priate staffing level to meet the desired level of service and also allows for system improvements to be evaluated in terms of their impact on overall system performance.

The committee has assumed in Figure 4-1 that all instances of service denial are equal, so that probability of service is the only measure of performance or effectiveness. However, the definition of service also needs to include a dimension of severity of consequences. The same outage (e.g., of a Primary RADAR or Radio channel) has far greater consequences at a major airport or en route sector than at a regional airport. Severity measures could include the number of flights affected or even the number of near-miss or actual collisions. This finding of differential impact from the same event implies that two staffing sites requiring the same probability of service should not necessarily be equally staffed. Almost any safety management system will include the two dimensions of probability and severity in assessing risks (see Figure 3-3, as an example), so this concept is certainly not novel to the FAA.

A model incorporating both stochastic demand and stochastic ATSS staffing levels would be much more realistic than a simpler deterministic model. Such a model would also enable those responsible for staffing ATSS to show the impact of the chosen staffing levels on the measure of most direct interest to the FAA’s air traffic management customers: the service level of the NAS. Whether a deterministic or a stochastic model best meets the needs of the FAA is a decision that needs to be made based on the inputs and modeling effort required in relationship to the outputs needed—and in particular the potential consequences of ignoring the stochastic relationships. That decision should not be based on cost and convenience alone.


This chapter has taken the modeling approaches and criteria developed in Chapter 3 from staffing model knowledge and has applied them to the WSSAS model, the Tech Ops District Model, and the proposed Grant Thornton approach to modeling. First, the factual basis of three models was tabulated and assessed in terms of the criteria. Next, other sources of successful modeling in similar situations were assessed for the insights they might add to the future models of ATSS staffing developed by the FAA.

The committee can summarize the attributes and the evaluation of models based on these attributes as a set of statements about what are good criteria for the FAA’s future modeling efforts. The best science currently available supports the following recommendations for a valid and usable model.

Recommendation 4-1: The FAA should develop a new ATSS staffing model based on the modeling framework and criteria developed in this report. The model should be developed using a model structure that is based on equipment inventory, failure rates, and time to perform each task, and should include any valid allowances and accommodations. The model structure should include both deterministic and stochastic estimates for variables such as task duration, as appropriate. The developed model structure should be based on the different specialties of ATSS technicians, rather than providing just an overall staffing level at each facility.

Recommendation 4-2: The FAA should develop a model that captures stochastic elements, unless it can be demonstrated that stochastic aspects of the maintenance process have no material effect on the staffing. For example, some tasks may exhibit multiple deterministic durations of identifiable elements, rather than strictly stochastic durations.

Recommendation 4-3: The FAA should incorporate data for the model that are appropriate to the duration and frequency of the tasks modeled and to its data collection capabilities. Specifically, the FAA

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