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Community protection factor: A new way to demonstrate station availability

The CPF measures the time available to respond to incidents from their district within the designated response time parameters


Photo/Windsor Severance Fire Rescue

By Battalion Chief Jon Nevin, Ph.D.

“You can’t manage what you can’t measure.” — Peter Drucker

“Not everything that can be counted counts, and not everything that counts can be counted.” — Albert Einstein

As analytics and data continue to play an expanded role in fire department operations, managers are faced with the challenge of using the right metrics to make large-scale decisions on resource deployment. These decisions can be both near-term or long-term, directly impacting properties and lives saved, and having significant labor and capital costs tied to them.

How we measure “busy”

As emergencies tend to be time-sensitive, much of our analysis is tied to time – turnout times, response times and effective fire force calculation. While this may seem like the most intuitive way to measure fire department capabilities, it is only a one-dimensional slice of risk evaluation; it is a reactive look at capabilities, not a view of proactive overall community protection.

In addition to temporal measurements, another evaluation that has become increasingly prevalent in the fire service is unit production measurements, most commonly unit hour utilization (UHU). UHU looks at the percentage of time that a unit is committed to an incident from dispatch to available. This measurement has been prominent in ambulance analytics for decades and was typically tied to revenue maximization.

The use of UHU in the fire service is often to demonstrate how “busy” a unit is and whether there is a need for additional units to be added. A challenge facing UHU is that there is no industry standard defining the critical UHU level, and in its basic form, it doesn’t take into consideration the ancillary duties that take up a large share of a fire company’s time (training, public education, etc.).

While there is a narrow window of usefulness of UHU when evaluating the workload of a fire company, one of its main weaknesses is the lens through which it evaluates. Instead of focusing on the availability of fire companies, it focuses on the workload of fire companies – the inverse of availability.

Moving back to our mission

As fire departments have endured massive shifts in the quantity and characteristics of their call loads over the last 40 years, an underlying philosophical shift has occurred where everything is now evaluated from a response window. Call volume, response times and mutual-aid use dominate the metrics of the modern fire service. Previously, the fire service was seen as a net of protection for a community.

As we have been stretched thin and low-acuity calls for service have inundated 911 systems, we have been drawn away from our most basic core competency – the ability to quickly respond to and mitigate life- and property-threatening emergencies. We need to think of our role in the community as a protective framework and safety network for fire and rescue emergencies. The most basic truth of the fire service’s role in the community is that we have nothing more valuable to offer the community than a fire company available in-district. Every time we empty a station to respond to a low-acuity call, we have stripped that valuable asset from its availability to protect.

Deploying the CPF

With those concepts in mind, and combining the importance of response times, a primary metric that we should consider using to evaluate our overall capabilities is the community protection factor (CPF), which can be defined as the percent of time over a year that fire companies are available to respond to incidents from their district within the designated response time parameters. This needs to be calculated for each fire station district. If a department has advanced mapping and analytics capabilities, this can also be performed by breaking the city into a grid to evaluate CPF on a more micro level.

In a dense, urban environment, there may be a highly concentrated number of fire stations in a community, but if they’re all responding to 15-20 runs a day, then that community suffers from a lack of available first responder protection. Alternatively, a rural area may have a very low call volume and thus high unit availability but does not have the density of stations to provide quick response to most emergencies.

CPF also needs to include known/assumed out-of-service time since presumably no company will have 100% availability. In addition to out-of-service training, a small allotment for miscellaneous out-of-service time for mechanical issues, etc., should be included.

As an example, if an engine company at a single house is expected to have nine hours of committed training time monthly across each of three shifts and is also assumed to have three additional hours out-of-service for miscellaneous needs, the CPF would be calculated by taking the 8,740 total hours in a year, minus the 27 hours of training a month and the three additional monthly hours for the out-of-service time. In this situation, the maximum base CPF possible would be 95.9% before including time committed on responses. If that same company then averages 2.4 hours on responses daily, then they would have 7,504 hours of availability remaining and a CPF of 85.9% (7,504 divided by 8,740, multiplied by 100).

The response time requirement used for the CPF is based on each jurisdiction’s situation. Ideally, the NFPA standard of 5:20 would be used, however, some agencies may have other pre-defined response goals based on the staffing/geography of their region. The concept of the CPF centers on the ability to arrive quickly for the most time-sensitive and critical emergencies, so setting a longer time requirement blunts the realities of not being able to respond to cardiac arrests or incipient fires quickly.

In sum

While there is no one-size-fits-all metric for fire departments, the CPF can play a helpful role for both fire department and municipal managers to evaluate response capabilities. Additionally, these figures can be examined year over year to see trends in CPF or compared to other jurisdictions. This presents an easy-to-understand dataset that can be used to study vulnerabilities in coverage and assist with future planning.


About the author
Jon Nevin, Ph.D, is a battalion chief for a municipal fire department in Southern California. He has a background in statistics and analytics, and his doctoral research was on emergency patient outcomes. Nevin is currently a student in the Executive Fire Officer Program at the National Fire Academy, as well as the Executive Leadership Program at the University of Southern California.