Corporate decision analysis : an engineering approach

We explore corporate decisions and their solutions under uncertainty using engineering methods. Corporate decisions tend to be complex; they are interdisciplinary and defy programmable solutions. To address these challenges, we take an engineering approach. Our proposition is that as in an engineering system, corporate problems and their potential solutions deal with the behavior of systems. Since systems can be studied with experiments, we use Design of Experiments (DOE) to understand the behavior of systems within which decisions are made and to estimate the consequences of candidate decisions as scenarios. The experiments are a systematically constructed class of gedanken experiments comparable to "what if' studies, but organized to span the entire space of controllable and uncontrollable options. In any experiment, the quality of data is important. Grounded on the work of scholars, we develop a debiasing process for eliciting data. And consistent with our engineering approach, we consider the composite consisting of the organization, their knowledge, data bases, formal and informal procedures as a measurement system. We then use Gage theory from Measurement Systems Analysis (MSA) to analyze the quality of the measuring composite.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Tang, Victor, Ph.D. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Warren Seering.

• Engineering Systems Division.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/37273

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/37273