As we’ve discussed in previous blogs, it was just a matter of time before Field Services organizations moved from the early adopter phase to implementing and leveraging artificial intelligence (AI) and machine learning (ML) to automate processes and gain insights that enable greater predictivity for strategic business decisions. This post will share some examples of how the Field Services industry is using AI, ML, Internet of Things (IoT) and Augmented Reality (AR) to survive and even thrive in the massive “New Normal” disruption caused by the COVID-19 pandemic.
Previously, we discussed the benefits of AI and ML related to workforce productivity, customer satisfaction, first-time fix, and how Field Service organizations can improve their metrics in these key areas.
Now, let’s fast forward to today and the disruption from the COVID-19 pandemic. Three key topics should be top of mind for Field Service organizations going into 2021:
Previously, we started by looking at service planning to meet customer service demand. Several variables should be taken into consideration when planning services based on demand. AI/ML can make a big impact here by using a combination of heuristics and predictive techniques to establish which underlying variables have historically been the most important factors in predicting actual demand. This enables Field Services organizations to effectively plan resources, mitigating overtime cost and minimizing the need for having to recruit contractors last-minute to meet customer-service needs.
Applying ML to historical data captured from service planning and customer demand forecasting helps realign territories to ensure adequate coverage is provided to meet customer demand. With the addition of IoT devices to the equation—measuring temperature, vibration, humidity and other environmental metrics, not only can we improve service and downtime from planned tasks, we can also routinely predict when a component will fail, based on continual, real-time measurements, and when we will need to plan for replacement of the failing or compromised component.
Using AI/ML and IoT together enables preventive maintenance to become predictive—by taking actual equipment condition into account when determining repair/replace schedules. Organizations that have implemented AI/ML use IoT censors to monitor equipment performance, capture data, and analyze it to identify any abnormalities. When performance falls below specific thresholds, work orders are automatically generated and sent to Field Service technicians to perform.
As we entered 2020, Field Service organizations were well on their way to providing paperless, digital processes for work order management, route planning, and invoices. The disruption caused by the COVID-19 pandemic forced these same organizations to pivot to completely paperless contactless delivery of service, electronic signatures, automated payments and constant customer communication. Although these moves were prudent from a cost and ROI perspective, they were also critical to ensure continuous operations and customer satisfaction while maintaining the safety of technicians and customers alike as a critical focus.
Field Service Organizations that made early investments in advanced technologies like AR and IoT benefited during the pandemic disruption, some of these benefits are as follows:
“According to McKinsey, Field Service organizations can reduce their personnel costs by up to 30%.”
According to McKinsey, as Field Service organizations make the move to fully-digital service delivery utilizing automation, personnel costs can be reduced by up to 30%. McKinsey also states the current shortage of field service technicians will be further exasperated—with up to half of all field service workers being freelance by 2025.
Field Service organizations that are investing in advanced technology to increase efficiency will need to insist that the applications and tools used by their workforce (both internal and external) be flexible enough to support variations of constituents. These constituents would encompass FTE resources, contractors, freelancers, and customers (as well as others, potentially). Much like an Uber driver, a field service technician may be freelancing for a number of service providers. The mobile tools must be safe, secure, and feature-rich, acting as a productive resource leveraging the same tools an FTE would have at their disposal, such as:
Some practical use cases to consider:
We work with countless Field Services organizations. One common objective shared by all has been the optimization of field services delivery. To do this effectively, Field Services organizations need to understand what to optimize for. But without having all the Field Services engagement data—from planning to execution—fully understanding the impact of such a move can be challenging.
Naturally, this has implications for other service metrics: utilization and customer satisfaction rates will fall because time-to-service increased (though field service employee satisfaction may improve).
The ability for Field Services organizations to respond quickly and make informed decisions in the face of continually changing business environments and conditions is critical. Leveraging AI, ML, IoT and AR can help by analyzing data captured throughout the Field Services Lifecyle and enabling the adjustment of service and resource models, resulting in operational efficiencies and—more importantly—greater customer satisfaction.
If you haven’t given these technologies much thought yet, it’s time to start. Industry-leading companies are already having great success with these solutions. You can, too. For more info on why the time to update your Field Service Strategy is now, please click here to read our recent white Paper: 5 Reasons to Rethink Your Field Strategy NOW.
Please don’t hesitate to contact us for more information. Our Enterprise Mobile Field Services Modernization Strategy Kickstart may be just the boost your business has been looking for.
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