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Impact of IoT in field service management

Ganeshmurthy Bhat Assistant Vice President, Analytics, IoT and IIoT Services and Solutions
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April 10, 2017 - 

Quality product support is increasingly one of the most important after-market success drivers for today's field services businesses. Most original equipment manufacturers (OEMs) spend approximately 27 % of their overall services budget on field service operations.

The challenges facing these organizations include:

  • Knowing when physically deployment of field engineers is essential for a specific issue
  • Optimizing the cost of field engineer deployment
  • Knowing if field engineers are working according to the assigned schedule?
  • Increasing the first-time fix ratio, and reduce overall cost of fix
  • Reducing repeat customer queries on the same issue
  • Knowing the best performance management indicators or KPIs

A study by marketsandmarkets shows that the Field Service Management (FSM) market size is estimated to grow from $1.97 billion in 2015 to $5.11 billion by 2020.

But to make the most of product support efforts and unlock growth after the initial product sale, field service operations perhaps need look no further than the valuable data their machines are producing.

With so many advancements in technology related to the IoT space, fine tuning operations related to field service organizations have reached an unprecedented transformative stage.

Leveraging the technology trends in IoT (from real-time machine data to advanced analytics) for solving field service problems is leading the businesses to reinvent as predictive rather than reactive operations. This means equipping technicians with intelligence that enables them to deliver strategic decisions.

This will unlock product manufacturers ability to not only provide service at a lower total cost with greater reliability, but also support repeatable, best in class field execution practices.

Furthermore, some of innovative solutions embedded in field service operations are:

  • Job prioritization, based on criticality, enabled by machine learning;
  • Usage of augmented reality for virtual troubleshooting (thereby avoiding physical field technician deployment);
  • Field engineer/parts/tools optimization governed by statistical principles with real-time alert management (for service deployment);
  • Real-time debriefing while onsite work is in progress; and
  • Tracking of real time utilization of field technician for better productivity benefits

Impact of IoT

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This clearly demonstrates the power of industrial internet adaptation in field services will drive operational efficiencies, reduce operational risks, improve tool deployment, provide better visibility into KPIs, and improve the productivity and optimize the cost of field technicians.

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