Rapid data center expansion and ongoing technician shortages make traditional, calendar-based maintenance unsustainable. Relying on rigid service schedules increases operational complexity, inflates expenses, and heightens the risk of human error outages.

This whitepaper details how transitioning to systemic, AI-driven Condition-Based Maintenance (CBM) de-risks operations. Featuring real-world data from Compass Datacenters, it demonstrates how digital twins and predictive analytics optimize resource allocation across your power and cooling infrastructure.

Download this whitepaper to discover how to:

• Lower total cost of ownership by up to 20% through predictive data-driven intervention timing
• Reduce intrusive on-site visits by 40% to ease technician shortages and minimize human error
• Optimize energy consumption and extend asset lifespans across mechanical and electrical systems
• De-risk infrastructure transitions using digital twins and systems-wide predictive analytics