Why Machine Learning and Predictive Analytics Are Crucial for Sustainable School Building Operations
Machine learning and predictive analytics are two iconic advances in technology that when used in K-12 school buildings district-wide propel sustainable operations forward. School officials must understand the role of machine learning and predictive analytics play in making this possible.
Lost Time Equates to Lost Savings
One of the most common problems with deciding on what assets to update in a school building as a way to gain energy efficiency tends to remind one of an adage that applies to any operation: Lost time is lost money. In schools, lost time means lost opportunity to recoup savings. Unfortunately, sudden investment in sustainable school building operations can have a disastrous impact on finances. The wrong investments can take years, if not decades, to recoup. Meanwhile, the school board will expect results sooner rather than later. Thus, the decision to implement sustainable operations is left on the back burner in favor of what has worked for now.
Machine Learning and Predictive Analytics Eliminate the Data-Legwork
Instead of trying to invest in sustainable school building operations through an all-or-nothing approach, school Facilities Managers can tap into the value of machine learning and predictive analytics to ensure all decisions are based on data, not an assumption. Data-based results eliminate the guesswork and offer a proven way to improve efficiency without sacrificing other needs within the budget.
For example, a recent study, asserts Fiona Burlig of the Energy Policy Institute at the University of Chicago, published by Forbes, found the application of machine learning in making investment decisions for energy efficiency upgrades in K-12 schools could bring harmony to the projected-versus-realized cost savings' potential of assets. In other words, machine learning could leverage historical and real-time data to determine which upgrades could provide the greatest, faster returns. Without the use of machine learning, actual savings from improvements only rose to 25 percent of their expected value.
After the initial decision, the combined power of machine learning and predictive analytics ensure upgrades continue to provide stable returns, as well as identify when other areas need attention. Virtually, the combination guarantees lasting success.
Best Practices in Leveraging Data-Based Sustainable School Building Operations
School Facilities Managers can influence superior outcomes for students, asset longevity, faculty performance, recognition for commitment to green practices and much more through sustainable school building operations. It is a monumental task, so Facility Managers should follow these steps to break free from their limitations and embrace sustainability for all time.
Recognize the visible problems in your school.
Consider applying to applicable local, state and federal programs for funding of sustainable school building operations’ improvements.
Decide which assets, if any, provide the best benefits through upgrades.
Use machine learning to ensure actual savings align with projected savings.
Prioritize upgrades based on steps two and three.
Leverage descriptive analytics to understand your assets.
Use predictive analytics to identify the problems likely to occur in the near-future.
Follow the recommendation of prescriptive analytics to achieve the best result.
Validate savings and performance after deployment.
Report savings to the school board, faculty, and community.
Simplify Your School's Energy Management
First appearances in sustainable school building operations can be deceiving. School Facility Managers must not let the complex nature of advanced energy management analytics be a deterrent to their use. The power of advanced analytics is easier to access than ever before thanks to energy management platforms that contain machine learning, and schools that leverage advanced analytics can achieve remarkable success. Kickstart your school's journey by contacting Cenergistic at 1-855-798-7779 or submitting your query online today.