4 Objectives of Effective Energy Data Analysis

While having access to utility data provides energy managers with an opportunity to improve their energy management program, the accurate analysis of that data is the actual tool that helps them effectively understand and modify their energy behavior to reduce costs. Acquiring energy data is the first step to effective energy management programs but the accurate analysis of this data is what drives necessary changes forward to reduce energy consumption. Often times poor energy analysis can lead to counterproductive impacts on operations and lead to improper conclusions for energy management. According to Natural Resources Canada, the objectives of energy data analysis are focused on obtaining the key influencing factors surrounding management decisions at facilities. Here, we go into the main objectives of energy data analysis and how a strong analysis can help you understand the story behind your building operations to reduce energy consumption. More importantly, with accurate analytics, energy managers can truthfully understand how individual assets fit into the bigger picture.

Understand Energy Use and Costs

An analysis of your energy data allows you to breakdown energy consumption and costs based on department segments and asset silos within a business or organization. It allows you to view specific energy use by utility, whether it’s oil, electricity or gas, to strategize how to manage usage moving forward. This kind of technical analysis allows energy managers to breakdown the areas in which they should focus their attention and dive deeper into understanding why there is such a high energy consumption. These analyses are important for generation discussion on how to incorporate changes to your business for reducing costs and managing energy consumption levels.  

Understand Variability

By generating a high level analysis of the energy data compiled for them by a utility aggregation company like Urjanet, energy managers are able to see the variability of energy usage throughout the week, day, hour, or 15 minute intervals, and understand how trends shift from one time frame to another. Generating charts allows them to see the peaks and valleys of energy usage and identify trends across larger periods of time. Additionally, plotting the data allows energy analysts to establish relationships between variables such as viewing the correlation between energy use and production. This information allows them to determine the best operating modes for their machinery as well as identify opportunities to increase efficiency.

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Calculate Targets and Track Progress

Data analysis allows energy analysts to calculate targets and set benchmark targets for consumption levels. Using historical data, an ideal threshold is set to allow energy managers to monitor activity and track the performance of new strategies that they have implemented to reduce energy consumption. If targets are incorrectly calculated, then poor performance will not be recognized, monitoring would be ineffective, and potential energy costs and consumption savings will not be reached.

Model Energy Demands

Energy data can also be used to model potential energy demands and conduct various “what if” analyses. Data can be extrapolated to foreshadow different outcomes depending on the factors that are being manipulated. For example, running simulations of strategies like powering down selected machinery during certain hours can help energy analysts forecast the potential energy consumption and cost savings for their business. This “what if” analysis of testing solutions before implementation can help them optimize their solutions to increase operational efficiency while cutting down on strategies that fail to deliver ROI.

With a proper and in depth energy data analysis, energy managers have the potential to deliver a significant impact to their energy programs in terms of reducing energy consumption and increasing profitability. By examining variability and using extrapolation models in their analysis methods, energy analysts can identify areas of high energy consumption within an organization and across departments in various facilities and data-test solutions to those problems. This allows them to set targets for measuring utility performance and making adjustments accordingly, and to commit to programs that are data driven from a bottom-line perspective.

To learn more about how Urjanet’s Utility Data Platform empowers energy managers, check out our Solutions Sheet: Utility Data for Energy Management & Procurement.

Related Resources:

• Successful Energy Data Management: Utility Data Is Key
• Solutions Sheet: Utility Data for Energy Management & Procurement
• Webinar: What Happens When Good Energy Data Goes Bad?

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