Many FMs often seek benchmarking data to measure how their organization is performing. When asked about what they want to learn, they often will reply that a table or chart showing their performance compared to others what they want. Sometimes the CEO will play golf with other executives and they will be told that Company ABC is doing well in securing their facilities and you need to take a look to get more like them. Usually that approach doesn’t work too well.
Comparing data or even processes isn’t a very effective way to improve your performance unless the comparisons are made with a relevant peer group. Here’s why that doesn’t work most of the time . Once you have charted your information, the next question becomes something like, “Do you have that broken down for just: industry type older facilities in my city that operate continuously secured with non-union labor with two guarded access points . etc. Wait, how many visitors do those other facilities have per year?
What is really happening is that the FM is realizing that looking at facilities without any meaningful data is a waste of time—while general numbers may be a good starting point, to make informed decisions, a more detailed breakdown by criteria that affect operating costs is necessary. That is the only way one can compare the benchmarked facility to one that is best-in-class.
We define that “breakdown” as using a set of filters. Each of the below items becomes a filter:
- Industry type
- Age of the facility
- City or region
- Hours of operation
- Union or non-union labor
- Number of employees
- Number of staffed entry points
- Number of controlled access points (card readers)
- Number of visitors
In actuality, there are nearly 30-40 potentially useful filters for looking at security metrics, and more that are germane to other operating costs, such as utilities, janitorial, maintenance, landscaping, etc.
Benchmarking of operating costs is popular among FMs, as these are what the FM can both measure and control. More than 95 percent of operational expenses are incurred by the following four areas:
- Utilities
- Maintenance
- Janitorial
- Security
For FMs there isn’t any single table that contains all the critical data needed for a detailed benchmarking analysis. For security, there may be 30-40 critical dimensions that could be applied and the importance of each will vary by the situation. For example, most FMs would probably expect higher costs for extended hours of operation or with more staffed entry points. But if most employees enter the facility through card access systems then there may not be much of cost premium for extended hours of operation. Let’s test that by using the filters provided by FM BENCHMARKING.
An Example
Let’s look at how the FM can benchmark their security costs, given the above conclusions. We will illustrate an example for security using tools provided courtesy of FM BENCHMARKING. For this example, we will benchmark a 1,325,000 gross square feet (GSF) office building that is 22 years old, operating 18 hours per day. Some of the input fields are shown in Figure 1 below.
The first filter we will turn on is the size of the facility so that we will only consider buildings that are 600,000 GSF or greater and a ‘campus setting.’ In the FM BENCHMARKING system this produces 452 facilities for comparison. In Figure 2, our security cost per gross square foot is shown by the yellow bar with $1.03 per gross square foot which indicates a performance near the middle of the second quartile. Others have higher costs.
Now let’s see if our relative performance compared with these filters might be improved if we modified the peer group. Consider operating hours and see if that has an impact. As shown in Figure 3, our costs relative to our peer group are now closer to the first quartile so operating hours do have some impact, but not a very large one. This probably is an indicator that many security functions are automated, and staffing may be at minimum levels for off-hour shifts, while staffing may be at similar levels when a shift is not running.
This filter moves our relative performance into the first quartile.
This seems like a reasonable peer group for comparison purposes and there is quite a difference in the relative ranking from our initial comparison. By careful application of filters, that are a reflection of our true peer group, our facility has moved from about the middle of the second quartile to the first quartile. percentile to about the 60th percentile.
Many FMs don’t go any further with the benchmarking process but nothing we’ve done so far will help improve your performance. All we’ve done is find out how we’re doing compared to our peer group (filter set). So let’s consider what could be done to improve our performance—isn’t that the purpose of this exercise? To do this, we will look at the best practices that have been implemented by our peer group, which is now the best-performing group in our filterset. However, to make this illustration more interesting, we “bumped” our building into the top-end of the second quartile, so we have the opportunity to compare to buildings in our new quartile (2nd) as well as better performing buildings (1st).
FM BENCHMARKING provides a very useful tool to integrate best practices responses with the quartile results. As shown in Figure 4, we will compare our building’s best practices with those implemented in our quartile and those in the next better quartile.
Shown are just the best practices for Security services. Where our facility has answered NO and there is a high percentage for our quartile and the next better performing quartile, we should consider implementing the practice. For example, we answered NO for ‘BPS5. Internal audit reviews .’ Yet 40% of the participants in our quartile and 100% of the next better performing quartile have implemented this best practice. So this may be something we should look at.
We also should see where there is a large jump in percentage between those in our quartile and those in the next better-performing quartile. These best practices are those that have enabled others to improve their performance and move to the next quartile.
These examples are meant to show how you can use benchmarking with filters to narrow your benchmarked comparisons to a valid peer group and then see which best practices others have implemented. By implementing those best practices, your performance should also improve over time.