Happy Birthday to the one and only Tom "Guitarman314" Eve
The ?G-Man Theory? is an excellent example of ?good ole? common sense and intuition expressing observations made over a long time into a theory that is actually based on very sound statistical calculations.
Every unit has a historical unavailability factor based on the percentage of hours that it is committed to responses, training, maintenance, etc. The addition of EMS responses or the elimination of units contributes to unavailability. The more responses a unit makes, the greater number of responses it will potentially miss.
The ?G-Man Theory? accumulates these unit percentages across all of the units on a first alarm assignment. For simplicity, if every unit had a 1-in-10 unavailability, the probability that any one unit on the first alarm assignment, without indicating which one in particular, will be unavailable, is cumulative. If the first due assignment is four units, the probability that one of them is unavailable would be 4-in-10. Small odds ? less than half of the time. However, when there are 8 units on the first due assignment, the odds are better 8-in-10. Throw in the BC?s, the Squad and the Rescue and the odds are least 10-in-10 and you get the statistical certainty. ?G-Man Theory? works!
The corollary also works because it applies to ?big jobs.? A 10-75 loads up the 1st alarm assignment and that loads up the probability for the ?G-Man Theory.? But does it only work for 10-75?s? Actually, it works all of the time overall (time of day is also a factor, but that is another layer of complexity). However, when a first alarm assignment does not result in a 10-75, it doesn?t get nearly as much attention or discussion because there are fewer adverse consequences.
The "G-Man Theory" is really the "G-Man Effect." Budget and policy makers should be more aware of it.
