Analyzing the 4 Types of FM Analytics Correctly

Analyzing the 4 Types of FM Analytics Correctly

In the digital age, the ability to capture, process, and refine data into actionable insights is fast becoming the key differentiator between successful organizations and the ones doomed to fail. The facilities management function is no exception. Facility managers who experience disconnect between their ability to capture data and their ability to analyze it are bound to lag behind their peers in terms of operational excellence and cost containment. For an industry that is so critical in creating a positive and safe customer experience, facility management has struggled to position itself as strategic to the business. Analytics can help change that.

What facility managers who do this well have come to understand is that collecting the data is merely the first step; taking advantage of all that it has to offer and examining it on a deeper level is a much more significant hurdle to overcome.

According to a paper published by Emerald Insight in August 2017 focusing on big data in facilities management, 67% of participants found making use of structured and unstructured data to be especially challenging.

One of the main takeaways from this research is the participant’s acknowledgment of an existing imbalance between data collection and data analysis capabilities. These two ingredients work best as a pair—you can’t develop an analytical approach for maintaining your facility if data collection is lacking. Without a commitment to analyzing that data, your data sets will remain idle, collecting dust and providing no added value for you or your organization.

Below, we outline the four types of analytics that are relevant in facilities management, and we explain how you can leverage each to improve operational efficiency.

Descriptive Analytics

Descriptive analytics give you the ability to look back and understand what happened in the past. They are the first step to making data understandable, and can help provide you with a baseline for understanding your facility and the work it has required in the past.

Descriptive analytics give you with a holistic view of your historical data. They can provide details on the current state of your assets, resources, and repair and maintenance volumes. These dashboards and reports could plainly outline hours worked, where those hours were spent, and your product inventory, just to name a few. Descriptive analytics give you insight into what happened in the past and are a necessary first step to get you asking deeper questions: Why did it happen? What could happen? How can I influence a better outcome?

Simply put, analyzing the work you’ve done in the past will help you better anticipate what work will need to be done in the future. These basic data points are the start of your deeper dive into FM analytics.

Diagnostic Analytics

Data collection and descriptive analytics may lead to more questions. Descriptive analytics provide you with a base for your dive into data science, while diagnostic analytics take that one step further to help you understand why it happened.

When you are reviewing your facility data, something might seem off. Identifying exactly what’s wrong without the proper context can be challenging.

Leveraging all of the available data and utilizing sophisticated data discovery tools can help you identify important trends and patterns. Whether it’s cleaning areas that don’t get enough attention, maintaining full efficiency with your HVAC system, or prioritizing pressing tasks, diagnostic analytics will help develop actionable insights and recommendations. From there, you will be able to identify anomalies, optimize spending, and maximize your time. 

Predictive Analytics

Collecting data and pulling insights from machine learning and other advanced techniques will limit surprises and forecast what comes next for your facility. That’s the crux of predictive analytics and the potential it has. By looking to the past, you will have a better understanding of what was successful, what wasn’t, and how you can improve moving forward.

Predictive analytics will enable your facility and your staff to function more efficiently. They move beyond descriptive and diagnostic analytics, which are both more focused on understanding the past. Making analytical, driven predictions for the future leads to data-backed decisions, and those decisions lead to a more efficient facility.

Anticipating significant repairs or replacements is one of the major advantages of predictive analytics. Whether it’s something as crucial as an HVAC unit that could be reaching the end of its life, or light

bulbs that are due to be replaced, predictive analytics allow you to leverage your vast collection of data to calculate key metrics like mean time to failure and create a predictive-based schedule that reflects the recurring maintenance needs of your equipment.

With the right amount of attention and data input, your facility will grow to become a connected entity and your predictive schedule can continuously optimize itself to quell any new issues as they arise. By having the foresight to predict these costly repairs, you can avoid emergency work orders and save money, helping you remain within your budget

Prescriptive Analytics

Unlike the other types of analytics mentioned, prescriptive analytics is a theoretical approach. A prescriptive approach to analyzing your data empowers your decision-making ability through data collection. Your data will provide insights into how you can improve your decision-making ability, but ultimately, it’s up to you to create a plan of attack.

Leveraging prescriptive analytics is all about making complex decisions easier and more streamlined, improving your efficiency. Using data to point you in the right direction, each decision you make will fulfill the goal of making business operations more manageable. Whether you are managing personnel and creating work schedules, or striving to eliminate wasteful spending and repetitive tasks, prescriptive analytics will empower your decision-making strategy.

For example, consider an HVAC or refrigerated asset that keeps failing. This failure could have a direct impact on your customer experience. Do you keep repairing the asset over and over or should you replace it? These are the decisions that prescriptive analytics will make easier. Prescriptive analytics provide you with the necessary insights to improve your operational efficiency.

Final Considerations

There are several benefits of taking an analytical approach to managing your facility. These four types of FM analytics present you with an opportunity to cut costs, improve efficiency, and make better use of your staff’s time.

Data isn’t tough to come by in this industry, but there often is a disconnect between collecting data and leveraging it to make data-driven decisions. Analytics will be instrumental in closing that gap.



Posted On June 4, 2019

Siddarth Shetty

Vice President of Major Accounts at ServiceChannel

Sid Shetty is the vice president of major accounts at ServiceChannel and has held various leadership roles in operations, global services and product strategy during his more than 10 years at the company. He holds a master’s degree in engineering management from Duke University and a bachelor’s degree in electronics engineering from VESIT-Mumbai University and is a Certified Six Sigma Green Belt. 

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Analyzing the 4 Types of FM Analytics Correctly
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