August 2012

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Using Data Analytics to Improve Facility Performance

A Path to Fast Financial Returns
John Petze

John Petze,

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Buildings owners are being presented with a wide range of options that promise to help them reduce energy and operating costs. The vast majority of these require significant capital investments. Many are what you would call “big projects” – lots of engineering, significant time required to deploy, and big financial commitments before any benefits will be realized.

Yet one of the most effective ways for facility managers to reduce costs doesn’t get delivered by a truck and doesn’t require a huge capital outlay to start generating savings.  The option I am referring to is using data analytics to identify operational issues that have the most immediate and significant financial benefits.

Analytics technology is fundamentally changing business and society bringing us to levels of efficiency not previously attainable. Analytics is being used by police departments to improve crime prevention and response, its being used in health care to improve diagnosis and treatment, and of course it is being used all over the web to improve sales results by more effectively identifying customer needs and buying behaviors. It’s only logical that we should be using this new technology to better operate our buildings. That’s the role of “operational analytics” and the great thing is that it’s easy to get started with analytics in our buildings.

Analytics Will Identify Waste and Inefficiency
Analytics show us how our buildings really operate (not how we think or hope they do), identifying exactly where opportunities for savings exist. Analytics software automatically analyzes operational data coming from equipment and control systems and identifies patterns that represent waste, equipment faults, deviations from desired performance, and opportunities for savings. The results enable you to know where to focus to drive operational improvements that reduce costs. Simply put, analytics enables you to turn the data from your building systems into money.

Analytics Can Deliver Fast Results
Unlike energy conservation measures that involve the installation of major capital equipment, you can start small with analytics and generate returns in a very short period of time. The results from those initial analytics generate the savings to go deeper into your operational data. Let's look at an example…

Let’s say the only data I can easily access is my interval meter data (kW demand), which is provided once per day by my utility company, and a list of occupancy schedule times in an Excel™ spreadsheet. Can I gain any valuable insight from that little amount of data? The answer is a resounding YES!  With just that limited amount of data SkySpark can identify:

- Buildings starting early
- Buildings running late
- Buildings that operate continuously
- Demand peaks that occur outside of occupied times
- Peak Load, Annual & Monthly and Short Load Durations

Here’s how. With typical energy analysis tools I can identify my kW demand pattern for each day. By looking at it manually I can assess whether the pattern follows expected occupancy times. But who has time to do that manually? I don’t! 

kW Demand Pattern

The solution – an analytics rule looks for a percentage change in kw demand at the transition to and from occupancy. The rule identifies when buildings run late, and start early. A weekly view shows how many times the issue has occurred and even calculates the cost of those events. Analytics takes me right to the issue. There’s no need to hunt through the data manually!

contemporary Delivering Financial Returns
Analytics delivers real, financial results and rapid ROI. Here’s another real world example based on a simple issue that many buildings have –equipment operating outside of occupancy times.

The Business Issue: Exceptions happen – buildings need to be put into override mode for a variety of reasons – but how long do they stay overridden and how much does it cost? Do they get put back in automatic mode?

The Solution – An analytic rule tracks the hours sites are in override mode. Auto-generated reports provide managers with a clear view of the number of hours of override by site and across the portfolio with costs.

The Result – Analytics produces actionable information that is being used to drive reductions in energy costs projected at $1.8 million annually across 925 sites through changes to operational practices to address just this one issue.

The important story here is that analytics doesn’t have to be complex or expensive to start delivering actionable information and tangible results. It’s the optimal way to take advantage of the wealth of information in your equipment systems to drive energy and operational improvements.

About the Author

John Petze, C.E.M., is a partner in SkyFoundry, the developers of SkySpark™, an analytics platform for building, energy and equipment data. John has over 25 years of experience in building automation, energy management and M2M, having served in senior level positions for manufacturers of hardware and software products including Tridium, Andover Controls, and Cisco Systems. At SkyFoundry he rejoins Brian Frank, co-founder and chief architect of Tridium’s Niagara Framework, as they look to bring the next generation of information analytics to the “Internet of Things”.


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