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In today’s technological era, data science is playing a critical role for making decisions and supporting management and engineers to achieve the optimal solutions based on technical and financial analysis. The data can be defined as facts or numbers that is usually collected, analyzed and utilized to make useful decisions. On the other hand, information is knowledge that is obtained from data through analysis and studies. With newly developed high tech and IT solutions such as IR4.0, IoT and other applications, data is coming more important and useful in reliability engineering applications and science.

Talk to a maintenance lead at any enterprise and the same theme comes up: they know their team generates real value, but they struggle to make it visible in numbers the CFO trusts. The operational story the data tells is not what actually happens on site. Notifications come in half-filled, time bookings get rounded to the hour, schedules live in Excel and reconcile to SAP once a week, and downtime is not assigned to the correct entity. That gap between reality and SAP (the world's most popular EAM platform) is what makes maintenance look like a cost line in the budget even when it is carrying revenue, reliability, and labor productivity.

Resilience is easy to talk about and hard to deliver. For water and wastewater utilities, it means sustaining safe, reliable service despite aging assets, workforce transitions, regulatory pressure, and increasing operational risk. That is exactly what the Water Industry Reliability Forum set out to unpack in a practical way during the Reliability Conference, in a full-day workshop co-hosted in collaboration with MaxGrip and Reliabilityweb. This is a recap of those sessions and discussions with the audience.