Many FMs participate in benchmarking programs only to find that they have difficulty developing good comparisons for their facility type. This is especially true with sustainability decisions as the technologies for achieving energy savings are relatively new. 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 sustainability benchmarking data.
In this example, our facility is a 795,000 gross square foot facility, 35 years old, with 1963 FTEs (full time equivalent workers) with a primary business function of aerospace manufacturing.
One of the Sustainability Summary output tables (see Figure 1) shows the energy savings performance target for the next year as a percentage. In the table below you can see that our sample site indicated a 4 percent savings target (this means that the subject facility intends to reduce its energy consumption by 4 percent over the next year). The median for all others in the comparison group was 5.2 percent.
Without our studying the bottom part of the table, we notice that the subject building target is less than most others in the comparison group. This suggests that we should at least consider increasing our energy savings target to be at the median or higher.
Figure 1. The first part of this table shows the energy savings performance target for our subject building and for others in our comparison group. The second part of the table shows how the subject plans to achieve those savings versus the plans for others in the comparison group.
Note also that a 38 percent of our savings is expected to occur from operational changes thru users and that our peer group median is only 28 percent savings from operational changes thru users. When we look at savings from operational changes due to new devices we expect to achieve only 22 percent where our peer group expects to achieve more savings than we do at 30 percent. Perhaps we need to consider adding more technology to our energy savings program and rely a little less on the users to achieve our reduction targets.
In our next example (see Figure 2), we are evaluating the same facility for possible LEED certification. Our analysis indicates that we have a preliminary score of 33 points and that if we implemented all of the items under consideration we would achieve 48 points, well over the minimum points required to get a basic LEED certification (40 points).
Figure 2. This chart summarizes the scores earned by the subject building for the 7 key LEED-EB credit areas. It also shows that the subject building has 33 of the 40 points needed for LEED certification, but if it were to implement all the credits “under consideration”, the building would be at 48 points, well over the 40-point minimum. However, they still would need to implement the two unsatisfied required credits.
The next step is to determine which of those credits under consideration make the most sense to implement. Figure 3 shows how benchmarking can help make this assessment.
Figure 3 expands the Indoor Environmental Quality section, providing detailed information about all eleven credits within this section. By studying which credits the subject building is considering implementing, and then seeing which of those credits have been implemented by most others, we will obtain clues to help us draw our conclusions.
From the table above, by looking at the right-hand column, we see that there are two items under consideration in the Sustainable Sites section: Credit 3 (Integrated Pest Management, Erosion Control and Landscape Management) and Credit 4 (Alternative Commuting Transportation). Only 42.1% of all LEED-certified buildings have satisfied Credit 3, and only 25.4% of the general population. This certainly does not sound like one of the low-hanging fruit.
On the other hand, nearly everyone has implemented Credit 4. Thus, if our object is to see which items to implement to help us gain LEED certification as easily as possible, Credit 4 would make much more sense for us to implement than Credit 3.
Before we jump to any premature conclusions, let’s try to apply a filter. Filters can make our analyses more appropriate and useful. For example, since our building is a suburban building, it may make sense to see if being a suburban building can impact the results for Credit 3, which deals with Pest Management, Erosion Control and Landscape Management — perhaps, not as many urban buildings have as much of a need for this Credit. These results are shown in Figure 4.
Figure 4 shows an increase in the percentage of buildings that have implemented Credit 3, after a filter to remove urban buildings from the comparison was applied.
As you can see filters are powerful tools to enhance your benchmarking value. 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 comparison