In a recent episode of the inService Podcast, Lexmark’s Alice Bowen and Service Council’s Gerardo Pelayo, Ph.D., shared how organizations can move toward predictive intelligence even when their data feels incomplete, inconsistent, or siloed.
Here’s how you can turn data into predictive power:
- Act now. Don’t wait for perfect data
- Deliver better service and boost customer loyalty
- Build trust in your data and scale with confidence
- Drive more revenue from existing assets
Start with what you have
Waiting for perfect data is a common trap. But progress doesn’t require perfection.
“It’s a journey,” said Alice. “But it’s one worth taking.”
Start small. Build confidence. Expand as you learn. For service teams, that might mean responding to basic device alerts. These early actions reduce downtime, improve customer satisfaction, and create momentum for more advanced predictive initiatives.
Build trust before you scale
Gerardo emphasized the importance of piloting predictive models in focused environments. By narrowing the scope, teams can avoid alert fatigue and confirm outcomes before expanding.
Lexmark followed this approach, starting with device and toner alerts and gradually evolving into advanced sensor telemetry. Each step layered data points, refined thresholds, and aligned with business goals.
Context turns data into decisions
Raw data tells only part of the story. The real value appears when it’s paired with context, like service history, usage patterns, customer profiles, and business rules.
It’s one thing to know if a device is overheating. It’s another to know who owns it, its physical location, how often it’s used, and what the client’s service agreement includes. That level of understanding turns data into decisions that drive measurable ROI.
From information to impact
If you're a service leader, operations manager, or product strategist, chances are you're already collecting data, but are you turning it into business value?
Whether you're just starting out or looking to refine your strategy, this conversation offers actionable guidance, real examples, and expert perspectives to help you see the full potential of your data.
Frequently asked questions
Is it possible to get business value from data that’s incomplete or siloed?
Yes, you don’t need perfect data to start driving results. Many service teams already have valuable data, even if it’s scattered or inconsistent. By adding context like service history and usage patterns, you can turn raw data into usable insights that reduce downtime, improve customer satisfaction, and ultimately drive more revenue.
How did Lexmark turn basic device data into a scalable predictive service model?
Lexmark started small, using device alerts to kick off their predictive journey. Over time we expanded into advanced sensor telemetry, layering learnings and refining thresholds to align with business goals. This phased approach helped build trust in the data, avoid alert fatigue, and scale predictive service in a way that supports growth and efficiency.
Why does adding context to device data matter for service decisions?
Context is what turns data into decisions. Knowing a device is overheating is helpful but knowing who owns it, where it sits, how often it’s used, and what their service agreement includes makes that insight actionable. With the right context, service teams can prioritize tasks, personalize support, and make better decisions that protect your bottom line and improve customer retention.
What will I learn from this podcast episode?
This episode of the inService Podcast offers practical strategies and expert advice for turning imperfect data into predictive power. Whether you're leading service operations or shaping product strategy, you’ll learn how to boost customer loyalty, turn operations into income drivers, and scale your data-driven initiatives with confidence.
What are the real benefits of starting small with predictive service?
Starting small, like responding to basic device alerts, can deliver quick wins such as reduced downtime, happier customers, and early ROI. These wins build trust in your data and create momentum for more advanced proactive and predictive models that can turn data into dollars and improve service efficiency.