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The internet of things, big data, machine learning, artificial intelligence, smart buildings. Even for those in the industry, it’s hard to tell what’s real and what is just hype.
One thing is certain. Commercial real estate companies are deploying technology today that is revolutionizing how they manage their assets.
In many sectors, automation spells disaster for the jobs that have traditionally driven the industry. However, in building operations and management, few see technology as a replacement to existing jobs. Instead, as Karen Whitt from Colliers stated, “While the applications of AI in commercial real estate are exciting, they won’t be a panacea for building management. AI likely won’t enable building owners to cut staffing levels in half or ask a digital Jarvis to fix a broken cooling tower.”
But broken cooling towers do need to get fixed, and faster than before due to competition. Industry leaders are already testing and adopting technologies to improve their operational efficiency, and ultimately, stay financially competitive in an increasingly competitive market.
Without robots capable of replacing skilled technicians, how are existing technologies making building operations and management easier and more effective?
The professionals in charge of operations for an entire portfolio have a tough job. They get calls every day from the managers of dozens of different buildings about a wide variety of issues. Not only do they need an in-depth knowledge of building systems, they need to know the specific building conditions and manager efficacy of each property.
While difficult, this is manageable for the most part. In many cases, the managers have years, or even decades of experience and are competent professionals.
Still, even experienced portfolio managers don’t know how well (or poorly) their property managers are running the buildings under their purview. It’s not due to a lack of competence; it’s simply a lack of data and transparency. There is no baseline for how long a piece of equipment should last, how much energy critical building systems should be using and what they should cost to run, or how much time on site teams spend to track down the root cause of tenants complaints. While this seems somewhat novel today, it’s hard to believe that such valuable assets are being run without this information readily available.
When managers have 20+ years of experience, talent might make up for the short coming in data. But a lot of companies are beginning to plan for the generational turnover of their managers. The upcoming crop of building managers will have to do more with less and will rely on technology to do their job. Top talent will seek employment at companies with tools already in place. A quick tour around the boiler room and electrical closets simply won’t cut it in today’s increasingly competitive CRE industry.
So, how is technology helping today and enabling companies to plan for tomorrow?
Decreases in costs and advances in the precision of equipment submetering and environmental sensors (IoT) are enabling buildings to produce massive amounts of real-time data around how their equipment systems are performing and the conditions that tenants are experiencing. On the back end, cloud computing is allowing for robust analytics (big data) to detect issues as they happen, and even “learn” (machine learning) equipment profiles to predict issues before they occur. This creates the conditions for buildings to “talk” to operators and inform decisions towards better management using data (smart buildings).
However, just because data and analytics exist doesn’t mean that portfolio managers are going to go from working hands-on with equipment and staff to sitting behind a desk just so they can pour over analytics. Instead, the solutions that the real estate industry leaders are adopting are based around actions supported by analytics.
For example, condition-based maintenance is beginning to substitute preventative maintenance. This “smart” maintenance strategy uses continuous tracking of every aspect of the operations of a building and notifies operators when maintenance is required, such as when a piece of equipment is veering off normal parameters or has failed entirely. When this happens, operators are provided a series of data-driven recommendations, product specifications, clear diagrams of the relevant power infrastructure, and basically everything one could need to quickly troubleshoot an issue once detected.
This setup does not require managers to be viewing the analytics involved in fault detection, only for them to respond to the output. Because the output is specific to individual systems or pieces of equipment, time is saved by shifting human labor away from investigation and towards implementing solutions. In addition, by reducing the amount of preventative maintenance checks required, time is made available to perform more high quality, longer lasting solutions to performance issues.
For building operators, reviewing the problems that have been detected across a portfolio allows them, for the first time, to allocate staff and resources based on data. This also shows the operator how well their building managers are responding to issues, and whether maintenance is acting as a band-aid to a problem or is a long-term solution. Lastly, by looking closely at recurring issues, directors can carefully plan for equipment replacements and upgrades.
Moreover, as the older generation of building managers retire and the younger generation needs to be educated, using data about which issues are most common can streamline the training process. Instead of answering the same issue multiple times, operators can focus their onboarding to get managers operating effectively in the shortest amount of time.
Although building managers will be most aided by actionable insights, the availability of analytics does provide a welcome infusion of data to the strategic decision-making process of operations and engineering executives.
When looking at the portfolio level, it is difficult to balance cash flow with equipment repairs and replacements. Major capital expenditures, such as replacing a boiler or chiller, can hurt a property’s ability to make tenant-facing investments and renovations. Beyond that, the annual energy cost for operating a chiller can be as much as one-third of its purchase price, so understanding how to balance short-term and long-term costs is crucial.
Armed with data, an operator may opt to pay more upfront to save money in the long run. For example, it costs an extra $6 per ton for each 0.01 kW/ton improvement of the efficiency of a 500-ton chiller. Going from 0.60 kW/ton to 0.56 kW/ton would increase that machine's initial cost by $12,000. But it would also reduce operating costs by $3,000 per year, yielding a four-year simple payback and add up to $48,000 in savings over the unit’s 20-year life span. Despite the increase in CapEx, the resulting decrease in net operating income for the property is often a compelling data point.
Being able to visualize the equipment system processes can provide insights that save buildings hundreds of thousands of dollars. Visualizing what has changed in specific equipment processes, such as chillers alternating, and why changes have occurred are truly a sea change in the way buildings are managed.
Ironically, while improvements in IoT and big data will not replace human jobs in the foreseeable future, it may replace existing technology. Some operators and engineers are realizing that they do not necessarily need an expensive building management system (BMS).
Using existing (and very new) technologies, operators can use run-time analytics and dynamic comparisons on a variety of dimensions to manage their buildings more cost effectively than a half million-dollar BMS can.
For buildings with a BMS already in place, it makes sense to add a layer of transparency via data derived from meters and sensors. Sometimes, poorly programmed BMS are the cause of wasted operating costs in buildings (and can even cause buildings to use more energy had the BMS never been there!). By comparing schedules to actual occupancy rates, operators can align greater control with optimization. For office and multifamily properties that don’t have a BMS, it is becoming clear that a building monitoring system focused on operations performance can enable operators to manage their equipment efficiently, for a much lower cost.
The effectiveness of BMS schedules is not the only area that technology is providing transparency for. Because so much of the real estate industry is still managed out of manual spreadsheets (around 33%), the budgeting process is often opaque, even for director-level management.
Instead of asking accounting for financial reports, operators are now able to pull up-to-the-minute reports themselves. For example, the cash flow of a property can be heavily affected by the cost outlay recovery for utility submetering. The ability to view invoicing and payment data in real time can have a dramatic effect on portfolio managers’ decision making.
Being able to access budget data helps in two ways: First, operations management is a dynamic process that often requires quick decision on where to allocate costs. Waiting on reports from accounting takes too long to act in the small window available.
Second, strategic decision making and P&L responsibilities are not just for this quarter, it’s for the next 5-10 years. Without being able to analyze costs dynamically for different time periods and relative to circumstantial conditions such as weather, it is impossible to make informed decisions.
As cities take stronger positions and create more demanding requirements for building operations and energy use, owners and operators need a better way to respond in real time.
Many cities today have benchmarking requirements. This can be a costly and time-consuming process if third party vendors need to be contracted to perform audits and prepare benchmarking reports. In this scenario, physical and digital technologies are replacing human jobs. When energy consumption is tracked continuously, benchmarking is simple, automated and very inexpensive.
Another example is demand response or interruptible gas programs from utilities. For those unfamiliar, these programs incentivize participants to reduce consumption or change fuels during peak times to lighten the grid’s overall load.
If lower energy costs are the carrot for these programs, severe penalties for non-compliance is the stick. In New York, there is a $20,000 fine for not switching to fuel oil from gas for buildings enrolled in the interruptible gas program.
Cost effective and cloud connected sensors can ensure that compliance requirements are being met, and notify operators if they are not. Just like building management, technology will not replace the human role in complying with regulations, but it can help.
Understanding the applications of artificial intelligence, the internet of things, big data and machine learning is an increasingly important task for real estate executives. When evaluating new solutions, technologies should be judged on their ability to deliver actionable insights, assist in strategic decision making, provide transparency into current processes, and ease regulatory burdens. Properly applied, emerging technologies can bring a boon in both portfolio profitability and tenant experience.
Enertiv deploys technology to provide full transparency for building operations management. Schedule a demo today to see how it works!