How focusing on key energy KPIs helps to reduce energy consumption

In energy management, misguided conclusions can be developed based on total energy consumed across all sectors. This “apples to oranges” approach, as in total energy in one sector against total energy in another sector, can skew your energy data and give an uneven representation of total energy usage.

For example, say you’re comparing a manufacturing plant to a distribution plant and notice how significantly less energy is consumed at the distribution center. The problem here is that even though there is less energy consumed at the distribution plant, the manufacturing plant has longer operating hours and has more machinery in use at a higher wattage. This machinery requires higher cooling loads and uses significantly more energy.

So instead of comparing the two plants based on total energy used, you should evaluate the two plants based on average energy consumption per business unit.

When developing your energy management program, a crucial step to reduce energy consumption is developing priority areas of focus. This is especially crucial if your organization has a variety of operations.

For example, an energy manager of a brewery notices that a group of packaging plants are the highest energy consumers based on their operational output. That would inform the energy manager that reducing energy consumed as a result of packaging should be a priority for the organization and doing so will help to improve energy efficiency across the board.

The manager can go a step further and compare the operational output of the packaging plants to discover why several plants are more efficient than others. The manager can then review the efficient plants to determine best practices to reduce energy consumption at the higher energy consuming plants.

In any energy management software, there is a handful of data that can be used to review performance and determine conservation measures. Understanding which data to utilize is important for analytics and key performance indicators (KPIs). Evaluating the right data leads to clearer objectives, whereas the wrong data can paint an inaccurate picture on building energy performance. Paying attention to the most pivotal factors and metrics within energy data management software will provide organizations of any type the data they need to make improvements to their operational processes and reduce energy consumption.

Polling energy analytics software for the average total energy consumption across sectors is just one “apples to oranges” approach that can drastically influence the reading of energy performance and the effectiveness of an energy management program.