How AI Can Help You Do More with Your Facilities Data
Though the concept itself was born out of a Dartmouth University lab in 1956, Artificial Intelligence (AI) is finally making its mark today as a mainstream technology – one that businesses are adopting seriously and at scale. Right now, almost half of the corporate world has embedded AI into at least one business process. This is up from 20 percent just two years ago, according to the Wall Street Journal.
As AI adoption accelerates, it has even prompted the so-called “fourth industrial revolution” a.k.a. “Industry 4.0.” The term represents the era of digitization marked by the shift from simple automation toward networked “cyber-physical systems.” AI is a hallmark of these connected systems, serving as the intelligent, algorithm-driven foundation through which immense quantities of data are automatically sorted, interpreted, and derived into actionable insights. These capabilities are transforming business functions and operations across industries – and this includes facilities management.
Some FM professionals fear such advancements could eventually reduce the number of FM and maintenance jobs on the market. This fear is understandable, but short-sighted. Every major technological shift throughout history has created far more and better jobs than it has eliminated; for every manual gas lamp lighter, how many workers are now employed to produce and distribute electricity to the billions of street lamps around the world today?
At ServiceChannel, this is exactly how we think about AI. It’s not about replicating human behaviors; it’s about harnessing a new mode of data analytics that makes our jobs easier and more proactive, decreasing the amount of time spent on tedious, repetitive tasks and improving decision-making processes. Analytical AI, in other words, helps businesses make immense quantities of data more actionable – and it happens with minimal human interference.
Looking for ways to integrate AI technology into your facilities program? Here are a few important steps to help you get there.
First Steps to Introducing AI to Your FM Program
There are multiple potential applications of artificial intelligence already available to facilities professionals. These range from advanced work order management software to smart energy consumption and space utilization technology. And where AI-enabled technology was once only available to organizations with exorbitant budgets, it’s now being packaged in more widely accessible and consumable formats – whether a component of vertical software or in point implementations from cloud providers.
To provide legitimate value to a business, AI must be integrated only once the FM program has undergone a sufficient digital transformation. Obviously, you can’t program sophisticated predictive and prescriptive algorithms into a paper ledger. To find out what gaps need to be filled in, start by conducting a thorough assessment of your organization’s digital capabilities, including the people, processes, and tools you rely on within the FM domain. Know which data, assets, and paper-based files can be digitized and adopt a lifecycle approach to your data infrastructure.
If you haven’t already, consider investing in a comprehensive digital facilities management platform to serve as the foundation for ongoing digital transformation. Service Automation software, for example, provides a centralized hub through which all forms of FM data can be collected and analyzed – from work order and invoicing data to historical asset maintenance records, preventive maintenance schedules, and contractor performance. This means your organization can break down data silos and obtain a holistic picture of overall FM program status.
Put Your Data to Work for You
The most powerful application of AI is its ability to mine raw data, making sense of massive (yet valuable) ‘data lakes’ that would otherwise be left untouched. And, as we’ve mentioned, data is not something that most facilities programs lack. AI can put years upon years of historical numbers to work for your team in ways that you might never have imagined, recommending best next steps, predicting equipment failures, and improving spend management. Here are a few ways AI can help you get the most out of your FM data:
Smarter Preventive Maintenance
Industry leaders estimate that some 80 percent of the time spent on industrial maintenance is purely reactive – and almost 50 percent of unscheduled downtime is the result of equipment failures, usually with equipment late in its lifecycle. What this means is that most facilities managers are using their valuable time addressing assets that have already broken down, as opposed to planning and executing preventive maintenance for assets that they know are soon to malfunction.
Unplanned downtime is costly to any business: Consider the number of lost customers if, for instance, your fast-casual restaurant has an important piece of kitchen equipment malfunction during the lunchtime rush. When AI is integrated into asset maintenance and performance data, however, it can identify patterns and trends too complex for the human eye. Using advanced algorithms, AI solutions predict when an asset is likely to fail based on data around typical operating time, energy intake and output, and overall performance. Then, FMs can respond by taking action to schedule a repair ahead of time or preemptively replace the asset before it breaks down.
With a sophisticated, AI-powered preventive maintenance program in place, businesses will reduce unexpected equipment outages, maximize brand uptime, and make annual budgeting far more predictable.
Improved Energy Demand Management
Energy demand management is becoming increasingly important for organizations looking to cut costs and minimize environmental damage. Compounding this desire are Demand Response programs, which incentivize businesses to scale back energy consumption during peak usage periods with the goal of controlling electricity grid constraints. Therefore, predicting trends in energy demand over time is immensely valuable: Fluctuations impact the cost of electricity, creating opportunities for businesses to save millions of dollars.
Several startups have recently begun to apply AI to predict these energy markets, using analysis of historical data to provide explicit forecasts. How? Actual energy consumption data is compared to factors such as weather, building occupancy, sunlight, and consumer behavior during different times of day. AI can pinpoint discrepancies between these factors and energy use, and a model is built to represent these discrepancies. This model is used to create predictions for future usage – and the more data is accumulated, the more accurate the predictions.
Ontario-based technology company EnPowered is one of the first organizations to successfully launch AI-powered energy demand response technology, reducing electricity costs with minimal operational impact. Some customers have seen as much as a 40 to 50 percent reduction in energy costs: No small number, especially with the ever-increasing pressure on facilities teams to cut down energy consumption and minimize spend. These technologies are sure to become more sophisticated over the next several years; businesses of all sizes should take note and begin to collect and store detailed energy use data with Service Automation technology in preparation for imminent change.
Prescriptive Vendor Proposal Review
One of the most immediate ways to leverage the brainpower of AI in your facilities’ data is by adopting sophisticated FM technology that utilizes prescriptive analytics. Prescriptive analytics are often considered the “final frontier” of data analytics, using a combination of algorithms, business rules, historical figures, and machine learning to answer the question, “What should we do next?” While descriptive analytics explain what’s already happened and predictive analytics show what might happen in the future, prescriptive analytics revolve around decision-making.
Since so many critical FM decisions are made based on “gut instinct” and require an extensive, time-consuming process of gathering feedback and manually sifting through data, AI and prescriptive analytics can be incredibly beneficial. It can not only reduce time-to-completion, but also increase consistency across FM operations and ensure repair and maintenance spending is kept to a minimum. In addition, AI-enabled FM software learns from your decisions over time, meaning core business priorities (which, of course, will differ from company to company or even from one facility to another) are taken into consideration when a recommendation is made.
ServiceChannel’s Decision Engine, for example, leverages 15 years of data to recommend the most appropriate next steps when evaluating key decisions around work orders and maintenance. One valuable use case for Decision Engine is the proposal review process: When looking at a contractor proposal, the technology evaluates historical actions (such as percentage of rejections for similar proposals above a certain price point) and considers factors such as contractor scorecards, asset repair history, and previous work orders of similar scope in order to make recommendations about whether to accept or reject.
While a high-end brand like Louis Vuitton might prioritize time-to-resolution over repair cost, another brand might have a higher rate of rejection based on cost and prefer to spend time finding a provider who can meet strict budgetary requirements. AI-enabled technology ‘understands’ these preferences and can make recommendations accordingly. This takes the qualitative aspect out of the FM decision-making process and helps facilities professionals focus on the numbers, driving marked improvements in efficiency for the entire organization.
AI has shown incredible potential for modernizing many industries and business functions – including facilities management. The majority of its power lies in data analytics, where prescriptive models can be leveraged across large datasets to assist FM professionals with core decision-making processes and reveal opportunities for significant savings. Perhaps the most valuable function of AI, however, is its ability to improve over time, “trained” by the users who interact with it to prioritize specific goals or outcomes. This means users can trust that the recommendations or results they’re seeing are consistent with high level business priorities, whether it’s reducing spend, decreasing carbon footprint, or minimizing downtime.
AI isn’t a futuristic concept. It’s widely available, ready to transform your business into a data-driven powerhouse. If you want to stay ahead of the competition, cut costs, and optimize your FM workflows, consider adopting AI-enabled technology – or risk being left behind in the wake of Industry 4.0.
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