A practical approach to effects-based operational assessment

Air & Space Power Journal, Summer, 2008 by Clinton R. Clark, Timothy J. Cook

Methodology Demonstration

This section applies the OA methodology developed in the previous section to a notional example (see table 3 for a generic plan framework). Admittedly incomplete, the plan nevertheless highlights the benefits of effects-based OA. The responsibility for developing such a plan falls to the strategy division, of which the OA team is a critical component. Therefore, the team should not undertake this task alone; conversely, it must not be excluded during development of the hierarchy. Any strategy-to-task hierarchy constructed without assessment in mind from the beginning will likely contain immeasurable portions that will force assessment back into the realm of an exclusively gut feel. (21)

Now that the plan is complete, we can build the effect and performance models. Figure 6 depicts the effect-scoring model for our generic plan, including the model structure and relative importance weights for each objective, effect, and MOE. Figure 7 provides the structure of the performance-scoring model, with relative importance weights shown for each objective, effect, task, and MOP.

[FIGURE 6 OMITTED]

[FIGURE 7 OMITTED]

We can use several techniques, such as "pricing out," "swing weighting," or "lottery weights" to derive the hierarchy weights. (22) A detailed discussion of these methods lies beyond the scope of this article, but it is important to note that the method chosen depends upon the personality, values, and experience of the commander--not the analyst. The method most straightforward to the commander will prove most useful in eliciting his or her true belief system.

With the structure defined and weights elicited, we can build an assessment tool. The calculations required by this methodology are rudimentary enough to be performed by hand, with a calculator, or in a simple spreadsheet model. The next section highlights the simple mathematics required to produce effect and performance scores for this notional example.

Model Calculations for Air Tasking Order "A"

This section walks the reader through the mathematical mechanics of our methodology for a sample data set. Tables 4 and 5 supply notional data for one ATO period we call "ATO A." The "observed" column contains notional observations, and the "Value" column the resulting individual utility scores. Again, higher scores are better, with a maximum value of one.

The calculations below determine the individual effect score for the notional effect "friendly fighter operations unaffected by enemy action," using equation 3 ("individual effect scores"), the weights from figure 6, and the values from table 4. For each MOE, we multiply the assigned relative-importance weighting by its observation value from ATO A. We then sum the three MOE scores to produce the individual effect score of 0.25. As previously stated, scores are between 0 and 1; a score of 0.25 would indicate to the OA team that we have far to go to realize the desired effect.

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