Case 1:

Consider the following case. Suppose a buyer needs to identify which of five car options is best across three evaluation criteria Car Color, Miles per Gallon (MPG), and Price. Furthermore, suppose the criterion MPG is twice as important as the criterion Car Color and Car Color is half as important as Price.

The three criteria are assumed to be mutually preferentially independent. It follows that the additive value function can be used to generate an overall score for the performance of each car across the three evaluation criteria. In this case, the additive value function is

V_Y(y) = w₁Vx₁(x₁) + w₂Vx₂(x₂) + w₃Vx₃(x₃)

where VxX11 (), V x X 2 2 ( ), and V x X 3 3 ( ) are the value functions for Car Color, MPG, and Price, respectively; and, w i i for = 1, 2, 3 are nonnegative weights (importance weights) whose values range between 0 and 1 and where w₁ + w₂ + w₃.

1. Generate right-half of Table using MS Excel

2. Generate a revised Table based on this new set of raw data

Case 2:

Consider Haime's 11 criteria for risk ranking and how they were used to rank failure of sub-system X. Apply Borda Algorithm discussed in Module 5 to rank the failures of these various sub-systems.

Table VII. Scoring of Subtopics for OOTW Using the Criteria Hierarchy

Case 3:

1. Show and explain why critical average and max average rules both generate a risk measure of 64.65 for the node labeled Network Operations Capability portfolio.

2. Suppose presents a portion of a capability portfolio defined as part of engineering an enterprise system. Given the  information shown, apply the risk analysis algebra in Module 6 to derive a risk measure for Capability.

What risks are driving this measure?