The conversation comes at a critical time. While predictive analytics discussions often center on failure data, Service Council research shows there is far more data generated across the service lifecycle that remains underutilized or unavailable. In fact, fewer than 3 in 5 frontline employees say they are satisfied with the completeness of the data they rely on. At the leadership level, the challenge is just as evident, with 28% of service leaders cite an insufficient digital data foundation as the biggest barrier to scaling AI initiatives.

Against this backdrop, Denise shared her perspective on how organizations can move beyond transactional service to unlock the full value of their data. Here’s a closer look at the conversation.

1. What are the biggest trends shaping service operations today?

Denise points to three key trends shaping service organizations:

• Data-driven decision-making : Organizations are moving from gut-driven decisions to insights derived from connected data across field service, inventory, and logistics.
• Customer expectations for speed and accuracy: Service teams must meet high-speed delivery and resolution demands while minimizing costs.
• Sustainability and operational efficiency : Companies are increasingly balancing service excellence with resource efficiency, including smarter parts management and reverse logistics.

These trends align closely with Service Council findings, where Service Innovation, (i.e. how service is delivered) was the most frequently cited priority, with 47% of leaders ranking it among their top focus areas.

2. What types of service data are often underutilized?

While failure data from a service event tends to get the most attention, Denise points out that much of the surrounding data is overlooked.

Some examples include:

• Inventory movements: Was the right part in the right place at the right time?
• Routing and dispatch decisions: Could transportation or scheduling have been optimized?
• Back-end processes: How are defective parts handled, repaired, or returned to inventory?

This gap between available and usable data is felt directly by frontline teams who often lack complete visibility. According to Service Council research, this lack of data completeness limits both execution and the ability to scale more advanced capabilities like AI.

Denise describes these overlooked data points as a “treasure trove” of insights that can unlock meaningful improvements when connected.

3. How does connecting data drive impact?

Connecting fragmented data across systems, from customer support to order management, field service, transportation, and inventory, unlocks powerful insights.

Denise explains that once data is unified, organizations can answer critical questions such as:

• Are we over- servicing  or under-servicing customers relative to commitments?
• Which parts are consistently being expedited, and why?
• How can inventory placement be optimized to balance cost and responsiveness?

When leveraged correctly, connected data not only reduces costs but also creates revenue opportunities, such as identifying where faster service delivery could support premium offerings.

4. What are best practices for consuming connected data?

Denise emphasizes that dashboards alone are not enough. While dashboards show what has happened, true insight comes from analyzing anomalies and aligning data with business objectives.

For example:

• Monitoring inventory carrying costs by location and movement frequency
• Identifying inefficiencies in dispatch or logistics processes
• Translating trends into actionable decisions to optimize performance and cost

By focusing on the right metrics and linking them to business priorities, organizations can turn raw data into intelligent decision-making.

5. How can data mining inspire innovation in service operations?

By mining connected data, organizations can uncover blind spots and rethink traditional processes. For example, defective parts are often shipped back for repair by default. Data analysis can reveal that in some cases, scrapping a part locally is more cost-effective than global shipping, repair, and re-import.

Similarly, modeling service costs against quality commitments allows organizations to find balance between service performance and cost efficiency. But perhaps most importantly, these insights are also fueling growth.

While efficiency has long been the primary focus of service organizations, Service Council’s in-progress research from the 2026 Service Leader’s Agenda survey, shows that 62% of leaders now identify growth as their fundamental mandate for 2026.

Denise’s perspective underscores the immense value of data when it’s connected, analyzed, and aligned with organizational goals. By leveraging the underutilized data generated across service operations, companies can reduce costs, enhance performance, and even drive new revenue opportunities.

For a deeper dive into these insights, including actionable strategies and real-world examples, listen to the full InService podcast episode featuring Denise.