Because of the emotional issues involved when human lives are at stake, many consider public safety the most essential of all city services. But because these services bring in little, if any, revenue, fire and police protection often are targeted above revenue-producing areas when budget cuts are needed. In the past, emotional appeals based on the safety of human life were utilized to justify continued and increased funding for fire and police protection. However, we no longer can rely simply on emotional appeals to justify our budgets—-we need to support our appeals with facts and evidence.

The nature of fire protection has made it difficult to measure effectiveness and productivity. The question “How can you put a price on a human life?” is enough to stifle most attempts. But while you cannot objectively measure in dollars something as subjective as a human being’s potential and personality, the fact remains that life, or a loss of life, is a factor that helps measure the effectiveness of fire protection.

Property, on the other hand, lends itself readily to economic analysis and therefore often is used to express fire protection values. The figure used most often is the value of lost property. The dollar amount of property affected by fire losses, like life safety, is just one factor affecting the overall measurement of fire protection.

The insurance industry uses a formula involving property value, fire loss, and several other factors to determine insurance rates. The ISO grading system and the key rate, which are used for the purpose of selling insurance rates, often are quoted as measures of fire protection effectiveness. They were not intended for this use (see “Lessons in Productivity,” Fire Engineering, February 1989).

What we need is a method or formula to calculate the effectiveness of each dollar spent on fire protection. A method of calculating the cost effectiveness of fire protection would be a valuable tool for a fire chief during budget justifications. Once a measurement of effectiveness has been determined, the issues of efficiency and productivity can be addressed. Attempts to alter efficiency and productivity without an adequate measure of effectiveness may appear to be working, but how can we determine if they really are? Take, for instance, the municipal fire department that starts recording the hours each shift spends at various activities as a “measure of productivity.” But without some measure of output, this amounts to nothing more than a measurement of hours. It may not even be an accurate measurement because most personnel probably record the number of hours the administration wants them to report, regardless of the actual time spent on the activity.

The need for some method of output measurement is necessary before the fire service can address efficiency and productivity issues. But first we must find a measurable unit of output. Since fire protection input is measured in dollars, we should be consistent when calculating output. The expression that comes up most often in discussions of fire protection effectiveness is the fire loss value. However, this number can be misleading in and of itself. This is illustrated by creating two hypothetical cities, A and B. Both cities are virtually identical in most measurable areas, for instance, in the size of the fire departments or availability and efficiency of water supply or in insurance ratings. The fire statistics for both cities havebeen relatively static over the past five years, growing only slightly in relation to population growth. For simplicity, we will use dollar figures and statistics that may seem small to many city fire departments.

This year, each city had a total fireloss of approximately 5250,000. This figure seems to indicate that the cities provide roughly equivalent fire protection. However, fire records show that City A had 10 fires resulting in the total loss of nine homes and businesses, each valued at about 525,000, and the partial loss of 525,000 to a home valued at SI00,000. City B, on the other hand, had only two fires, one that totally destroyed a 525,000 home and one that destroyed about 20 percent (5225,000) of a business valued at SI,125,000. Does it still look as though both cities are equally effective at fire protection? Obviously, some data must accompany the fire loss value if the fire protection effectiveness is to be accurately determined.


If we take the total number of fires into account, City B has a higher loss per fire (SI25,000) than City A (S25.000). The arithmetic value of the loss per fire is correct, but its value in measuring fire protection effectiveness is still unclear. To get a true fire loss picture, the percentage of damage to the exposed property must enter into the calculation. Calculating an average based on the percentage of Involved Property Destroyed Per Fire (IPDPF) in each city makes the picture clearer. City A averages 92.5 percent IPDPF, while City B averages only 60 percent IPDPF. In other words, City A saves about 7.5 percent of fire-involved property, and City B saves about 40 percent of fire-involved property.

At this point we still do not have the information we want. Did City A save 7.5 percent of the property involved in dumpster fires or in house fires? Instead of basing our average on the percentage of property saved or destroyed, let’s go back and figure the percentages again, using dollar amounts for the property, dividing the dollar amount of property involved but saved by the dollar amount of total property value. I will refer to the resulting figure as the Property Coefficient (PC).

Dollar amounts are used in figuring the PC because they easily can be obtained through tax rolls and insurance files. The PC always will be a number between zero and one. A completely effective fire protection system will be represented by a PC of one, since there will be a negligible difference between the value of property involved and the value of property saved. It is not likely that any fire protection system will achieve absolute effectiveness unless some measure that entirely eliminates fire occurrence is developed. The other end of the spectrum, a PC of zero, indicates a total property loss. Figuring the PC for our two hypothetical cities shows that City A has a PC of 0.231, representing a relatively ineffective system, and City B has a PC of 0.783, representing a more effective system.

For most cities, this calculation will not involve any massive changes in record keeping because the only additional figure that needs to be recorded for each fire is the total value of the property involved. This does not even have to be done at the time of the fire; it can be determined later during a follow-up visit. Unlike the ISO grading system and the key rate, the PC is a direct measure of a fire protection system’s effectiveness in relation to property.


The PC still does not completely measure fire protection effectiveness, however, because the factor of life safety is not considered. Any dollar value assigned to a human life is subjective and therefore docs not represent anything. We do have an objective way of measuring the life safety component of fire protection— statistics on fire deaths and injuries. Let’s use this factor as we did the dollar values of property to determine a property coefficient—divide the total number of lives involved but saved by the total number of lives involved. We ll call the resulting number the Life Safety Coefficient (LSC). Like the PC, this number will fall between zero and one, with total efficiency resulting in an LSC of one and total inefficiency resulting in a LSC of zero.

Keep in mind that in referring to the system I mean the entire fire protection system, not just the reaction of fire suppression forces to one or more incidents. Thus, if the system’s public education efforts successfully educated the public about proper fire safety and emergency behavior, which in turn enabled some members of the public to escape from a fire, it can be considered a result of the system the same as if suppression forces had rescued the people directly from a burning building. Collecting data for the LSC is as simple as collecting those for the PC. The only addition to the information currently gathered is the total number of occupants within the involved structure at the time of the fire.


Property Coefficient (PC)

PC = PS/P1 Property Coefficient – Property saved (in $s) – Property valve (in $s)

Example: 1

Total value of all property involved in fire for the year (flür market or assessed value prior to fire): City A = 325,000 City B = 1,150,000

Total fire loss for the year: City A = 250,000 City B = 250,000

Dollar amount of property saved for the year:

City A = 25MOO – 250.000 75.000

City B = 1,150,000 – 250,000 = 900,000

PC City A = 75,00 ÷ 325,000 = .231

City B = 900,000 ÷ 1,150,000 = .783

Life Safety Coefficient (LSC)

LSC = LS/LI Lives saved Life Safety Coefficient lives involved

Example 2:

Total number of lives exposed during the year:

CityA3O CityB=102

Total fatalities for the year: City A = 7 City B = 7

Total lives saved for the year: City A = 30 – 7 = 23

City B = 102 •-~7 = 95

LSC City A = 23 ÷ 30 = .767 City B = 95 ÷ 102 = .931

Effectiveness Coefficient (EC)


Let’s return to our two hypothetical cities, A and B. This year, unfortunately, both cities suffered some loss of life due to fire. In a tragic nighttime fire in City A, seven members of one family perished when their home burned as they slept. A total of 23 occupants were in the other nine buildings that burned in City A. They all escaped or were rescued. Thus, the total number of lives exposed in City A was 30. City B also lost seven people during a large fire at a business establishment, which contained 97 occupants at the time of the fire. There were also five occupants who escaped from the one residential fire, bringing the total number of lives exposed to 102 for City B. Thus, City A had an LSC of 0.767 and City B had an LSC of 0.931. We now have a relative measure of life safety, which was obtained without assigning a dollar value to human life.


Let’s see how the two measures of effectiveness described so far can be used to calculate a single composite measure of effectiveness.

At this point I will make the assumption that life and property figures contribute equally to the measurement of fire protection effectiveness. On an emotional basis, one certainly could argue that this is not the case; but for our purpose, emotions must be left out. Let’s return to our hypothetical case studies. We now have two factors for each city. City A has a PC of 0.231 and an LSC of 0.767, and City B has a PC of 0.783 and an LSC of 0.931. Assuming both coefficients contribute equally to the final indicator, averaging the PC and LSC for each city obtains what we will refer to as the effectiveness coefficient (EC). These calculations result in an EC of 0.499 for City A and an EC of 0.857 for City B.

We now have a measure of property conservation, a measure of life safety, and a composite measure involving both. The numbers are verifiable and objective. The coefficients can be used by themselves for relative comparisons among cities or for yearto-year analysis within the same city.

What I have presented is the preliminary development of one possible method for fire protection measurement. The thrust of future research should be on fully developing the measurement of fire protection effectiveness, as this forms a foundation for addressing the efficiency and productivity issues relevant to the fire service. The threat to municipal fire departments is expressed in economic terms (dollars) by those with supporting statistics (city managers and councils). The future of the fire service depends on its ability to adapt itself to change and defend itself against external threats. And it is only after we determine our present level of effectiveness that we can present an accurate and justifiable plan for the future.

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