Building Management Systems (BMS) offer facility managers many advantages, including intelligent information about a facility's operational performance and energy use that can help identify root causes and correct deficiencies in buildings.
By harnessing building data properly, facility owners and operators can better realize the full return on their BMS investment as they save energy, reduce operating and maintenance costs, and improve building comfort. But in order to realize these returns and leverage the full power of their BMS, building operators need significant training, in-depth understanding of their facilities and often additional tools to aggregate and make sense of the growing volume of data in a timely manner.
Over the past decade, several types of tools have come onto the market to fill this need, from dashboards to automated analytics to machine learning optimization engines. Each of these tools fulfills a different objective to help facility managers in their day-to-day operations and long-term planning. However, much like the sophisticated BMS platforms available today, each tool requires training and time to learn how to use it, along with an investment in I.T. infrastructure and support, to achieve its full benefits.
Research shows that only about 20% of facility managers use 80% of the available capabilities in their BMS. The remaining 80% use a very limited amount (20%) of the potential functionality in their system. Personnel turnover and competing facility-management responsibilities (janitorial, construction management and general repair) leave many facilities without the luxury of well-trained teams with adequate time to learn the full capabilities of these tools. Outsourcing different functions is one way to overcome these issues. But vendors must be managed closely in order to ensure effectiveness and outsourcing can be expensive if vendors spend significant time on site.
Combining the right tools in remote, cloud-enabled managed software as a service (MSaaS) may be a better fit. The combination of the right diagnostic data and expert engineering insight can help facility managers:
• better understand how their buildings are performing
• maximize the return on building management and metering investments
• overcome training challenges
• reduce outsourced vendor management and costs
Today's building management challenges
Today's facility managers face a myriad of challenges that not only make it difficult to operate a building efficiently, but also increase the risks to the facility, especially in aging buildings. It is estimated that 75% of the buildings that will be occupied in 2050 have already been built today. This means that with little or no new construction on the horizon, building managers must create greater efficiencies in existing facilities.
Reduced budgets force building owners to manage sophisticated building systems with fewer resources, an issue further aggravated by older systems becoming inefficient over time. And even when there is sufficient budget, it is increasingly difficult and time-consuming to hire, develop, and retain staff with the skills and knowledge to take advantage of BMS capabilities.
Facility managers also face the challenge of an immediate and continuous decline in existing equipment performance. Components break or fall out of calibration, and general wear and tear often leads to a rapid decline in a building's operational efficiency. Changes in building use and occupancy can contribute to indoor air-quality problems, uncomfortable environments, and higher overall energy costs. These changes begin immediately after construction is complete.
So what other options exist to help facilities become part of the 20% that get more out of their investment in building management systems?
Turning BMS data into actionable information
Many facility managers are turning to data analytics software that allows them to interpret massive amounts of BMS data. Best-in-class 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. Data analytics software complements BMS dashboards because it takes the additional step of interpreting the data—showing not just where but why inefficiencies occur. Engineers then convert this intelligence into “actionable information” for troubleshooting and preventative maintenance, as well as for solving more complicated operational challenges. The software augments building management staff, helping to fill knowledge and resource gaps. More important, it allows facility managers to proactively optimize and commission building operations more effectively than with a BMS alone. Understanding why a building is operating efficiently (and why it is not) leads to more-permanent solutions.
A core feature of the most advanced data analytics software is a process referred to as automated fault detection and diagnostics (aFDD), which identifies problems and recommends opportunities for savings without any human intervention. The most effective aFDD platforms use robust hierarchical, rule-based diagnostics to identify faults, diagnose mechanical systems, and determine the cost or savings incurred through making repairs, improvements, or upgrades to a building’s systems or operations.
The actionable intelligence from data analytics provides facility managers with clear, prioritized recommendations for optimizing assets. The recommendations are based on statistical analysis, performance trending, and automated diagnostics. This approach drives results that are designed to maximize building performance and comfort with cost savings that further maximize the return on investment (ROI) associated with a BMS.
For instance, with data analytics, facility managers can proactively identify operational problems such as equipment that needs to be repaired or replaced before critical failure. Building managers can schedule repairs before an emergency arises, thus eliminating costly replacement and avoiding failure and downtime. With this proactive approach, equipment becomes more reliable, the cost of replacement and repair can be much lower, and occupants are assured of optimal comfort.
The use of data analytics helps facility managers keep maintenance objectives on track and provides transparency into the performance of aging and upgraded equipment. Maintenance becomes more predictive, and operations and performance become more reliable—creating greater peace of mind. In addition, aFDD findings and documentation can be used for measurement and verification (M&V) to meet green building certifications.
SaaS: a cost-effective, more efficient option
Some facility managers choose to build their own on-site building data analytics system that can be customized specifically for and integrated into their building’s systems. This gives building managers the greatest flexibility with the system, as they have exclusive access to all the servers, software, and tools. But a custom-made solution can be a costly option.
On-site software can be expensive because a library of automated rules and diagnostics needs to be built from scratch for the specific equipment, environments, and situations of a particular building’s operations. Since every facility is unique, this makes the system more difficult to deploy across multiple buildings or sites: the library of rules would need to be constantly updated to accommodate different equipment and situations. Not only does a custom-built solution require an investment in the IT infrastructure, it also calls for highly skilled staff or vendors to build the diagnostics and maintain the data systems. Further, customized systems rarely allow remote access or utilize web browser interfaces because of the high cost of keeping up with web browser versions and rapidly changing IT to combat security threats.
A more cost-effective and efficient option is a cloud-based software as service (SaaS) data analytics solution. Data is automatically pulled from building management systems and analyzed in a virtual cloud environment. This gives building managers both the powerful insights of data analytics and the flexibility of remote access and control – anytime, anywhere.
Leveraging a “mass-customization” approach, these subscription-based solutions cost less to deploy because an existing, fully built library of complex diagnostics can be customized to individual buildings very quickly. Additionally, the pace of technology change is so rapid today that on-site solutions may become antiquated very fast. Cloud-based SaaS solutions can react to customer feedback and constantly deploy new versions with added features and functionality continuously, at no additional cost to the user. Software upgrades and diagnostic improvements are also cost-effective and predictable, budgetable expensed because they are included in the subscription.
An emerging option is to fully embed and integrate analytics into existing BMS hardware and software. Embedding analytics is particularly challenging with retrofits or building upgrades, but it works will in new construction. Because this option is still in the early stages, there is limited functionality and availability today.
MSaaS: add expert insights and support for a complete solution
SaaS-based data analytics solutions reduce setup and ongoing maintenance costs, but they still require staff to manage the software, interpret and analyze the data, and, most important, act on the opportunities identified. In order to maximize their investment, facility managers have the option to choose a managed software as a service (MSaaS) as an analytics solution, which combines the SaaS analytics solution with the oversight of remote engineering experts.
Remote engineers work with facility managers to fully understand their priorities, budgets, financial goals, and performance objectives, so building management can be viewed within the context of the overall business. Using insights from the analytics, remote engineering analysts monitor, detect, diagnose, and identify energy savings opportunities and use building data to understand why building issues are happening and deliver recommendations for upgrade/repair/maintenance based on business priorities.
The combination of analytics software and engineering expertise can drive measurable results, such as up to 30% reduction in HVAC systems energy costs, which enhancing building comfort and preventing premature equipment failure. Persistent, costly inefficiencies can be resolved, which drives a greater return on investment. Remote engineers also eliminate the need for additional staff resources, allowing internal teams to focus on their core day-to-day responsibilities and also focus on repairs/maintenance with highest impact.
Additionally, an MSaaS analytics solution can increase the efficiency of vendors and partners by consolidating and integrating data from various building systems. This data can then be made accessible to all 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 utilizing analytic findings and monitoring capabilities to ensure issues do not reappear.
Schneider practices what it preaches - and saves money
A Schneider Electric manufacturing facility in Seneca, South Carolina, realized an 83% decrease in avoidable HVAC energy costs through its own building analytics solution, for an annual savings of $9,000 (€6,525). The solution paid for itself during the first year by providing automated, sophisticated analysis of root-cause inefficiencies.
Instead of facility manages relying primarily on monthly checkups to track performance, comfort levels, and maintenance and energy data, the solution automatically analyzes the 280,000 ft2 (26,013 m 2 ) plant’s data every five minutes. The analytics was able to diagnose and troubleshoot HVAC problems the facilities staff didn’t even know they had.
The Seneca plant has seen a 29% reduction in the number of maintenance incidents, and comfort incidents decreased by 33%.
Choosing a MSaas analytics provider
To achieve these kinds of results, building managers can partner with an MSaaS analytics provider and maximize the value of their data analytics technology. The following checklist outlines the critical functionalities and capabilities to look for in an MSaaS analytics solution vendor.
- Advanced FDD Library - A robust library of hierarchical, rule-based fault detection and diagnostics (FDD) that can be quickly adapted through mass customization is a key feature in MSaaS analytics solutions. Adding these essential functionalities later may result in significant additional costs.
- Detailed Reports - A comprehensive solution offers regular detailed reports that prioritize fault findings based on comfort, energy savings, and maintenance impact.
- Scalability A flexible software platform that can consume billions of data points – from a single building to an entire enterprise – enables cost efficiency and better building management as an organization grows.
- Open Protocols - Open software protocols allow integration with all third-party building automation systems to maximize efficiency and ease of installation.
- Global Presence and Service Support - Proven industry expertise in efficient building management, along with a global presence, enables seamless services across an enterprise. BMS, building analytics data software, and MSaaS analytics solutions are continually evolving, so it is important to partner with a market leader that understands and evolves with industry demands.