The Big Discussion: Artificial Intelligence and Field Service. Part 1.

In the Big Discussion we bring together a panel of industry experts and focus on one key topic within the field service sector. In the first of a four part series, we turn our attention to AI where our panel includes FieldAware’s Mark Tatarsky and ServiceMax’s Amit Jain…


Question: Just how important is ArtificIal intelligence going to be in the future of field service?


Marc Tatarsky, SVP Marketing, FieldAware


Artificial Intelligence (AI) is already working its way into many different aspects of field service delivery today.


However, its prevalence and impact will be more influential for some field service organizations than others. It really depends on the industry served; the type of service provided as well as the complexity of the equipment serviced. AI can impact all field service delivery to varying levels.


In many instances, AI can be applied behind the scenes to improve efficiency without the end-user, even knowing it is at work.


An example of behind the scenes activity is when AI improves the optimization engine results for scheduling and routing. Even basic consumer-oriented routing systems like WAZE or GoogleMaps use varying levels of AI to help select the most efficient route.


When field service organizations are servicing sophisticated equipment monitored via IoT connectivity, AI will be applied to the monitoring and deployment process to enable predictive maintenance and automated dispatch based on AI processes and equipment tolerance thresholds.


Amit Jain, Senior VP of Product, ServiceMax


Last mile service delivery has always relied on good scheduling for field service excellence. With increasing pressure to achieve more with less and time-window/SLA expectations shortening, it is harder than ever to achieve this well without a schedule optimiser.


The best scheduling technology will not only plan accurately but also have ability to dynamically react in real-time to the progress of travel and work changes on the day. Engineer job allocation will re-optimise automatically to ensure priorities, including emergency jobs, are best met within available resources, highlighting SLA’s or appointments that will be missed so a Planner can override by exception.


This dynamic operation does not suit all service businesses and the technology is flexible. For example, many appointment based companies want the schedule finalised and ‘fixed’ for engineers the night before.


In this case the system will display real-time progress and give accurate prediction of when appointment windows will not be met or the engineer late home. By exception, the company may then decide to reassign using system recommendations.


The further importance for optimised scheduling is the ability to provide auto notification of arrival times and Uber-style tracking the engineer’s arrival by the customer on their phone. FLS were ahead when we launched this with FLS Portal last year and the function is increasingly an expectation for field service.