations, the gap is 33%.
  • Mean time to resolution, which is the time that’s needed to resolve a customer’s issue. The skills gap is 20% among workers at the best organizations, while it’s 59% among lower-ranking organizations.
  • Mean time between visits, which reflects uptime rates. Top organizations have a 36% gap in workforce skills; those in the 20th percentile have a 57% skills gap.

However, FTF may not be the measurement medical device technicians should be paying attention to.

The Total-Cost Impact

Studies show the skills gap is particularly telling when organizations measure service cost per success.  This all-encompassing indicator captures the costs of multiple visits, multiple truck rolls, parts, and the expense of assigning high-priced experts to the most complex jobs.

This is a far better indicator than first time fix rates. Even if FTF rates stand at 75%—a figure that’s been common through the medical devices industry for the better part of a decade—that means one in every four repair calls requires a return visit. In fact, failed first visits result in an average of 2.5 additional visits and 20 additional days to resolve the issue.

Take, for example, the service cost per success records of two technicians:

Jessica, a highly skilled top technician has a first-time fix rate of 76%. She resolves problems within an average of 5.2 days. An average service cost per success of $908 results from her work. 

Jason, her less-skillful co-worker, has a lower first-time fix rate of 63.2%. He also needs a little longer to fix problems — 6.6 days. His work requires an average cost of $1,225 per success.

The difference in first-time fix rates is modest. So is the difference in the amount of time that the two technicians need to resolve issues. But the difference is dramatic — 35% higher — when the cost per success is measured. That’s because service cost per success captures all those costs that escape notice when only FTF rates are tracked.

In short, a wide gap in skills leads to skyrocketing service costs. But without technological advancements to effectively track these metrics, service leaders will never be able to effectively measure their teams’ performance, meet customer demands to keep medical devices running, or provide a service experience that distinguishes their organizations from competitors.

The Cost of Frustrated Customers

For the clinics, hospitals, and research laboratories that rely on field-service teams, downtime isn’t merely an inconvenience or an expense. Patients’ lives or the outcome of important clinical trials may be at stake when service levels slip.

At one leading medical device company, a top field-service executive observes that clients in hospitals, clinics, and similar settings these days demand a faster resolution of service issues to reduce downtime for medically important, revenue-generating devices.

The medical device executive added that tools that put the power of artificial intelligence into the hands of field-service teams can help technicians meet customer expectations, improve their work satisfaction, and provide service leaders with solid information they can use for coaching other technicians.

Coaching, in turn, provides a consistent service experience. When skill levels vary across an organization, customers don’t know what to expect, either the technician who will get things right the first time or the one who will need extra days to solve the problem.

Growing Pressures to Close the Gap

The gaps in knowledge across the medical device technician workforce may  worsen in the coming years. Service organizations already report tens of thousands of unfilled jobs in the current tight labor market. Every retirement of a service technician could result in the loss of sharing decades of hard-earned practical knowledge to newer, less-experienced techs.

Adding to the pressure, field service organizations in the medical-device arena are experiencing rapid growth in demand. The number of service events in the sector has grown by 65% since the start of the COVID pandemic, and it’s taking technicians more time to resolve issues. With every new generation of medical devices, the complexity of service and maintenance issues grows.

The impacts of the skills gap also are felt in other ways. Managers of field-service teams lean even more on their already overburdened expert technicians. As these experts burn out, seek out new opportunities, or retire, costs rise rapidly as managers are forced to rely on less-skilled technicians.

How Technology and Training Helps

The aforementioned issues create an emphasis on developing consistent, ongoing training to ensure that the hands-on knowledge of the most skilled technicians is shared with their less-experienced colleagues. Top field-service leaders are also turning to sophisticated technological solutions, which enable organizations to reduce the skills gaps —technicians can tap into a common database of maintenance and diagnostic instructions while they’re at a location where research or medical care depends on their skilled capabilities.

One large medical device company, for instance, reports that it reduced the number of service visits per month by 20%, saving more than $5.5 million annually, after the implementation of AI-powered solutions. Along with the bottom-line contribution of more efficient field service, the medical-device executive says that data generated by AI solutions provides his company’s sales team with a competitive advantage: they can provide fact-based findings to potential equipment purchasers.

Customers expect unrivaled service from the field-service teams who repair and maintain medical devices. It’s up to the leaders in the field to make sure all the members of their teams have the skills to deliver consistently excellent service for medical networks. And it’s up to all of us in the industry to commit ourselves to use of the performance indicators and data that gather the right information and allow us to accurately measure our teams’ progress toward excellent results.

Sidney Lara is currently the service principal at Aquant, a software company focused on bringing service intelligence to field service organizations through AI and data-powered platforms. Questions and comments can be directed to [email protected].