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 third of a four part series on AI our panellists, FieldAware's Mark Tatarsky and ServiceMax's Amit Jain, discuss the benefits the technology can bring to a business.

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 second of a four part series on AI our panellists, FieldAware's Mark Tatarsky and ServiceMax's Amit Jain, define the difference between Artificial Intelligence and Machine Learning.

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.

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

Mark 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. 

Artificial Intelligence is going to play a significant role in many areas that are crucial to field service delivery today and moving forward—it is early stages now.  Much of the conversation in field service now is centred on two key aspects - how we drive efficiency and how we establish the 360-degree view of the customer. In each of these areas, data is an essential factor in terms of driving improvements - and having a view into asset service data is equally important.

Connected asset and service data as maintained in the field hold insights far beyond the service department, providing a better business lens for almost every other line of business. Within field service operations, a major component of any day-to-day business is the data that is used in the variety of operational processes. Field service engineers, dispatchers and managers rely on and collect valuable data direct from source and ensure its accuracy, whether that’s product status and performance, contracts, location or account details.

With the advent of predictive analytics and condition-based maintenance, this data, which can be curated and fed into an organization’s data system has the potential to provide accurate intelligence across the organization. As it gravitates towards the data lake, it can touch and enhance other data sources such as CRM, ERP, parts, logistics and supply chain, HR, compliance and even data sources such as traffic and weather forecasting. Essentially, field service and asset data gives all other data relevance and accuracy.

However, the sheer unprecedented volumes of data being generated today, which is set to continue to increase almost exponentially moving forwards, is simply too vast to be useful unless we implement Artificial Intelligence within FSM systems. This is also the case with interpreting IoT data, which is largely predicted to be the backbone of field service operations of the future, and is empowering field service organizations to move away from the traditional break/fix approach to much more effective and profitable advanced service models.

The second part of this Big Discussion will be published next week, when the pair are asked the difference between Artificial Intelligence and Machine Learning.

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