Blog, Facilities Management

Using Data Analytics in Facilities Management

Facilities management is all about making sure that buildings and spaces are safe, clean, and comfortable for the people who use them. But how do you make sure you're doing a good job? One way is by using data analytics!

In recent years, the use of data analytics in facilities management has become increasingly popular. It allows organizations to optimize their operations and improve efficiency.

Table of Contents

Data Analytics in FM

Data analytics is a helpful tool for facilities management. It can give us a better understanding of what is happening and what we need to do to make sure buildings and spaces are safe, clean, and comfortable for the people who use them. By using data analytics, we can make better decisions and improve the way we manage facilities.

What is Big Data Analytics and Why is it Important in Facility Management?

Data analytics is the process of collecting, analyzing, and interpreting large amounts of data to extract valuable insights. By using data analytics, facilities managers can gain a better understanding of how their buildings are being used, identify areas where improvements can be made, and make data-driven decisions.

Big data analytics is when you use computers to look at a lot of information and find patterns and trends. This is important in facility management because it helps you make decisions about things like repairs, cleaning, and energy use. By looking at the data, you can see what is working well and what needs to be improved.

5 Types of Data Analytics

  1. Descriptive Analytics: This looks at what has happened in the past, like how many people have visited a building.
  2. Diagnostic Analytics: This looks at why something happened, like why a machine broke down.
  3. Predictive Analytics: This looks at what might happen in the future, like how many people will visit a building next month.
  4. Prescriptive Analytics: This looks at what should be done to solve a problem, like how to fix a machine.
  5. Cognitive Analytics: This looks at how to make sense of unstructured data, like social media comments about a building.
City and building data

CRE Analytics

CRE stands for commercial real estate. This is when a company rents or buys a building to use for its business. CRE analytics is when you use data to make decisions about buying or renting a building. For example, you might look at how many people live near a building and how much they earn to see if it would be a good place for a store.

Benefits of FM Data Analysis

One of the key benefits of using data analytics in facilities management is the ability to identify and prioritize maintenance needs. By analyzing data on energy usage, temperature, and equipment performance, facilities managers can identify areas where maintenance is required and prioritize their efforts accordingly. This allows them to focus on the most critical issues and avoid unnecessary downtime.

Another benefit of using data analytics is the ability to optimize energy usage. By analyzing data on energy consumption, facilities managers can identify areas where energy is being wasted and implement measures to reduce consumption. This can lead to significant cost savings and help organizations meet their sustainability goals.

Data analytics can also be used to improve security. By analyzing data from security cameras and other monitoring systems, facilities managers can identify potential security risks and take action to mitigate them. This can include installing additional cameras, increasing patrols, or implementing new security protocols.

How Data Analytics Helps with Planning

Data analytics can help with planning by giving you a better idea of what will happen in the future. For example, if you know that more people will be visiting a building next month, you can make sure there are enough cleaners or security guards.

CRE vs. CP CRE

CRE stands for commercial real estate. CP CRE stands for corporate portfolio commercial real estate. CP CRE is when a company owns multiple buildings, like a shopping centre, business parks or a hotel chain.

Steps in CRE

  1. Research: Look at data to find a good location for a building.
  2. Planning: Make a plan for how the building will be used.
  3. Design: Draw up plans for how the building will look.
  4. Construction: Build the building.
  5. Management: Make sure the building is being used well and is in good condition.

5 Basic Procedures in Planning Data Analysis

The five basic procedures in planning data analysis in facilities management are:

  1. Defining the problem or research question: Clearly identifying the problem or question that needs to be addressed is the first step in planning data analysis.
  2. Reviewing the literature: Reviewing existing literature and research on the topic can provide valuable information and context for the analysis.
  3. Identifying the data sources: Identifying the data sources that will be used in the analysis, including the type and format of the data.
  4. Developing a plan for data collection and analysis: Develop a plan for how the data will be collected and analyzed, including any statistical or analytical techniques that will be used.
  5. Communicating the results: Communicating the results of the data analysis in a clear and meaningful way, including any recommendations or conclusions.

Remember Why You Are Analysing the Data

It’s also important to note that data analysis should be done with a purpose, and the results of data analysis should be used to improve the facility’s management.

Analytics in Facilities Management

How is CAFM used in Data Analysis of FM

CAFM, or Computer-Aided Facility Management, is a software system that is used to manage and organize data related to the maintenance and operation of a facility. It can be used for data analysis in several ways, such as:

  • Tracking and analyzing maintenance and repair data, such as the cost and frequency of different types of repairs and the time it takes to complete them.
  • Analyzing energy and resource usage data, such as electricity, water, and gas consumption, to identify patterns and areas for improvement.
  • Tracking and analyzing occupancy and usage data, such as room occupancy rates, to optimize space usage and make more efficient use of resources.
  • Analyzing and reporting on key performance indicators (KPIs) to measure the effectiveness of FM operations and identify areas for improvement.

Overall, CAFM is a powerful tool that allows facility managers to collect, organize, and analyze data related to the operation and maintenance of a facility, in order to make data-driven decisions that improve efficiency and reduce costs.

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Future of Data Analytics in Facilities Management

As technology continues to advance, the use of data analytics in facilities management is expected to become even more important. Here are a few ways in which data analytics might be used in the future:

  1. Smart Buildings
    In the future, buildings may be outfitted with sensors that collect data on things like temperature, humidity, and energy use. This data can be analyzed to help facilities managers make decisions about things like heating and cooling, lighting, and energy efficiency.
  2. Predictive Maintenance
    Data analytics can be used to predict when equipment and systems in a building will need maintenance, so they can be fixed before they break down. This can save time and money, and prevent disruptions to the people who use the building.
  3. Virtual Reality
    (VR) technology can be used to create virtual models of buildings. This can help facilities managers visualize how a building is being used and identify areas that need improvement.
  4. Automation
    Data analytics can be used to automate tasks like scheduling maintenance, ordering supplies, and monitoring security. This can save time and reduce errors.
  5. IoT (Internet of Things)
    The Internet of Things (IoT) is a network of devices that are connected to the internet. In the future, facilities managers may be able to use data from IoT devices to make decisions about things like energy usage and security. The use of sensors and monitors allows the FM to utilise Conditioned-based maintenance (CBM)

Conclusion

Data analytics is already playing an important role in facilities management, and it is expected to become even more important in the future. By using data to make decisions about things like repairs, cleaning, and energy use, facilities managers can make sure that buildings and spaces are safe, clean, and comfortable for the people who use them. Advances in technology, like IoT and VR, will make data analytics even more powerful, allowing facilities managers to make better decisions and improve the way they manage facilities.

Frequently Asked Questions about Data Analytics in Facilities Management

  1. What is data analytics in facilities management?

    Data analytics in facilities management is the use of data and technology to make decisions about the maintenance, operation, and management of buildings and spaces. This can include analyzing data on things like energy usage, occupancy, and maintenance needs to make decisions about how to improve building performance and create a better experience for building users.

  2. Why is data analytics important in facilities management?

    Data analytics is important in facilities management because it allows managers to make informed decisions based on data, rather than assumptions. By analyzing data, facilities managers can identify patterns, trends and inefficiencies that they might not have been aware of, and make adjustments accordingly.

  3. What kind of data can be analyzed in facilities management?

    There are many different types of data that can be analyzed in facilities management, including energy usage, occupancy, maintenance needs, and operational costs. Additionally, data from IoT devices, social media, and other sources can be analyzed to gain insights about building usage, user satisfaction, and other factors.

  4. How can data analytics be used to improve energy efficiency in a building?

    Data analytics can be used to identify patterns and trends in energy usage, such as when and where energy is being used most. This information can then be used to make adjustments, such as adjusting the thermostat or lighting, to reduce energy usage and improve energy efficiency.

  5. How can data analytics be used to improve the user experience in a building?

    Data analytics can be used to analyze data on things like occupancy and usage patterns, to identify areas of a building that are underutilized or overcrowded. This information can then be used to make adjustments, such as reconfiguring spaces or adding amenities, to create a better user experience.

  6. How can data analytics be used to improve building maintenance?

    Data analytics can be used to analyze data on things like equipment usage and maintenance needs, to identify patterns and trends. This information can then be used to schedule preventative maintenance, reduce downtime and improve overall building performance.

  7. What are the benefits of data analytics in facilities management?

    Benefits of data analytics in facilities management include: improved decision-making, increased energy efficiency, improved user experience, improved building maintenance and cost savings.

  8. How can I get started with data analytics in my facility?

    There are many ways to get started with data analytics in your facility, depending on your specific needs and resources. Some options include: working with a data analytics provider, installing IoT devices, and hiring a data analyst.

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