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Abstract
Because of dynamic, complex and competitive environments, many information technology (IT) projects are plagued by significant cost overruns and unexpected schedule slips. Research suggests that a major reason for project failures is management’s inability to address uncertainty during the development of a new management information system. Dealing with project uncertainty consists of three main segments: identifying sources of project development uncertainty, quantifying project uncertainty, and using such uncertainty measure for improving decision making process with respect to projects. While the first segment has been a major concern for researchers and practitioners, very little progress in the way of theoretical development has been achieved in the areas of uncertainty quantification and its use in project management. This paper explores various aspects of project uncertainties and offers three entropy-based uncertainty measures: aggregate uncertainty, weighted aggregate uncertainty, and deviation uncertainty. Aggregate uncertainty incorporates a list of unknown risk factors into a single entropy-based measure. Weighted aggregate uncertainty considers the relative importance of unknown uncertainty factors. Deviation uncertainty is a relative uncertainty measure which indicates the degree of deviation of a given project from an ideal project in which all factors are certain. An actual project is used to demonstrate our measures. The paper also discusses managerial implications of such measure.
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Abstract
Because of dynamic, complex and competitive environments, many information technology (IT) projects are plagued by significant cost overruns and unexpected schedule slips. Research suggests that a major reason for project failures is management’s inability to address uncertainty during the development of a new management information system. Dealing with project uncertainty consists of three main segments: identifying sources of project development uncertainty, quantifying project uncertainty, and using such uncertainty measure for improving decision making process with respect to projects. While the first segment has been a major concern for researchers and practitioners, very little progress in the way of theoretical development has been achieved in the areas of uncertainty quantification and its use in project management. This paper explores various aspects of project uncertainties and offers three entropy-based uncertainty measures: aggregate uncertainty, weighted aggregate uncertainty, and deviation uncertainty. Aggregate uncertainty incorporates a list of unknown risk factors into a single entropy-based measure. Weighted aggregate uncertainty considers the relative importance of unknown uncertainty factors. Deviation uncertainty is a relative uncertainty measure which indicates the degree of deviation of a given project from an ideal project in which all factors are certain. An actual project is used to demonstrate our measures. The paper also discusses managerial implications of such measure.