The Future of Field Service Management
By Gerhard Grenacher, Lucas Hubacher, Lauren Gibbons Paul
Situated on the western tip of Labrador about 1,000 kilometers northeast of Quebec City, Wabush is home of Rogers Electric and Machine, a provider of electric motors, gearboxes, pumps, compressors, and heavy machinery equipment. The Rogers team serves companies in the petroleum, mining, lumber, hydro, potable water/water treatment, and fisheries industries.
But when customer equipment needs emergency service, the logistics of getting a repairperson to the customer site are complicated. There are few flights out – and they’re expensive – and travel times are long. But it costs a lot when an oil well or fishing trawler is out of commission, and the company says unexpected production downtime can soar into the hundreds of thousands of dollars per hour.
Looking for a better way to get repair help to its customers, Rogers turned to a “mixed reality” remote worker support system that enables senior technicians to guide technicians in the field without having to travel, according to a Kognitiv Spark case study. Senior techs use tablets to answer calls for help and can see what the field workers see through their HoloLens headsets. The technician can transmit content (such as PDFs, CAD assets, and images) needed to fix the problem. The content appears as holograms in the field worker’s environment as seen through the headset. The field worker can then perform repairs while consulting the technician.
The savings of time and money – for both Rogers and its customers – is clear. Rather than enduring three to 24 hours of travel time, the senior technician can be virtually on-site providing answers within minutes – and customers avoid heavy downtime costs. Even the environment benefits since fewer flights and van trips are needed.
– Kevin Bowers, Director of Field Services Research for the Technology & Services Industry Association
This approach to field service management – delivering experts’ knowledge and services to a customer site with a combination of remote access, communications, and sensors – goes beyond the ways that companies used to perform maintenance and repairs. Traditionally, field service organizations sent technicians to customers’ sites armed with paper and clipboards to track assets, check equipment status, and fix machines. Companies in various sectors, such as manufacturing and utilities, have relied on these manual processes for more than 100 years.
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Now a combination of new technologies and business process adjustments is advancing the field service function. Advanced preventive and predictive maintenance technologies, which use connected devices in the field to reduce routine maintenance tasks, enable enterprises to increase first-time fix rates and head off unplanned downtime.
For companies that employ service organizations, these advances promise to increase the service organization’s profitability. For companies that maintain their own equipment field service teams, they promise to reduce the costs involved. At the same time, both types of service organizations can improve customer service and increase worker and equipment productivity.
These technologies – especially Internet of Things (IoT)-connected devices – aid the transition to “servitization” for companies that sell equipment as they steadily transition from being product vendors to service providers, according to Kevin Bowers, director of field services research for the Technology & Services Industry Association.
“Field service organizations are finally seeing an influx of data from connected devices, and they’re investing in data scientists and analytics professionals to begin to take advantage of that data,” says Bowers. “Product revenues are declining, and service revenues are increasing. Traditional product manufacturers can drive revenues by investing in field service technology.”
Advances that lead to business process improvements
In recent years, there has been a surge in the introduction of field service management tools that employ advanced technologies to reduce cost, increase efficiency, and boost customer satisfaction. The rise of IoT connectivity and the incorporation of equipment data in field service applications through high-speed networks is driving adoption of these systems, according to a May 2022 research note from Reports and Data.
The combination of these capabilities is driving a number of business process improvements that enable companies to get ahead of needed maintenance, including:
Proactive move no. 1: Condition-based maintenance
Condition-based maintenance means that maintenance tasks are performed according to the actual condition of equipment in the field as reported by sensors to a central maintenance system. It stands in contrast to traditional maintenance (also called “reactive” or “run-to-fail”), which was based on a set schedule and was analogous to changing the oil in your car every 3,000 miles whether it needed it or not.
Now, machines connected by IoT sensors can automatically report their conditions to a system that then launches routine maintenance, including dispatching a technician to the site if needed. This avoids wasting time and resources on unnecessary maintenance while also potentially giving early warning where needed if a part or piece of equipment required attention earlier than expected.
The oil and gas industry, which relies on expensive rotating mechanical equipment, such as induction motors, compressors, and pumps, illustrates the value of condition-based maintenance, a recent Institute of Electrical and Electronics Engineers conference report notes. With conventional maintenance schedules, companies risked wasting money working on equipment that did not need fixing.
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Proactive move no. 2: Predictive maintenance
Predictive maintenance goes one step further than condition-based maintenance to identify specific items that need attention before they break. Using alerts from IoT sensors to flag equipment that is about to have a problem based on trends spotted by data analytics and machine learning algorithms, predictive maintenance systems use past and current IoT sensor data to assess machines’ activity patterns.
“The system might say, ‘Within a couple of weeks, we think this motor is going to fail, because we see some vibration or some higher temperatures,’” says Bowers. In that case, the field service organization could dispatch a technician when it is convenient for the customer before an actual problem brought down the whole system. That’s the point of predictive maintenance: avoid costly unplanned downtime.
Predictive maintenance is not just for manufacturing. If a restaurant’s refrigerator is beginning to malfunction, predictive maintenance technology can alert restaurant staff, enabling them to fix the problem before the fridge went down and food was spoiled or wasted, notes Semiconductor Engineering.
Connecting remote expertise: Augmented reality and virtual reality
Augmented reality supplements the user’s surroundings by adding digital elements to a live view, often by using a smartphone. A user can see and hear things in the surrounding environment while experiencing the additional information.
Virtual reality, on the other hand, creates an immersive experience – usually delivered through goggles – that replaces a real-life environment with a simulated one.
Augmented and virtual reality can be used in complementary fashion, creating a “mixed reality” application in which users can both see and interact with the real world and the virtual environment at the same time.
These systems are useful in the field, both to provide service and to conduct training. Technicians can wear headsets such as the Microsoft HoloLens or the Vuzix Blade at a remote location (such as company headquarters or a technician’s home) to maintain systems at a customer site, as with the Rogers example described at the start of this article. The systems can present information in an immersive format – with 3D illustrations and video-driven instructions – that eases access to key information and can provide real-time feedback when connected to an in-house technician, as analyst Tim Bajarin notes on Forbes online.
Using data to improve service: AI and machine learning
AI and machine learning use data sets derived from IoT sensors on equipment to predict patterns of behavior or reveal actionable insights.
The equipment can include service vehicles. Consider scheduling service calls for a task force of technicians. For example, if it’s taking too long to dispatch a technician, a machine learning application could comb through data from the service organization to figure out why.
There are several possibilities for using AI to improve field service – whether the AI capabilities come embedded in a field service system or the customer does its own – such as training a machine learning system to identify needed parts and the steps to take in the case of unplanned equipment outages.
The Business of Service
Leaning into the human factor – and the history of the field
While field service organizations deal with equipment, they’re also in a people-oriented business. Over many years, technicians can get accustomed to familiar routines and customers as well as the machines they service.
As with any technology, adapting new field service management systems means paying attention to the effect it has on an organization’s people. Field service veterans, even those approaching retirement, might resist new technology if they view it as an attempt to replace their expertise. On the other hand, younger field service workers, especially at companies where service is the business, may be keen to get their hands on the latest and greatest technologies for professional advancement and other reasons.
In both cases, leaders can make a concerted effort to communicate to each group the benefits of using the technology. Veterans who are receptive to learning to use new tools can extend their careers and take on consulting and teaching roles. Younger workers can gain needed experience in the new technologies, giving them portable skills.
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And it pays to recognize that retaining talented technicians is not a luxury. Field service organizations have been clamoring about labor shortages for years. In 2016, 70% of organizations surveyed by The Service Council, a service industry group, said they would be “burdened by the knowledge loss of a retiring workforce” by now or 2027. Meanwhile, a Korn Ferry study estimates global labor shortages of 85.2 million skilled workers of all types by 2030.
As Baby Boomers continue to retire, digital natives who acquired fluency in technology as early as they did in language will come to the fore of field service organizations, as elsewhere.
When implemented well, advancing field service management technologies promise a kind of talent bridge – to link experienced workers with customers and new colleagues and to deliver expertise remotely – while modernizing traditional business processes. Field service has come a long way since the days when clipboards were the gold standard for keeping far-flung machines humming.
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