Buildings management is increasingly more data-centric. The advent of direct digital controls three decades ago has given way to feedback signals from most devices installed in buildings. In buildings, a vast array of digital devices now provides signals about the operations, use and well-being of everything from space and elevators to engineered building systems. An enormous range of sensors constantly produce data from lighting, occupancy sensors, security, HVAC, electrical plug loads and meters across varied utilities, to name a few of the sources. While information from individual devices and systems can help you improve that system’s efficiency, there are additional lessons to be learned across

systems through analytics and event correlation. The key is integrating signals from disparate components into a system of systems, and reporting correlations to the operations teams that maintain them. The point is that big data is good, if expertly managed and applied to management decisions and followed up with actions. But information overload can be a problem when data volume is exploding. Without a link to prioritized actions, signals are just noise. Modern data management and analytics not only monitor and make sense of the data from all the components and conditions within buildings as an integrated whole, they are valuable for prioritizing alerts and actions on the basis of criticality, cost, or both.

Summary lesson: Most enterprises don’t see or take advantage of the data they have as well as they could. Even though buildings produce a lot of data, it is not always easy to use. Just because you have data doesn’t mean you can work with it or draw any meaningful conclusions from it. Data focused on individual systems and invisible or lost data means that vital information is not available to management charged with business outcomes. In many cases, isolated information and current practices result in unintended energy waste and inefficiently occupied space. To harvest intelligence and new value from these varied data sources, the data must be aggregated and expertly analyzed against key performance indicators. Management requires new data tools to harvest hidden value from existing devices and occupancy patterns.

An example of this is how US General Services Administration (GSA) is applying a new data management system to facility management. It uses a single integration solution to capture and normalize huge amounts of data from a broad range of building types, control systems and assets. Analytics of the data reveals actionable opportunities for significant energy and operations savings.