Energy Data Analytics Turn Energy Managers Into Superheroes
Energy data analytics include the use of reactive, predictive and prescriptive analytics, powered by machine learning, to maximize savings' potential of energy-efficiency improvements. Such improvements range from upgraded facility assets to change the way building occupants use energy. The application of energy data analytics, through intelligent building software, is one-way education Facility Managers can leverage information to save money.
School Facility Management Is Riddled With Poor Visibility and Significant Costs
A common problem with school facility management is poor visibility. Poor visibility is the result of aging buildings, limited budgets, and resources. Schools may not have the financial resources to inspect assets every day, and with the average age of schools in the U.S. sitting at 40 years, it may not be physically possible to inspect the internal workings of assets with the naked eye. As a result, energy costs for districts continue to climb, and these costs will only grow as average energy rates charged by utility companies increase. The only solution lies in making changes necessary to save energy.
Energy Data Analytics Provide a Path to Understand Energy Use
Energy data analytics effectively match energy supply against demand in schools, explains Damon Lapping via Disruptor Daily. When the district understands the top users of energy, including people and assets, they can work to reduce energy demand. As a result, the supplier, which is the utility company, may charge lower rates or offer additional incentives. Government-sponsored incentives may also be available, provided a school can demonstrate the value of energy improvements and effect on student progress.
For example, reactive analytics can help Facility Managers recognize the factors that contributed to the past malfunction of an asset or what behaviors contributed to higher energy costs. Predictive analytics can then be used to determine the outcome for assets and energy costs if current conditions continue. Meanwhile, prescriptive energy data analytics provide a sense of direction for Facility Managers to drive future savings and prevent unnecessary expenses.
Ways Energy Data Analytics Empower School Facility Managers
Energy data analytics transform the typical school manager into an informed Energy Manager, bordering on becoming a super-hero, in the following ways:
Reactive energy data analytics allow you to see how energy has been used historically in your buildings allowing you the opportunity to make changes and see reduction in consumption.
Predictive analytics help school districts determine what today’s actions will mean for tomorrow’s energy costs. It allows you to be prepared for possible equipment failure or to plan equipment/facility maintenance allowing you to spend budget dollars more wisely. As a result, schools can plan for changes that are defined in prescriptive analytics.
Prescriptive analytics take things further by determining which improvements in energy use will have the best result. It allows for close to real-time analysis of energy use so changes can be made quickly, reducing energy spend before your monthly bill is prepared. Therefore, prioritization of upgrades is streamlined, and Facilities Managers can use this form of analytics in gamification, encouraging students to make decisions that conserve energy, such as using natural light or not leaving chargers plugged in unnecessarily.
Improved conditions in the school translate into better student experiences, improving learning and helping students succeed in the classroom and life.
Utility companies may make errors in billing, and energy management analytics can assist with auditing of such bills. This provides the ability to push back against unreasonable or unexpected energy bills.
Lower operating costs, through improved use of labor and material resources, lead to opportunities for reinvestment into supplies for the classroom or even financial benefits for teachers.