AI and machine learning are often falsely portrayed in mass media as machines that take away jobs and outsmart humanity. In reality, advancements in machine learning have the potential to revolutionize business processes and decision-making, including how enterprises manage multiple locations and facilities.
For facilities management, machine learning is primarily used to get the most out of stored data. In this post, we will take a look at three of the ways facilities managers are using machine learning to improve processes and make better decisions:
What is Machine Learning?
Machine learning is a subset of artificial intelligence (AI) that programs computers to learn from their own processes, thereby automating analytical model building. Machine learning typically begins with an algorithm for generating predictive functions, and grows as the computers adapt through experience. By applying more and more data to the programmed algorithm, smart machines can provide recommendations based on what they see in the data. In short, machine learning is teaching computers to “think” on their own.
How Can Facilities Management Benefit from Machine Learning?
Facilities management software with machine learning capabilities gives the industry advantages it has never had. By combining the power of intelligent technology with vast amount of facilities management data, FMs can automate tasks and deliver greater efficiency.
1. Self-Monitoring Technology
FM technology with machine learning capabilities is able to identify when processes aren’t operating at optimal levels and predict process failures. Smart machines can then alert facilities managers to abnormalities before they affect business operations. In this way, the self-monitoring benefit of machine learning helps facilities managers be proactive, saving time and money by handling potential problems — such as ordering replacement parts, cleaning out filters, or replacing equipment — before they manifest and grow in complexity and cost.
Smart FM technology can also learn to automate processes for facilities managers; when the machine once alerted the facilities manager of an action to take, over time it learned to automatically perform the action on its own. An example could be noticing that a piece of equipment is on track to break and independently ordering a replacement part.
Smart technology powered by machine learning is also able to find data patterns it is not specifically programmed to find. This capability alerts facilities managers to FM inefficiencies, giving them the knowledge and data necessary for making changes. In one application, smart facilities management technology could crawl work order data and find there is a lag in work order resolution due to inefficient invoicing processes. The technology can then alert FMs to this inefficiency, providing the deep data insight that present an opportunity to streamline work order invoicing.
2. Data-Driven Decisions
Machine learning teaches computers to independently comb through data and pick out trends, patterns, and outliers. By combining machine learning with predictive analytics, technology can provide insights facilities managers can use to make data-driven decisions. This increases FM efficiency, since facilities managers have all the information they need to make optimal decisions at their fingertips.
Additionally, since this kind of technology expands on its knowledge as it works, the data-combing and subsequent FM recommendations will get better over time. Data-driven decisions in facilities management include whether to repair a machine or replace it for best results and cost-savings, how to allocate spend to receive the greatest ROI, and when to visit various locations based on the current status of their facilities.
3. Smart Data Storage
Machine learning transforms stored data into smart stored data. Facilities managers once faced the problem of disorganized data stores, which made finding the information you were looking for extremely time-consuming and frustrating. Now, machine learning technology can analyze and categorize data based on what kind of action it requires — data related to preparing facilities for winter is stored together, while data pertinent to a machine’s repair history is moved to live in the same space. Technology that utilizes machine learning automatically sorts data into actionable groupings, helping facilities managers figure out how to use data efficiently and effectively.
In order to take full advantage of machine learning capabilities, FMs should first ensure they have an efficient system for collecting and storing facilities management data. Many facilities management professionals are currently facing older equipment and processors that are not up to modern technology standards. Facilities managers should keep in mind that, when changing over legacy equipment, it is most beneficial to ensure their new technology has machine learning capabilities. Not only will this bring technology up-to-date, but it will also act as an investment in facilities’ futures, since machine learning capabilities expand as it accumulates experience.
By teaching technology to operate independently, machine learning helps facilities managers improve decision speed, quality, and consistently. Smart technology also reduces costs in the immediate, while also setting facilities up for success in the future.
Machine learning is transforming the facilities management industry. Learn more about how from ServiceChannel’s VP of Marketplace Strategy & Experience, Siddarth Shetty at his presentation at NFMT Orlando 2017. He will be presenting on November 14th at 10 am. We hope to see you there!