By Peter Sells
The ultimate measure of a man is not where he stands in moments of
comfort and convenience, but where he stands at times of challenge and
-Martin Luther King Jr., Strength to Love, 1963
By Peter Sells
The ultimate measure of a man is not where he stands in moments of comfort and convenience, but where he stands at times of challenge and controversy.
-Martin Luther King Jr., Strength to Love, 1963
How many firefighters are enough? What is the right staffing level and staffing model for a municipality?
|An analysis of staffing of 14 fire departments shows an average of one full-time firefighter per 1,000 residents. Numbers in composite departments follow a more complex formula. Photo by Laura King
These are questions a fire-protection management consultant needs to be able to answer. It seems like a fairly straightforward problem to solve. I had always heard of a rule of thumb of one firefighter per 1,000 people, but I couldn’t source that rule or how it was determined. I suppose that I could have tried to derive a formula based on population density and response time, then plugged in specific parameters for fire ground staffing based on 20 full-time firefighters per apparatus, each working 42-hour weeks on average. But how could I factor in financial factors such as salary, benefits, capital and operating costs for stations, apparatus and equipment, then balance that against a municipality’s ability to pay based on its tax base? Deriving a staffing formula from scratch is more complex than I had figured.
So, instead of working from the ground up, I decided to look at the issue from an empirical viewpoint.
According to Wikipedia, the empirical method is using a collection of data on which to base a theory or from which to derive a conclusion. You observe the existing data and come up with an explanation, rather than starting with a theory and testing it through experimentation. So, the next step was to look into the staffing of some fire departments.
I did an analysis of fire-service staffing of 14 mid-sized Ontario cities and towns, with populations of between about 90,000 and 205,000. These are populations large enough to afford full-time career staffing. Several municipalities in that range with composite staffing were excluded from the analysis, in order to ensure that I was comparing apples to apples. Each of the 14 municipalities is relatively homogeneous in terms of its city form, whereas those with composite staffing provide protection over vast expanses of rural territory in addition to their town cores. In all cases, only responding firefighters (assigned to suppression or operations), and command officers were included in the staffing tally.
To my surprise, the numbers crunched out in support of the mysterious rule of thumb. On average, career fire services are employing almost exactly one firefighter per 1,000 residents (0.9954 to be exact). There were a few statistical outliers on the high and low ends, but the majority of those 14 departments were within nine per cent of the average.
For some municipalities with fluctuating populations, this model is not appropriate or at least must be placed in context. For example, Toronto’s resident population of 2.6 million routinely increases each day to almost 3.5 million – that’s like having all of Nova Scotia show up for work every morning and go home every night. During special events such as the Santa Claus parade or a Leafs Stanley Cup celebration (hey, it could happen!) you could toss in New Brunswick as well. On a smaller scale, resort communities across Canada swell on a seasonal basis, sometimes by several times their resident population. An example right in the middle would be the city of Niagara Falls, where the number of visitors in July and August causes the population to increase by about 90 per cent. In all of these cases, staffing the fire service through a simple population ratio is too simplistic a formula.
I had been talking to Process Evolution, a U.K.-based company that makes software to analyse, design and evaluate shift schedules and deployment models for emergency services. Modelling software can take into account variables such as fluctuating populations, seasonal industries and historical response statistics. Police and EMS are familiar with variable shift schedules – higher staffing during some time periods and lower staffing during others. Process Evolution has been able to achieve some impressive efficiencies for some of its U.K. fire-service clients using similar methods, but the North American fire service is largely based on a standing-army model of consistent staffing 24/7/365 to protect our cities and towns. It’s hard to imagine a big Canadian city having fewer firefighters on duty at night and the surrounding bedroom communities having fewer during the day. A more detailed analysis of local needs and circumstances of each municipality would be required in order to determine appropriate staffing levels.
What about the staffing of composite fire services? To complete this part of the analysis I had to make one assumption, the validity of which I will leave for readers to judge. If a municipality has a volunteer component to augment its on-duty career firefighters, then there is likely a deficit between the population expressed in thousands and the number of career firefighters employed. That deficit should then be a fraction of the number of volunteer firefighters maintained within the local system. I set out to determine that fraction, which I will call the volunteer factor. Here is my assumption as a formula;
(Population/1000) – (# of career firefighters)
= (# of volunteer firefighters)/(volunteer factor)
To determine the volunteer factor, I looked at another 17 departments, all with composite staffing, serving populations of between 13,000 and 505,000 people. After applying the above formula, those 17 have a volunteer factor of 5.42 on average. The volunteer factor crunches out at 4.82 when all 17 departments are taken collectively. In round numbers, then, we can conclude that a deficit in career staffing is effectively augmented by volunteer staffing of five times the deficit.
As an example, let me give you a hypothetical town of 90,000 people, an amalgamation of four previous towns and villages. There are four areas that are built up, one of which contains about half of the town’s population, two of which house between 15,000 and 20,000 people, and one that is little more than a crossroads with a few dozen homes and businesses surrounded by rural farmland. The bigger area has a career station with a rescue pumper, a quint and a command van; the two mid-sized areas each have a one-truck career station; and the rural community has a volunteer station with a pumper, a rescue truck and a tanker. The four career-staffed apparatuses are each staffed by 16 firefighters and four company officers, and there is always a platoon chief on duty, totalling 84 full-time staff on four shifts. According to my formula using a volunteer factor of five:
(90,000/1000) – 84 = (# of volunteers)/5
Rearranging the formula,
# of volunteers = (90-84) x 5 = 6 x 5 = 30
If the formula and the volunteer factor are valid, then we would expect that the rural station is staffed by 30 firefighters and officers. Sounds pretty reasonable to me.
It is important to not read into this analysis any judgment on the value of career versus volunteer firefighters, either individually or collectively. The analysis is not based on any assumptions about the amount or quality of work performed by firefighters on the fire ground, regardless of their employment model. I have written before that fire-service staffing is not one size fits all, and that composite or volunteer staffing can often allow for greater numbers of firefighters on scene than could be afforded by career staffing in all but the largest cities. This is an empirical analysis of fire service staffing, nothing else. Any interpretation as to the effectiveness of firefighters on the fire ground is taking these conclusions out of context.
With deference to Dr. King’s quote above, we all stand together in times of challenge; there is no need to create false controversy.
Retired District Chief Peter Sells writes, speaks and consults on fire service management and professional development across North America and internationally. He holds a B.Sc. from the University of Toronto and an MBA from the University of Windsor. He sits on the advisory councils of the Ontario Fire College and the Institution of Fire Engineers, Canada branch. Contact him at email@example.com