Field Service Innovation Starts with Solving the Data Gap
Service innovation is at the top of many service leaders’ agendas—and for good reason. It directly drives efficiency, customer satisfaction, and profitability.
One innovation generating particular excitement in aftermarket and field service is Generative AI. McKinsey projects that, over the next 12 to 24 months, Gen AI could cut content creation costs by 80%, improve operational efficiency by 30%, and automate a quarter of customer interactions. It could also increase revenues by 10–30%, increase customer satisfaction by 10–30%, and increase overall service productivity by the same margin.
These gains are especially relevant given the focus of service leaders on measurable outcomes. According to Service Council’s 2025 Key Performance Indicators & Metrics report, cost and productivity rank among the top three indicators of business health, cited by 86% of leaders—more than any other metric. Two-thirds (67%) expect investments in people and processes to have a direct impact on these measures.
Yet despite this focus and potential, a familiar barrier is preventing many organizations from turning innovation into reality: data.
Data Gaps are Holding Back Service Innovation
1 in 4
field service engineers (FSEs) can’t access the information they need.
50%
More than half of an FSE’s day is spent on paperwork and data capture instead of solving problems.
27%
of service leaders say outdated processes are dragging down performance—a four-point increase from 2023.
28%
point to inadequate data visibility, up more than five points from last year.
The message is clear: without better access to data and insights, service innovation stalls.
But before organizations can realize the full value of their data, they need to answer a fundamental question: what exactly is “field service data”?
Field Service Data: Structured and Unstructured
Structured Data: What the Job Needs
Structured data is operational and answers the what behind a service job – what happened, what (or who) is affected, and what is needed.
What happened:
What (or who) is affected:
What is needed:
Structured data is essential for understanding and assessing the state of operations, and for tracking the profitability of your service work. By giving a clear, quantifiable view of work orders, resources, and outcomes, it enables service leaders to measure performance and scale operations efficiently. It also lays the groundwork for achieving greater efficiency and cost savings through better planning, more accurate forecasting, and smarter resource allocation.
However, structured data only tells part of the story.
Unstructured Data: Why It Happened
Unstructured data answers the why behind service – why did the issue occur, what factors contributed to the issue, and how do we prevent it from happening again.
Why did the issue occur:
Factors contributing to the issue:
How do we prevent it from happening again:
Unstructured data provides the context and nuance that accelerates service performance. Issues are quicker and easier to solve, which means faster first-time fix rates, fewer truck rolls, and higher customer satisfaction. It also opens up opportunities for upselling and cross-selling, as technicians can identify where equipment is underperforming, nearing end-of-life, or would benefit from an upgrade, and can have informed conversations with customers about potential solutions.
And as workforce shortages and skills gaps continue to drive the need to train and ramp up technicians faster, having historical and visual records makes it far easier to onboard and upskill new technicians quickly.
But the challenge lies in accessibility – unstructured data resides outside of the typical legacy business management systems. It’s stuck in technician’s heads, devices, or notebooks; it’s locked in PDFs and SharePoint sites.
Where should this data be stored, and how can it be made available?
Centralizing Data with Enterprise Platforms and AI
Historically, organizations stored all their field service data in their FSM system, but this approach creates silos because important information from other systems – like ERP records, CRM data, IoT sensors, manuals, technician notes – remains isolated.
If various parts of your business are not sharing core datasets that are important to your organization, then all kinds of problems can arise. It's important to build systems with the understanding that shared data needs to exist and be served to users at the right time.
Modern, data-driven field service requires centralizing both structured and unstructured data in an enterprise platform.
Microsoft Fabric Makes it Possible
Data-Driven Field Service: A Competitive Advantage
Data-driven field service is about more than work orders and assets – it’s about understanding the entire service ecosystem. Success comes from starting with a solid primary field service application that frontline users rely on, plus the surrounding data that drives deeper insights and operational excellence.
HSO helps manufacturers and service organizations connect people, systems, and data to drive service success. Microsoft provides the framework and data foundation, while solutions like HSO’s service360 act as the glue for connecting everything end-to-end: quoting, maintenance, billing, and revenue collection – even in complex scenarios like rentals or asset depreciation.
If your goal is to transform field service into a revenue engine, the first step is getting your field service data in order. Connect with HSO to see how we can help.
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