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This technical note shows how designers of infrastructure systems can evaluate flexibility in engineering systems in fairly simple ways. Specifically, it illustrates a spreadsheet approach to valuing "real options" in a project. The model avoids complex financial procedures, which are both inappropriate for most design issues and constitute barriers to understanding and thus achieving the substantial improvement in performance that real options enable. The spreadsheet approach uses standard procedures; is based on data available in practice; and provides graphics that explain the results intuitively. It should thus be readily accessible to practicing professionals responsible for engineering design and management. A practical application to the design of a parking garage demonstrates the ease of use and presentation of results of this approach.

This note describes a simple procedure for assessing utility functions which avoids many difficulties of the standard techniques. The conventional methods suffer from at least three drawbacks; they (1) generate utility functions that depend on the probability levels used; (2) chain responses from one question to the next, so that any bias is propagated and even magnified; and (3) change ranges and reference points constantly, introducing range effects and other distortions. Noting the evidence linking the dependence of utility functions on the “certainty effect,” our method: (1) compares lotteries with other lotteries rather than certain amounts; (2) does not “chain” responses; and (3) consistently uses “elementary lotteries” which control for range and reference points. Experimental work supports the proposed procedure.

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The "traditional" way of designing constellations of communications satellites in low Earth orbit is to optimize the design for a specified global capacity. This approach is based on a forecast of the expected number of users and their activity level, both of which are highly uncertain. This can lead to economic failure if the actual demand is significantly smaller than the one predicted. This paper presents an alternative flexible approach. The idea is to deploy the constellation progressively, starting with a smaller, more affordable capacity that can be increased in stages as necessary by launching additional satellites and reconfiguring the existing constellation in orbit. It is shown how to find the best reconfigurable constellations within a given design space. The approach, in effect, provides system designers and managers with real options that enable them to match the system evolution path to the actual unfolding demand scenario. A case study demonstrates significant economic benefits of the proposed approach, when applied to Low Earth Orbit (LEO) constellations of communications satellites. In the process, life cycle cost and capacity are traded against each other for a given fixed per-channel performance requirement. The benefits of the staged approach demonstrably increase, with greater levels of demand uncertainty. A generalized framework is proposed for large capacity systems facing high demand uncertainty.

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