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How Business Intelligence Can Help Your Company Get Smart with Data

Tracking facilities data is a complicated, end-to-end process that takes time and organization to complete. Collecting information alone does not mean you will get the best results. The key is to maximize the time and effort you put into collecting data, which is why implementing Business Intelligence (BI) is so important.

BI is the process of studying data and presenting information that is useful when answering questions and making decisions.. 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. We would like to share a few BI practices that have emerged as trends among the companies who optimize their data:

1. 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, temperature, pressure, occupancy and network by placing sensors on HVAC units
  • Sustainable energy use by placing light sensors in aisles and restrooms
  • Actionable data, predictive and forward-looking capabilities from the sensors

  • Better space utilization, displays, inventory planning and promotions from monitoring foot traffic.

An interesting case from another industry is Toyota. Toyota uses IoT to eliminate issues in their manufacturing process. The car company tracks the performance of equipment with sensors to help them schedule future maintenance. Toyota also backlogs data from the sensors for future use. When a field issue occurs, they refer back to their catalog of data and try to relate the problem to a machine that was not working properly.

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.

2. Deeper Data Mining:

Companies that use BI can increase the value of their organization when they understand more than 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 retail industry, companies like Kohl’s have used data mining to predict consumer behavior. Because Kohl’s has found that customers are more likely to take advantage of offers near the time of purchase, shoppers in the retail store receive emails with personalized offers that feature products they have searched in the past.

In the facility maintenance industry, data helps companies reach goals like reducing, minimizing and optimizing an asset lifecycle at all phases. Patterns that a company could use to improve their facility maintenance might include relationships between:

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3. 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. we will replace an asset if it has a 75% chance of failing in the next 3 months)
  • Setting specific KPIs (key point indicators) to monitor assets

Companies in different industries have used predictive analytics, as well. Boston Medical Center implemented a predictive analytics solution that allows healthcare institutions to predict how many staff members and rooms they need during peak times based on demand patterns. To put the expansive capabilities of predictive analytics into perspective, this same solution can help retailers and restaurants avoid over- or under-staffing in their facilities.

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.

If you are interested in additional information about the best practices of data use, read our blog focused on the organization of facility maintenance data, here.

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