Business
Technology

AI in Field Service Management: How to Stand Out From the Crowd

Although the many benefits of AI are just being realized, there are several simple and accessible methods to utilize the technology that already exist.
By Marne Martin
April 30, 2019
Topics
Business
Technology

Artificial intelligence (AI) solutions are here, and their presence is being felt in all industries. Put simply, they enable human workers to focus on complex problems that demand a personalized service, while they take care of repetitive, automated activities. AI solutions are now beginning to influence field service management processes. Here are three areas of field service where intelligent solutions are already delivering real business value.

1. Solving complex scheduling

In the case of scheduling technicians in the field, the constant numerical challenge of optimally adjusting a schedule can become a complex and challenging task for human workers to handle. Manual or traditional software-based scheduling may work for service organizations with a very small number of technicians engaged in a small number of jobs, but it doesn’t take many technicians or jobs for the number of possible solutions to outstrip human computation capabilities.

Even at the bottom of the spectrum, problems can be too complex for any human dispatcher or customer service agent to quickly identify all the possible solutions and pick the best one. This becomes even more difficult as unexpected factors such as emergency jobs, SLAs, technician skill sets, or tools and materials in stock on each service vehicle come into play. A dynamic scheduling engine driven by AI algorithms, however, can solve complex scheduling problems in real time, making adjustments based on priorities outlined by service organization management and real-time information. Human dispatchers can then manage by exception and deliver meaningful communication to help improve customer relationships.

2. Enhancing customer communication

The initial interaction a customer has with a service organization tends to involve several lapses in communication—with on-hold wait times a primary culprit. In addition, customers are reaching out via email, chat and social media, and communication becomes disjointed when these data streams drop into disconnected siloes.

Today, AI solutions can solve these problems. Intelligence software tied into chatbots can learn the appropriate answers for each customer question, automating a significant majority of chat interactions. A chatbot can be taught to answer common queries about when a technician is scheduled to arrive, for example, providing customers with a convenient digital experience while enabling call center agents to deliver personalized service.

Typically, AI alone can handle between 50%-60% of requests, but if an AI chatbot cannot answer a question, a human agent can take over the discussion thread without missing a beat. This should be seamless for the customer and internal customer service, ticketing and support systems.

A major benefit of this AI functionality is that it learns from human answers and gets better at answering questions. Integration between an AI chatbot, email, voice, social and enterprise applications is also critical because it enables one version of the customer record. Without this, a customer can send an email, send a message on social media, call and sit on hold, and still not get a response. Each interaction may not appear in a central customer record, despite three attempts have been made to contact the company.

3. Enabling true management by exception

For service organizations, a primary ROI driver of AI applications is that humans can manage by exception. High volumes of activity can be automated, with human intervention limited to when situations occur outside business rules or logic built into service management software. AI doesn’t eliminate the need for human interaction; it allows humans to do what they do best—handle escalations and complex decisions for unique cases.

Management by exception is more successful when an AI application has access to extensive information about each customer. Therefore, full integration with enterprise resource planning, field service management and other enterprise tools is key. AI tools can be more effective if they hold more rather than less information on the status of the customer’s account—such as their maintenance or service history, warranty or service level agreement entitlements.


Planning and optimizing a field service schedule in real time is a complex task for the human mind.

Don’t miss out on the rewards of AI

Service organizations would be foolish to ignore the massive potential of AI solutions. Intelligence software capabilities can help organizations revolutionize their business operations to stand out from their competitors. The number of ways AI can be deployed to ease the burden of delivering the best possible service in an increasingly changing environment is just being realized, but there are several simple and accessible methods that already exist—meaning service chiefs can embrace this game-changing technology today.

by Marne Martin
Marne Martin is President of IFS Service Management and CEO of WorkWave. An experienced executive, her focus is to continue to elevate the strategic importance of service management to the success of the overall IFS business. She is a winner of several awards including 2016 CEO Gamechanger of the Year (FSM) from ACQ 5 Global Awards and 2015 Field Service CEO of the Year from Executive Awards. She holds a master’s degree in International Management from ESCP Europe.

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