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Author Lawson, Catherine A
Title Business process characterization using categorical data models
book jacket
Descript 120 p
Note Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1110
Adviser: Douglas Montgomery
Thesis (Ph.D.)--Arizona State University, 2005
Variation exists in all processes, especially business processes where critical variables may be controlled by human intervention. Significant returns may be realized by identifying and removing sources of variation from business processes. Because business processes tend to be heavily dependent on human interaction, they can be difficult to characterize and model. This research develops a methodology for synthesizing the qualitative information about the performance of a business process and transforming it into specifically defined categorical data that can be used for statistical modeling and optimization. The process under investigation is the identification and pursuit of new business opportunities for a Department of Defense (DoD) prime contractor. This process is heavily dependent on the people who obtain information about potential opportunities and make decisions about whether to pursue an identified opportunity. This research explores methods for taking the demographic, anecdotal and qualitative data associated with particular business opportunities and creating categorical data sets that can be statistically modeled. This research illustrates how binary logistic regression was used to analyze these data and establish significant relationships between these key process attributes and the process outcome which is either the win or loss of the opportunity
School code: 0010
DDC
Host Item Dissertation Abstracts International 66-02B
Subject Engineering, Industrial
0546
Alt Author Arizona State University
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