Many FMs are often seeking benchmarking data to measure how their organization is performing. When asked about what they want to learn they will often reply that they would like to see a table or chart showing their buildings’ performance compared to others.
In this article, we will be looking at utility costs, as they are very much in the mind of today’s facility professionals. However, the methodology and analysis presented here are identical to what can be done to study other types of operating costs, such as those for maintenance, janitorial, security, landscaping, etc.
The Starting Point—Defining Your Peer Group
Most people who benchmark realize that unless the comparisons are made with a relevant peer group, the comparisons may not be of significant value to the organization. We later will explore ways of taking these comparison data to help us improve our buildings’ performance, but for right now, let’s just try to identify a relevant peer group.
We’ll look at the cost-based best practices (instead of the consumption-based ones) for this exercise since most CFOs and others in senior management are highly focused on cost metrics (we will come back to consumption later).
For these examples, we will use a very large manufacturing facility located in Florida and compare its utility costs with several different peer groups to see how its building is doing. From this type of analysis, we will learn how to define just the right peer group of buildings.
In Figure 1 below, our utility costs are $2.33 per gross square foot (GSF). We have shown the 1st Quartile, Median and 3rd Quartile points for reference. Note that our building’s utility costs are midway between the 1st Quartile and Median (in other words, in the top half of all performing buildings).
Filter 1: Size of Facility. If we filter this sample for size of the facility (see the right side of Figure 1), looking at only larger buildings (those greater than 600,000 GSF), our relative performance drops just a little — an insignificant amount. Clearly the size of the facility is not a critical factor in benchmarking utility costs, although in the worst performing facilities, the larger facilities are spending less per GSF ($4.51 versus $4.86 per GSF).
One also can note that there is quite a range in utility coststhis is probably due to a combination of certain types of filters (other than facility size) and perhaps less implemented best practices in the worse-performing facilities. Benchmarking can help identify these differences and what can be done about them.
Figure 1 — Utility Costs per GSF filtered by size of facility. The results indicate that size of facility does not have a significant impact on utility costs per GSF. Provided courtesy of FM BENCHMARKING.
Filter 2: Type of Facility. Let’s take a look at the type of facility and see if this has a significant impact on our benchmarked costs. We’ll refer to Figure 2 below; the left side (without any filters assigned) is, of course, the same as in Figure 1. The cost of our utilities is still $2.33 per gross square foot (GSF); it won’t change no matter what peer group we compare ourselves to.
Based on this filter set, our buildings utility costs are midway between the 1st Quartile and Median. There doesn’t appear to be much improvement for us through use of this filter. However, the 3rd Quartile performance of manufacturing facilities improves by about 10 percent. So this filter may be a good one for those who are in the worse performing buildings (3rd and 4th Quartile buildings), but not necessarily for those in the better performing buildings, such as our building. So let’s look at another filter.
Figure 2 — Utility Costs per GSF filtered by type of facility. The results indicate that type of facility does not have a significant impact on utility costs per GSF. Provided courtesy of FM BENCHMARKING.
Filter 3: Climate Type. Perhaps climate type may have a more significant impact on our total utilities costs. In Figure 3 below, we compare our costs to our peer group in similar hot and humid climates. This really changes our reference points. Notice that our first Quartile’s peer group costs are about 10 percent higher for the “hot and humid” climate type and our relative performance has moved to nearly the first quartile (a significant improvement). Climate type clearly has a significant impact on our utility cost performance.
It also is interesting to note that whereas when analyzing data by building size and type of facility, the third Quartile’s buildings were about 10% better (lower utility costs) than when looking at the entire database without filters applied. Yet, in the analysis by climate type, the third Quartile’s costs were slightly higher than the costs for the rest of the database.
Figure 3 — Utility Costs per GSF filtered by climate type. The results indicate that climate type does have a significant impact on utility costs per GSF. Provided courtesy of FM BENCHMARKING.
More filters. What is really happening here is that the FM is realizing that looking at facilities without good peer group comparisons is a real waste of time. To do this, one needs tools to identify the most appropriate peer group(s) for each specific situation. General numbers such as the ones in this paper are a good starting point, but to make informed decisions, one will require a more detailed breakdown by criteria that affect operating costs is necessary; these criteria are really filters. Our research has indicated that there are over 60 such filters that can have an impact on a building’s performancethe trick is to identify those that apply to any given building. That is the only way one can compare the benchmarked facility to one that is best-in-class.
Here are some of the most useful filters:
- Industry type
- Age of the facility
- Climate type
- Hours of operation
- Days of operation
- Union or non-union labor
- Number of employees
- Facility condition index
About 40-50 of the filters are useful in general, and 10-20 more are useful when analyzing specific metrics, such as for utility costs and consumption, maintenance costs, janitorial costs and security costs. It should be apparent that the same building may very well have a different peer group (set of filters) for each type of metrics being analyzed.
Identifying the most relevant comparison (filter) sets, as we started to do above, yields useful information:
- We have learned which types of data on which we should focus.
- We have seen where our building stands in relation to other buildings that are truly similar; i.e., we have created a “scorecard.”.
- We have a sense of what reasonable utility costs are for our facility.
However, here is what we don’t yet know and what we have not done:
- We don’t know if there is anything we can do differently to get our building into the first Quartile.
- If there is something we can do, we don’t know what that is.
Benchmarking, when integrated with best practices, will yield the answers to the above two questions. In next month’s benchmarking article, we will show how that can work in the area of utilities.
