Titled "Maximizing Advantage with AI in Field Service Operations," here's the rewritten article:
In the realm of field service, providers are eager to leverage technology to modernize age-old processes that have often hindered progress. Historically, field service businesses have operated like urgent care centers, relying on reactive maintenance when issues arise. However, post-pandemic customer expectations have evolved, and Deloitte asserts that the convergence of digital solutions and a commitment to delivering exceptional service is opening new avenues for profitability. This shift has prompted providers to reposition themselves from mere suppliers to trusted advisors.
Proactive Field Service
Innovation in field service has always been driven by a "push-pull" dynamic. Some companies push change before it's necessary, while others are pulled along by customer demand. In both cases, providers and customers have recognized that the long-term health of their assets hinges on proactive maintenance. This proactive approach is akin to routinely changing your car's oil to prevent mechanical issues. Delaying maintenance until problems arise can be costly.
Two significant outcomes of this proactive stance in field service are scheduled maintenance and intelligent dispatching. Unlike other transformative technologies, the return on investment in these areas can be immediate and substantial, resulting in increased efficiency, improved communication, and enhanced control.
Scheduled Maintenance
For far too long, field service providers (and customers) have adopted a "if it ain't broke, don't fix it" mentality. However, modern customers now expect their machinery to operate without downtime. As a result, 46% of service organizations plan to introduce or reinvent a proactive maintenance strategy to minimize asset downtime.
The benefits of scheduled maintenance are clear. For providers, this shift to a subscription-based service model leads to predictable resource deployment, steady revenue, and stronger relationships with customers. For customers, they enjoy more reliable service, reduced downtime, and lower long-term costs.
AI in Maintenance
Providers are leveraging AI and machine learning to predict equipment failures and address issues before customers become aware of them. By analyzing massive amounts of data, AI helps spot and address potential problems before they impact operations. On the human side, AI assists technicians with specialized training and provides them with more information in the field. According to Gartner, AI will significantly impact the customer service function, as 80% of customer service and support organizations will be applying AI or generative AI by 2025 to improve productivity and customer experience.
Actionable Steps
To build customer buy-in for scheduled maintenance, providers must create and share vertical-specific case studies, share knowledge via customer service channels, and equip field techs with compelling talking points. For instance, an HVAC business might use an emergency repair call as an opportunity to emphasize the importance of scheduling preventative maintenance visits.
Providers should encourage customers to contact them regarding more proactive maintenance plans and research the specific services that could benefit their local customers. They should also share examples of how certain repairs might have been avoided with more frequent maintenance visits.
Intelligent Dispatching
Ensuring the efficient and timely deployment of field service technicians is no easy feat. Managing high service job volumes, coordinating full-time employees and contractors, and juggling technician schedules present numerous challenges. According to McKinsey, more than a third of each day is lost to late starts and early finishes. Optimizing technician utilization and making informed decisions about dispatching are critical to minimizing customer dissatisfaction and maximizing efficiency.
AI in Dispatching
Intelligent dispatching employs AI-powered automation to assign jobs effectively based on considerations such as technician availability, skill sets, travel time, location, and priority. This leads to technicians working at their most productive times and being assigned to jobs that match their abilities.
Let's consider the impact of AI-driven intelligent dispatching on a summer air conditioning breakdown. Customers might Naively believe that a fleet of technicians is anxiously awaiting assignments, but in reality, field service professionals are managing complex challenges. AI-powered customizable templates facilitate real-time job assignment changes and improvements in the on-site customer experience by providing estimated arrival times, technician location, and service history.
Taking Action
Begin by analyzing current operational stressors and pain points to develop a foundation for identifying AI-driven process automation opportunities. Establishing those foundations will help you understand where technology can be most impactful.
By embracing AI-driven scheduled maintenance and intelligent dispatching, field service companies can proactively maintain equipment, optimize dispatch processes, and improve overall operational efficiency, resulting in enhanced customer satisfaction and reduced costs.
Anand Subbaraj, the Deloitte Global Practice Leader for Enterprise Operations and Sustainability, advocates for the convergence of digital solutions and exceptional service as a means to drive profitability in the field service industry. In the same vein, Anand Subbaraj highlights the importance of using AI and machine learning to predict equipment failures and provide specialized training for technicians, which can significantly impact the customer service function.
