Tracking facilities data is a complicated, end-to-end process that takes time and organization to complete. However, collecting information alone doesn't always provide the best results. The key is to maximize the time and effort put into collecting the data. Implementing a business intelligence (BI) strategy can help businesses making more strategic, data-driven decisions to improve operational efficiency, identify opportunities, and gain a competitive edge.

Business intelligence (BI) refers to a set of technologies, processes, tools, and strategies that enable organizations to collect, analyze, and transform data into valuable insights for informed decision-making. Executives and facility maintenance teams can benefit from BI because reliable data leads to decisions that result in measurable ROI and continual savings on capital investments.

When it comes to making data-driven decisions in facilities maintenance, these are the foundational components:

  1. Data collection: BI begins with the collection of data from various sources, such as databases, spreadsheets, web services, and external data providers. This data can be structured or unstructured.
  2. Data integration: Data from diverse sources often needs to be integrated and transformed into a consistent format to ensure accurate analysis. Data integration is a critical step in the BI process.
  3. Data warehousing: In many cases, organizations use data warehouses to store and manage large volumes of structured data. Data warehouses are designed for efficient querying and reporting.
  4. Data analysis: BI tools and platforms provide capabilities for data analysis, including querying, reporting, data visualization, and data mining. These tools allow users to explore data and discover patterns, trends, and insights.
  5. Reporting and dashboards: BI solutions often include reporting tools to create static or interactive reports and dashboards. These visualizations help users understand data at a glance and track key performance indicators (KPIs).

Using business intelligence in facilities maintenance leads to better long-term planning for cost transparency and spend optimization, which allows for stronger budgets and better capital planning. Below are just a few of the trends that are fueling business intelligence in the facilities maintenance industry.

Incorporating IoT

Internet of Things (IoT) is a common example of emerging technology that enhances BI capabilities. By using sensors that communicate, analyze and share data, companies can collect real-time and detailed information about their products, assets and locations. The information IoT devices provide can lead to:

  • Observation and control of carbon dioxide, humidity, temperatures, pressure, occupancy, and network through sensors placed on HVAC units
  • Sustainable energy use through the placement of light sensors in aisles and restrooms
  • Actionable data that is predictive and forward-looking
  • Better space utilization, displays, inventory planning and promotions from monitoring foot traffic.

Facility maintenance companies can use the same framework of using sensors to create a log of their own data. However, understanding what data is the most important to track for a backlog can be difficult, which is why data mining is important.

Deeper Data Mining

Companies that use BI can increase the value of their organization when they understand more about what is occurring in their facilities. Data mining is the process of analyzing big data and finding new trends within the data. Finding these trends can help BI users understand why certain happenings occur and predict what will happen in the future. In the facility maintenance industry, data helps companies reach goals like reducing, minimizing, and optimizing an asset lifecycle at all phases.

Predictive Analytics

After collecting data with IoT and finding actionable trends to make the best decisions in asset investment planning, network design, procurement, installation and disposal/replacement, facilities can use data to foresee future outcomes. Predictive analytics is the process of comparing historical data to current data for future planning. This process helps implement techniques like:

  • Using past equipment failures to predict future equipment failures
  • Creating maintenance rules based on forecasted failure (e.g., replacing an asset if it has a 75% chance of failing in the next three months)
  • Setting specific KPIs (key point indicators) to monitor assets

How can these BI strategies benefit your company?

While documented impacts of BI adoption in the facility maintenance industry are minimal, there is a lot of potential. By implementing BI initiatives in FM programs, companies like yours can experience improved asset utilization, lifecycle management and cost savings. Read more about the best practices of data use and the organization of facilities maintenance data.

A well-functioning maintenance strategy is essential to the success of any modern-day facilities portfolio. To make sure your facilities maintenance strategy is meeting your needs, request a demo to learn more about how our programs can help you.

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