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BENCHMARKING
Benchmarking—Benchmarking – Using filters to compare your building to just the right comparables Benchmarking – Using filters to compare your building to just the right comparables
Many FMs participate in benchmarking programs only to find that they have difficulty developing good comparisons for their facility type. Having access to ample data with good filter sets is key to making the right comparisons. Let’s look at a few examples from FM BENCHMARKING to see the value that filters can bring to the analysis of your benchmarking data.
For example, if you are comparing your facility’s utility costs you might want to compare it with others of a similar climate and age. Facilities built during different time periods are likely to have different types of glazing, insulation, mechanical systems, etc.
In the following example, a manufacturing facility is shown without applying a filter for the age of the facility (we’ll get to the impact of climate next). This results in a median utility cost for the group of $2.27 per gross square foot (see Figure 1).
Figure 1. Total Utility Cost Per Unit Area without applying a filter for Building Age.
In the next example (see Figure 2), we take the same facility but filter for those in a similar age category: 21-50 years. So instead of a sample size of 202 facilities without the age filter, we now have a sample size of 62 with the age filter. This is still an adequate sample size for good comparisons.
Note that the median cost with the age filtered sample is $2.47 per gross square foot which is about 9 percent higher than the non-age filtered sample.
Figure 2. Total Utility Cost Per Unit Area, applying a filter for Building Age. Note that the median utility cost per unit area is about 9% higher than without the filter.
Climate zone might be another important factor on total utilities costs. In this next example we have filtered the data set only for the size of the facility: 125,000 to 250,000 gross square feet. This produces a sample size of 63 facilities with a median cost for utilities of $3.70 per square foot (see Figure 3).
Figure 3. Total Utility Cost Per Unit Area without applying a filter for Climate.
Next we will filter just for the climate zone where the facility is located. This produces a sample size of 85 facilities and a median utility cost of $2.67 per gross square foot (see Figure 4).
Figure 4. Total Utility Cost Per Unit Area, applying a filter for Climate. Note that the median utility cost per unit area is much lower than without the filter.
In this example it is clear that a "Mixed Humid" climate type has about a 39 percent reduction in energy costs compared with the non-filtered group.
There are many other examples. For example, when looking at maintenance costs performed by outside contractors, if one applies a filter to factor out facilities that require security clearance of all workers, one will see a lower median cost.
Turning benchmarking data into information is an iterative process. It is not as simple as applying a group of filters, and then drawing a conclusion. Rather, the key is to identify the filters that have the most impact for your type of facility and situation. It usually is not recommended to apply every possible filter, as you will eliminate a lot of buildings that may provide valuable information to you. So one should start with very few filters, and then gradually apply more, to see where the differences will be greatest.
By applying filters that are appropriate to the benchmarking metrics under consideration you can enhance the value of the process and be sure you are making valid comparisons.
More information about FM BENCHMARKING may be found at www.FMBENCHMARKING.com, including a free demonstration tool where you can input your facility data and see some benchmarking results.
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