ENTOUCH Smart Building Solutions

How to Implement Smart Energy Management With Predictive Analytics

Smart energy management with predictive analytics can lead to big improvements in your facility ecosystem – if used properly.

The Internet of Things (IoT) and smart energy management with predictive analytics are on track to bring energy efficiency to businesses of any scale. However, IOT-enabled devices come with challenges, including problems analyzing data and ensuring proper integration. However, your organization can leverage the IoT to create and supercharge smart energy management with predictive analytics in several ways.

Smart Energy Management With Predictive Analytics Is Scalable

A simple and scalable solution is a precursor to empowering smart energy management. Your organization needs to retrofit existing buildings, as well as design and construct new facilities with IOT-enabled sensors in mind. Fortunately, today’s IoT-enabled devices contain the processing power necessary to provide actionable insights into your facility’s activities.

They Integrate With Legacy EMS and ERP Systems

Smart energy management with predictive analytics can also be empowered through integration with your existing enterprise resource planning (ERP) and legacy energy management systems (EMS). Although the systems may have limited data capture and analysis capability, they do represent an investment and opportunity for gathering critical information about your facility’s assets.


Leverage Organic Growth of the IOT

The IOT is also growing at a phenomenal rate, and more IoT-enabled devices come online daily as consumers and businesses alike look to new technology as a way of improving efficiency. Organic growth of IoT-enabled devices means prices of sensors and such technology will steadily decline, and your organization can leverage organic growth to provide more opportunities to capture critical data regarding the overall health of your capital assets and facilties.

Use Predictive Analytics to Drive Actionable Outcomes

After collecting data, predictive analytics review the information and determine what might happen if your facility continues operating at its current state. This includes expected results and analytics-driven outcomes for your assets, like reducing HVAC total cost ownership or increased productivity of personnel. By knowing what might happen, your organization can take proactive steps to midigate risk while boosting your bottomline.

Leverage Automated Analytics

Having predictive analytics is great, but you need to take advantage of automation too. Automation provides a seamless, easy-to-use way of tapping into predictive analytics’ potential. Automation can be leveraged and data capture, analytics processes, including algorithms, and self-optimizing systems.


Plan Activities, Like Maintenance, Around Analytics-Based Models

Your organization can also plan certain activities, like maintenance or upgrading of systems, around Analytics-based Models. By understanding what may happen, maintenance schedules can be refined, and analytics can determine the best time and way to accomplish such activities.

Embrace Energy Providers to Drive Growth and Sustainability for Just-In-Time Power

Energy providers have a vested interest in reducing the amount of power consumed. Less power demand results in greater opportunities for savings among service providers, so overall energy rates decrease. Also, more service providers are looking for ways to provide just-in-time power, driving down energy production costs. By implementing smart energy management with predictive analytics systems, you can become a partner in achieving energy companies’ goals of reducing overall demand. This may also open the door to discount programs and unique partnership-exclusive benefits.

Implement These Steps to Empower Your Energy Management Strategy Now

Your organization needs to develop the smart energy management strategy, but your strategy is only as strong as its weakest link. Understand the top concepts in creating and effectively maintain a smart energy management strategy through the power of predictive analytics.