Benchmarking: Collect Data


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Collecting energy consumption data from your utility is the first step in benchmarking. However, you will need additional information to complete the benchmarking process.

Conditioned Building Floor Area

You will need to determine the conditioned floor area of your building so that you can compare buildings that have different floor areas but are used for similar purposes. The conditioned area is the area of the building that is heated or cooled. It does not include garages or other unconditioned spaces. A common error is to use rentable area (which is often readily available). Rentable area does not include building common areas (which are usually conditioned) so it is usually smaller than conditioned area. Using rentable area to compute energy use per square foot will exaggerate energy use.

Operating Schedule

Most benchmarking tools will need the number of hours per week your building operates. This should exclude those hours when only maintenance, security, or other support staff occupy the building. For many facilities, the operating schedule varies throughout the year so when a benchmarking tool asks for "operating hours/week," use the total weekly hours for the most common operating schedule.

Operating hours also vary between buildings with different uses. For example, a 24-hour computer center operates 168 hours per week, while an office space operates about 65 hours per week.


Weather information for benchmarking comes in a variety of forms:

  • Cooling and heating degree days (CDD and HDD)
  • Actual daily average temperatures from a nearby weather station
  • Historical temperature and humidity - typically 20-year averages

Some tools that help you track your utility bills also support benchmarking and may provide the necessary weather data.

Weather data is also available through several other sources. The National Climatic Data Center is a prominent source of nationwide weather data. In addition, the University of Washington and Oregon State University offer regional weather data through their web sites.

Normalizing for Differences Between Buildings

Adjusting consumption data for differences in hours of operation, floor area, weather, or other factors, is called normalization. Such adjustments are needed to fairly compare energy use between buildings. Some benchmarking tools, such as Energy Star's Portfolio Manager, normalize consumption and may request one or more of the following types of data:

  • Building operating schedule
  • Building area by type of use
  • Regional and yearly weather data
  • Building occupancy - this may be in the units of building occupants (commercial) or beds (healthcare).
  • Process loads - Some buildings have energy-intensive equipment such as file servers in large commercial buildings or medical diagnostic or treatment equipment in healthcare buildings. Benchmarking tools may account for this high-use equipment by asking you to define the category in which your building falls. Common categories include office, K-12 schools, hospitals, motels and hotels, medical offices, supermarkets, residential halls/dormitories, and warehouses.
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