Thomas Ruggia, Vice President, Global Surgical Customer Experience, Johnson & Johnson Vision
Anyone in the Field Service space will tell you that perfection has become an expectation. In the healthcare industry, that dynamic is magnified. Our customers demand a “one-touch (or less)” experience that never fails. Gone are the days where a health care provider can wait for repairs on the devices or capital equipment they depend on. Today, most capital equipment in a health care facility are part of a network of diagnostic and treatment devices that create an ecosystem designed to support a patient care strategy. If one cog in the wheel goes down, it can impact the entire ecosystem, the provider and even the patient. Though we pride ourselves on our equipment’s reliability, even the most reliable equipment will require repair some percentage of the time. When repairs become necessary, an organization’s ability to respond quickly is a competitive differentiator. Thus, executing an efficient service operation is a primary objective of our industry.
An effective field service operation relies on 3 components: (1) a reactive response function that gets devices back into operation with minimal interruption to the ecosystem, (2) a proactive preventative maintenance function to keep the devices in operation, and (3) a strong R&D function to create fail-safe devices that avoid overburdening a field service operation in the first place. Technology enables all three.
The automobile industry is the standard for preventative maintenance. Car owners get regular maintenance as a matter of course to extend the lives of their vehicles. In medical devices, maintenance is just as important, but cost is a complicating factor. In the past, increasing preventative maintenance has required more service engineers, driving additional costs against a backdrop of already shrinking margins.
At Johnson & Johnson Vision, we’re using AI to transform our preventative maintenance function. By using the data generated by our equipment to predict breakdowns before they happen, we have found we can improve the customer experience while reducing our operating costs. Briefly, here’s how it works: our devices generate performance logs during use. The performance logs reveal patterns, which can be predictive when compiled into a story. When a machine fails, the log can tell the forensic story of the failure. With enough data, we can make assumptions from the patterns that can be applied to avoid future failures. This technology is already in effect today. With Johnson & Johnson Vision Connect, we have the ability to see the patterns before a failure happens, and text message an engineer in advance of a failure, dispatching him to the site to save the day. Applying this technology to R&D pipeline projects is an obvious step in the right direction, but finding a way to retro-fit the equipment already installed in the field is a more effective way to improve our customer experience now.
Today, most capital equipment in a health care facility are part of a network of diagnostic and treatment devices that create an ecosystem designed to support a patient care strategy
The biggest challenge we will face along the way are costs associated with data. As data accumulates, the cost to apply the tech, analyze it, and create meaningful outcomes will also rise. How should we structure costs to fund the tech, without disincentivizing customer use? We’ve got to strike the right balance or we could miss out on critical pieces of data that make the system work.
The future is bright. Innovation will continue at a rapid rate, and the problems we have to solve are good ones. When mobile phones were first introduced, they were used almost exclusively for placing voice calls. Today, we use phones as mini-computers – summoning taxis, coordinating calendars, finding restaurants, finding jobs, and even diagnosing illness. That same spirit of digital innovation that has driven the evolution of consumer tech is moving into health tech, and will transform the way we serve our customers.