2015Unpublished venueRequires access

Creating Value: Data Exploration, Multiple Objectives, and Real Options

Robert T. Clemen

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Abstract

One of the key tasks of decision analysis is to help a decision maker identify better decision opportunities than those that the decision maker started with. The use of data exploration and the adoption of multiple objectives can help a decision maker uncover such decision opportunities -- real options -- that are either future opportunities that the decision maker might not have recognized, additional alternatives for the current decision, or completely new decision opportunities. The concepts are illustrated via a fictional example from the pharmaceutical industry. Implications for information and decision support systems design are discussed in the conclusion.

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What this paper is about

One of the key tasks of decision analysis is to help a decision maker identify better decision opportunities than those that the decision maker started with. The use of data exploration and the adoption of multiple objectives can help a decision maker uncover such decision opportunities -- real options -- that are either future opportunities that the decision maker might not have recognized, additional alternatives for the current decision, or completely new decision opportunities. The concepts are illustrated via a fictional example from the pharmaceutical industry. Implications for information and decision support systems design are discussed in the conclusion.

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Available abstract

One of the key tasks of decision analysis is to help a decision maker identify better decision opportunities than those that the decision maker started with. The use of data exploration and the adoption of multiple objectives can help a decision maker uncover such decision opportunities -- real options -- that are either future opportunities that the decision maker might not have recognized, additional alternatives for the current decision, or completely new decision opportunities. The concepts are illustrated via a fictional example from the pharmaceutical industry. Implications for information and decision support systems design are discussed in the conclusion.

Key concepts: Decision maker, Decision analysis, Decision engineering, Decision support system, Business decision mapping, Computer science, Key (lock), R-CAST

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