Don Ryan

Predictive maintenance technology is widely deployed across energy, chemicals and oil & gas, but for many teams, the results still fall short. The issue isn't the data or the sensors. It's what happens after an insight surfaces. In this session, we will dive into the importance of moving from alert-generating to outcome-driving by building the ownership structures, response workflows, and internal buy-in that make predictive programs actually perform.

• How high-performing reliability teams structure alert ownership so insights don't stall between departments
• The workflow design that scales consistent maintenance response across multiple sites and asset types
• How to translate predictive data into the financial and operational language that earns leadership alignment
• Lessons from the field: what adoption really looks like inside an industrial organization and what slows it down
• A practical framework for moving from a technology-first program to a reliability-first culture with measurable uptime and cost avoidance results