How to Improve Field Service Operations with Data & Analytics

How to Improve Field Service Operations with Data & Analytics
Field service technicians are responsible for front-line duties that are at the foundation of day-to-day utility operations. Field technicians working to restore service and fix infrastructure in the field also serve as de facto ground-level customer support teams. Successfully supporting all of these responsibilities requires field service management to coordinate complex, interconnected service operations.

Field service technicians are responsible for front-line duties that are at the foundation of day-to-day utility operations. Field service technicians and managers support business-critical work such as:

  • Installing and connecting new network infrastructure.
  • Disconnecting and decommissioning failed or end-of-life equipment.
  • Performing regular preventive maintenance work, driven by either scheduled work or predictive analytics.
  • Responding to service interruptions and other issues in real time.
  • Interacting directly with customers in the field and responding to their service requests

Field technicians working to restore service and fix infrastructure in the field also serve as de facto ground-level customer support teams. Successfully supporting all of these responsibilities requires field service management to coordinate complex, interconnected service operations. This coordination work involves scheduling work orders, dispatching technicians, tracking shifts and labor hours, monitoring maintenance conditions, managing extensive part inventories, and much more.

All of these challenges can benefit directly from convenient field-enabled access to real-time data and analytics. Effectively harnessing and sharing field service data (for technicians and managers alike) can directly enable more efficient field service operations—and ultimately a better customer experience.

In this article, we look at some important ideas for getting the most possible value out of your field service data. Ideally, this data will be harnessed to not only support vital real-time work but to conduct historical analyses that can be used to uncover new operational efficiencies.

The Importance of Historical Field Service Data for Continuous Improvement

In our experience, stock implementations of leading Field Service Analytics source systems, like Oracle OFS, often provide a limited view of historical data. which may be suitable for quickly addressing day to day operational questions. It limits, however, this data’s potential for analysis in pursuit of continuous improvement. Furthermore, most mobile fieldwork systems tend to offer only basic reporting, which makes it difficult to derive value from captured data without the addition of analytics. Deeper historical field service analytics can lead directly to efficiencies like:

  • Reduced technician idle time.
  • “Wrench-Time” Analysis: examine how factors including experience, training, and even hiring source influence technician performance
  • Demand forecasting: anticipating impending work lulls and spikes for more proactive, responsive scheduling.
  • Aligning maintenance schedules for assets with common maintenance needs to reduce wasted effort.
  • Optimized technician travel routes.

The most impactful field service analytics should offer not only a look at recent data, but the ability to quickly expand to historical data ranges for longer term analyses. Software defaults should not dictate which data your organization can utilize.

Field Service Analytics that Deliver Mobile-Friendly Maintenance Insights

Field service analytics are essential for translating copious T&D asset data into actionable insights for field service technicians. With more connected equipment and sensors than ever, field service technicians have access to more potentially valuable data nuggets than ever.

This data needs to be carefully managed and curated, however, to offer real value to technicians in the field. Ideally, field technicians will have access to data processed into actionable maintenance insights. For example, an alert can be generated automatically when an asset exhibits abnormal behavior, when it is overdue for routine maintenance, or when predictive analytics suggest a high-risk of failure. Deloitte notes that “As predictive asset maintenance systems are able to solve routine problems, technicians will be best employed in dealing with more complex issues, such as defining strategies for managing the end-to-end asset lifecycle and extending the life of the asset.” We take a more specific look at predictive analytics for T&D asset management in our blog here.

Convenient, mobile access to these curated analytics is essential. Technicians should have the ability to see their schedule in advance, quickly access resources like work order history, and check maintenance data for any asset relevant to their work.

Process Automation for Field Service Management

Field service management demands precise administration of many complex moving parts. Many field service managers are:

  • Scheduling hundreds of technicians for critical work across multiple shifts.
  • Tracking inventories and purchasing for thousands of parts.
  • Developing and executing maintenance strategies for a broad array of equipment (including associated tasks like warranty-management).

This complex management challenge can come alongside a substantial administrative burden. Field service analytics implementations can employ targeted automation to directly ease administrative time demands. For example, the moment a technician is assigned to a work order, the relevant bill of materials for the repair at hand can be automatically generated. From there, if inventories of any associated material fall below a designated margin, an alert and purchase order template can be generated automatically for management approval. We take a broader look at the value of process automation for utilities in our blog here.

Customer Facing Field-Service Integration

Utility customers now expect more timely, accurate, and responsive communication than ever. In many cases, good communication about a service issue can be just as important to the customer as rapid issue resolution (we take a deeper look at how analytics drive a quality customer experience here).

Integrating customer-facing tools directly with field service and other utility data can facilitate precise customer updates. If a customer is waiting for a technician to arrive at their house, they can use a web portal or mobile map to track their technician’s live ETA. GPS can even provide customers with like map-based tracking.

Utilities are also increasingly recognizing that field technicians also operate as de facto customer service representatives. With more and more customer communication conducted digitally, field visits are increasingly likely to be the primary person-to-person touch point between utilities and their customers. Out in the field, technicians should be trained and equipped with the data needed to answer customer questions quickly and accurately.

Learning More About Field Service Analytics for Your Utility

Maximizing the value of your utility’s field service analytics should not require a large, complicated investment. Thoughtful configuration of the underlying data infrastructure can help:

  • Ensure flexible access to field service data from any time period.
  • Streamline sharing of field service insights with other business units.
  • Open up new capabilities like predictive asset management and field service process automation.

HEXstream has proven experience helping utilities get the most out of their data. Our work is rooted not only in technical expertise but deep domain knowledge using technology to solve business problems for some of the largest utilities in North America.

To learn more about using analytics to enhance your utility’s field service capabilities, reach out to our team using the button below.


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