Principal Analyst for Systems Development at JLG Industries
Event: Field Service East 2025
Resources: From Pilot to Enterprise
The session will explore how organizations can move beyond one-off AI implementations to achieve readiness for service-wide adoption. Drawing on real-world experience, John will outline the critical steps and considerations for building a scalable AI roadmap. As Principal Analyst for Systems Development at JLG Industries since 2015, John has played a pivotal role in modernizing the North American Technical Support contact center. Over the past two years, he has led the development and deployment of an AI/ML solution. In this keynote, John will discuss the journey from isolated AI pilots to enterprise-wide adoption, focusing on practical strategies and lessons learned from JLG's transformation.
Event: Field Service East 2025
Resources: Predictive Maintenance
In an era where unplanned downtime can cost industries thousands per hour, predictive maintenance is revolutionizing field service operations by leveraging AI, IoT, and machine learning to anticipate equipment failures before they occur. By deploying IoT sensors to monitor real-time equipment health and feeding this data into advanced algorithms, organizations can transition from reactive, break-fix models to proactive, data-driven strategies that reduce downtime, lower maintenance costs, and enhance customer satisfaction.
This session delves into the mechanics of predictive maintenance, showcasing how real-time analytics and machine learning enable precise failure forecasting, optimized resource allocation, and outcome-based service models. Through real-world case studies, attendees will explore successful implementations across industries, learn how to measure the impact of predictive strategies, and gain insights into overcoming common challenges such as data silos, cultural resistance, and integration complexities.
Event: Field Service East 2025
Resources: Customer Portals
In an era where unplanned downtime can cost industries thousands per hour, predictive maintenance is revolutionizing field service operations by leveraging AI, IoT, and machine learning to anticipate equipment failures before they occur. By deploying IoT sensors to monitor real-time equipment health and feeding this data into advanced algorithms, organizations can transition from reactive, break-fix models to proactive, data-driven strategies that reduce downtime, lower maintenance costs, and enhance customer satisfaction.