FM Issue: Building Automation Analytics

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By Brandy Moore
From the June 2014 issue of Today’s Facility Manager

Facility management (FM) professionals are being asked to do more with less. Shrinking budgets and staffs make it difficult to keep up with the rising demands for building efficiency, comfort, and safety. Making the right decisions about where to spend time and money is critical to accomplishing these goals.

Viewing the building management system (BMS) interface from a handheld tablet device.

Photo: Siemens.com

Installing a modern building management system (BMS) that integrates all of the disparate systems to provide a holistic view of a facility is an important first step. Taking it to a higher level by using data analytics software to interpret the massive amounts of data generated by the BMS is the next. Even though data analytics is fairly new to the FM space, there are several choices available today. Having a firm grasp of priorities, budget, and staff level will help facility managers (fms) choose the right option for them and their buildings.

Best in class data analytics software automatically trends energy and equipment use, identifies faults, provides root-cause analysis, and prioritizes opportunities for improvement based on cost, comfort, and maintenance impact. This software complements BMS dashboards because it takes the critical next step of interpreting the data—showing not just where, but why, inefficiencies occur. This provides actionable information for troubleshooting and preventive maintenance as well as for solving more complicated operational challenges.

Even with ample budgets and a full staff covering a building 24/7, it is humanly impossible to gather, analyze, and interpret all of the data generated by a facility. And why would one want to do so? This would leave little to no time to do anything about the data.

Analytics software augments FM staff, helping to fill knowledge and resource gaps. More importantly, it provides prioritized recommendations for optimizing building assets. Recommendations are based on statistical analysis, performance trending, and automated diagnostics. This approach drives results that are designed to maximize building performance and comfort while lowering costs.

There are four fundamental options for incorporating data analytics: a customized solution; embedded analytics with BMS; Software as a Service (SaaS) data analytics; and managed SaaS.

Customized Solution

Building an on-site building data analytics system customized specifically for, and integrated into, a building’s systems provides fms complete flexibility on how to design and deploy the servers, software, and tools to deliver the data analytics. The downside is that customized solutions are usually more costly to deploy and maintain.

On-site software requires a custom library of automated rules and diagnostics designed for the specific equipment, environments, and situations of the facility’s operations. Since every facility has distinct characteristics, it is difficult to deploy a highly customized solution across multiple buildings or sites.

This approach also requires a person to update the software consistently to accommodate different equipment and scenarios. This requires a significant investment in IT infrastructure as well as skilled staff or vendors to build the diagnostics and maintain the data systems. To provide remote access or use web browser interfaces the software then needs to be changed to support all browser updates.

Embed Analytics With The BMS 

An emerging option in the market is to embed and integrate analytics fully into existing BMS hardware and software. This is a good choice for new construction where all of the equipment will be compatible, but it is particularly challenging with retrofits or building upgrades. Because this option is still in the early stages, there is limited functionality and availability. This might become a more viable option in the future and merits fms watching the developments.

SaaS Data Analytics

A cloud based SaaS data analytics solution is a cost-effective alternative to a custom solution. With this type of system, data is automatically pulled from a BMS and then analyzed in a virtual cloud environment. This provides fms with both the powerful insights of data analytics and the flexibility of remote access and control.

In using a mass customization approach, these subscription based solutions are more cost-effective because they use an existing, fully built library of complex diagnostics that can be modified to work for individual buildings. A good cloud based SaaS solution should quickly address user feedback and consistently deploy new versions with added features and functionality as part of the subscription service. This helps to facilitate efficient budgeting for required software upgrades as well as diagnostic improvements.

One downside to the SaaS based data analytics option is that they require staff to manage the software, interpret and analyze the data, and, most importantly, act on the opportunities identified.

Managed SaaS

An MSaaS approach combines an SaaS analytics solution with the oversight of remote engineering experts. In this scenario, remote engineers work with fms to understand their financial and performance goals. Next, remote engineering analysts use the insights from the analytics to troubleshoot issues remotely and identify energy savings opportunities, which enables them to deliver recommendations for upgrade/repair/maintenance based on the fm’s stated priorities. 

MSaaS analytics solutions breakdown.

In this quarterly analytic report, an MSaaS solution has identified facility issues. These types of reports can also include recommended actions, such as “Check AHU 4, 5, 6, and 11 for leaking cooling valves.” (Image: Schneider Electric.)

This combination of analytics software and engineering expertise can drive significant results. Fms have all the information they need, and staff is completely focused on doing the right thing at the right time.

The MSaaS analytics solution can be made accessible to all the facility’s vendors, saving them time and making building services more effective. The data can be leveraged to improve vendor management by ensuring issues are fully resolved by using analytic findings and monitoring capabilities to ensure issues do not reappear. 

Important things to look for in an MSaaS vendor include:

  • Advanced FDD Library: A robust library of hierarchical, rule based fault detection and diagnostics (FDD) that can be quickly adapted to a specific building through mass customization is a crucial feature. 
  • Detailed Reports: Regular detailed reports that prioritize fault findings based on comfort, energy savings, and maintenance impact should be available so fms can choose to fix the faults that impact business priorities. 
  • Scalability: Fms should make sure the solution is on a flexible software platform that can consume billions of data points and scale from a single building to an entire enterprise. This ensures that as the organization grows, the solution can meet its needs. 
  • Open Protocols: Open software protocols allow integration with all third-party building automation systems to maximize efficiency and ease of installation.
  • Service Support: Depending on the size of the organization, looking for a vendor with a solid industry expertise in building management, along with a global presence, could be a critical decision point. At the very least, fms should ensure the vendor they choose is a market leader that will provide a solution that continually evolves to keep up with the market changes. 

For fms who have little or no on-site staff, adding a maintenance agreement to any of these options will provide a turnkey solution. The table below summarizes these four options to help in choosing the one that is right for the budget and performance goals.

A table summarizing four options to help in choosing data analytics solutions.

Facility managers can compare the various data analytics offerings available on the market. (Image: Schneider Electric.)

Data To Drive Improvement

A sophisticated BMS generates a lot of data about a building’s performance. Reports and graphics that aggregate the data are an integral part of a system’s functionality. These data dashboards help facility staff to visualize what is happening throughout their buildings at any given time.

But dashboards tell only where inefficiencies exist—not why. The addition of data analytics software can interpret this data and convert it into actionable information so that fms can prioritize and proactively address issues for long-term solutions. Best in class solutions might include reports that provide data driven prioritization based on the goals of the customer—for example, saving energy, improving comfort, or better life cycle maintenance. Customer value reports highlight the impact of recommended changes and provide concrete return on investment information for the C-suite. These reports serve as a way for FM departments to justify continued investment in data analytics and help with overall operating budgets.

Moore is offer management director for Schneider Electric’s Global Field Services for Buildings. She has held several positions at the company, including director of global education solutions and local service manager. She holds a BS of Industrial Distribution from Texas A&M University.

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