The concepts behind operational intelligence are undergoing a significant transformation. No longer are we stuck in a state of being “data rich” but “information poor.” Instead, we are moving toward an era of information-driven actionable insights delivered in real time. Many industries would assert we’re already there and have been for several years.

For facilities groups, this may be manifested as analytics-enhanced reliability and predictive maintenance. For energy groups, this reality may be energy optimization and economics-based decisions for dispatch of renewable generation sources. For groups with a sustainability mission, this may take the form of monitoring and tracking infrastructure supporting measurable insights on decarbonization initiatives.

Information-Rich Sources of Isolated Data

Automated controls for systems installed in buildings, central utility plants and overall utility infrastructure have been digitized for decades now. However, this digitization is now gaining renewed momentum and even accelerating.

Countless platforms and industry offerings have flooded the market to provide best-of-breed solutions for a core need. Often, the result is a campus with various makes, models, and versions of building automation and control systems that have been put into service over decades of renovations, upgrades and new construction. Energy metering and submetering as well as lighting control systems have been installed and manage data separately. Renewables and their digital control systems as well as EV infrastructure have been added to the campus portfolio. Finally, isolated PLC and SCADA systems capture volumes of data that when combined with other data sources can contribute to the comprehensive understanding of campus operations, energy usage, optimization opportunities and overall situational awareness.

Considerations for Data Acquisition and Aggregation

It is common to find isolated control systems and a plethora of data sources across facilities within large campus settings. As these systems and sources are aggregated, a much more comprehensive understanding of overall campus operations can be gained.

In many cases, a risk-benefit analysis will result in a solid business case in support of connecting these control systems and data sources through a well-designed network tailored to specific operational characteristics while diligently applying cybersecurity best practices. In scenarios that don’t support networking and integration of control systems and other relevant data sources, processes and procedures can be established to achieve the air-gapped equivalent of data acquisition and aggregation. It is also important to keep in mind special circumstances such as the potential of creating a classified data source when combining two unclassified data sources.

Analytics Are Key to Actionable Insights

Regardless of how operational data is acquired, it is not uncommon for a significant effort to be required to produce a quality data foundation yielding valuable analytics-based insights. There is a dizzying landscape of analytic approaches and options to improve operational awareness. When combined with a solid data foundation, these approaches can deliver a new generation of actionable insights to the organization.

Over the last decade, we’ve seen facility and campus analytics evolve from basic preventive insights to condition-based insights to more advanced insights that leverage digital twins and machine learning as well as artificial intelligence.

A More Solid Foundation

Digital control and automation systems have steadily been replacing legacy systems for decades through renovations and major upgrades, often in conjunction with construction of new buildings, utility plants and related utility infrastructure on campus settings.

This has resulted in a legacy of large volumes of isolated operations data for many organizations. This data has tremendous, unrealized potential to deliver actionable insights for future system performance based on historical and even current trends.

Connecting and centralizing isolated control system, meter, and sensor data as well as other relevant and contextual data sources can serve as a solid foundation for actionable insights through applied analytics. This will take time, resources and commitment, but should be considered as a strategy each time a utility plant or facility is renovated or built. This can help any organization achieve broader goals of understanding what its operational data is really telling them — moving to a pathway of comprehensive understanding and away from uncertainty caused by lack of awareness, and setting the stage for a natural evolution toward the next generation of analytic capabilities.


With federal facilities facing stringent energy efficiency mandates, technology for advanced monitoring and diagnostics can provide much-needed visibility into whether equipment is operating outside of normal ranges.

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Richard Wendland is operational intelligence manager for the commissioning group at Burns & McDonnell. With nearly 30 years of information management experience, he specializes in management technology projects and providing technical and strategic guidance to clients. Richard manages the Burns & McDonnell partnership with OSIsoft and has overseen the successful execution of many client software and technology projects for the Department of Defense, federal agencies and commercial sectors. Richard helps clients move their organizations into more modern, data-driven operations using current technology, architectures, best practices and data and systems integration.