One of the core precepts of business profitability is planning ahead, so needs and expenses are anticipated. Otherwise, you’re constantly “putting out fires,” which is inefficient—and costly.

For facility managers, planning means having a comprehensive operations and maintenance (O & M) plan for your buildings. It dictates the strategy for maintaining and extending the service life of critical (and typically expensive) building systems such as HVAC. Establishing and following an O & M strategy can help prevent the breakdown of these systems at inopportune times and ensure they are operating at peak efficiency.

Most building managers have a plan already in place, but when was the last time you evaluated it? In this article, we’ll look at how modernizing your O & M strategy with the Internet of Things (IoT) offers an opportunity to increase the efficiency of operations and maintenance in facility management—and deliver cost savings to improve bottom-line profitability.

Want a partner to help you integrate IoT technology into your O & M plan? Schedule a free Discovery Call with Iota and let’s get started.

Traditional Operation & Maintenance Planning For Buildings

The O & M strategy for any large or complex facility covers (at minimum) the following three areas:

• The maintenance strategy—The O & M plan dictates the schedule for routine maintenance of HVAC, fire suppression, plumbing, and electrical systems, as well as elevators and motors for other equipment within the facility. Regular system checks and maintenance help to avert system failures that can disrupt operations—or worse, pose safety hazards to building occupants. Traditionally, a preventive maintenance approach relies on manufacturer’s recommendations for maintenance procedures and frequency.
• Emergency plans—An O & M plan should lay out procedures to follow in the event of a system failure. Even with good maintenance, the unexpected sometimes occurs; having an emergency plan in place is crucial for minimizing disruption and providing for the safety and comfort of building occupants. One hospital that neglected to properly maintain a large compressor worth several hundred thousand dollars suffered a failure during the summer, when the weather was hot and demand for cooling was high. To continue operations, the maintenance department leased industrial-sized emergency compressors until the malfunctioning compressor could be replaced. (In this case, the emergency cost much more than maintaining the compressor.)
• Budgeting—The O & M strategy should also include budgeting for the maintenance and repair of equipment, and its eventual (inevitable) replacement. Every piece of mechanical equipment has an expected life span that varies by type and service load; that life span should be tracked, whether it’s five, ten, or 20 years. If a compressor has a service life of 20 years, funds should be allocated annually starting in year one to a capital replacement account in order to avoid trying to fund the replacement in the last useful years of service. Accurate budgeting can help avoid major disruptions and the sometimes exorbitant costs of having to replace something unexpectedly.

[bctt tweet=”An O & M plan should lay out procedures to follow in the event of a system failure. Having an emergency plan in place is crucial for minimizing disruption and providing for the safety and comfort of building occupants.” username=”iotacomm”]

Up to this point, preventive maintenance and traditional emergency planning and budgeting have all been adequate in minimizing failures and managing building assets. Today, it’s possible for facility managers to adopt a more proactive strategy with regard to building management: predictive maintenance using the IoT.

A Modern Approach To Operations & Maintenance In Facility Management

Predictive maintenance is an advanced strategy that uses data analytics to drive decision-making with regard to O & M. It allows facility managers to design an O & M strategy that relies less on predetermined manufacturer’s recommendations for maintenance and more on real-world performance data of machines and equipment. The result is a better understanding of your building operations, faster identification of issues and failures, and better budgeting for future needs.

A modernized O & M strategy looks more like this:

• Maintenance strategy—In contrast with the preventive model, where manufacturer recommendations provide the guidelines for maintenance, a predictive maintenance approach uses IoT sensors to monitor machinery and systems. These sensors provide real-time data about power usage, temperature, vibration, and other parameters, so operations managers can verify all machinery is operating within normal ranges and give priority to those areas where attention is needed. This more effective maintenance routine makes better use of resources and saves time.
• Emergency plans—Rather than hoping that regular preventive maintenance will reveal major issues with equipment, continuous monitoring can pinpoint when a piece of equipment is likely to fail so you can address it before it happens. With the help of machine learning and algorithms, IoT data about your equipment can be mined and patterns identified. Eventually, that data can be used to provide valuable insights about aberrant performance that could indicate the likelihood of an imminent breakdown, helping, in some cases, to avoid having to put costly emergency plans into action.
• Budgeting—Complementing the traditional method of budgeting, IoT sensor data provides additional information that allows you to more accurately budget for future needs. Plus, early detection of problems can help you lengthen the lifespan of your capital equipment.

Ready to update the operations and maintenance plan for your building?

If you’re ready to start gathering IoT data as part of your new O & M strategy, get in touch with us at Iota.

We can help your company get all the information you need from your important assets so you can predict and prevent failures before they happen. We also offer a subscription-based service of predictive analytics and machine learning algorithms designed to help you optimize equipment performance through fault and anomaly detection. Contact us to get started with monitoring and management today.