An Examination Of The Variation In Information Systems Project Cost Estimates: The Case Of Year 2000 Compliance Projects

The year 2000 (Y2K) problem presented a fortuitous opportunity to explore the relationship between estimated costs of software projects and five cost influence dimensions described by the Year 2000 Enterprise Cost Model (Kappelman, et al., 1998) -- organization, problem, solution, resources, and sta...

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Bibliographic Details
Main Author: Fent, Darla
Other Authors: Kappelman, Leon A.
Format: Others
Language:English
Published: University of North Texas 2000
Subjects:
Y2K
Online Access:https://digital.library.unt.edu/ark:/67531/metadc2535/
Description
Summary:The year 2000 (Y2K) problem presented a fortuitous opportunity to explore the relationship between estimated costs of software projects and five cost influence dimensions described by the Year 2000 Enterprise Cost Model (Kappelman, et al., 1998) -- organization, problem, solution, resources, and stage of completion. This research was a field study survey of (Y2K) project managers in industry, government, and education and part of a joint project that began in 1996 between the University of North Texas and the Y2K Working Group of the Society for Information Management (SIM). Evidence was found to support relationships between estimated costs and organization, problem, resources, and project stage but not for the solution dimension. Project stage appears to moderate the relationships for organization, particularly IS practices, and resources. A history of superior IS practices appears to mean lower estimated costs, especially for projects in larger IS organizations. Acquiring resources, especially external skills, appears to increase costs. Moreover, projects apparently have many individual differences, many related to size and to project stage, and their influences on costs appear to be at the sub-dimension or even the individual variable level. A Revised Year 2000 Enterprise Model is presented incorporating this granularity. Two primary conclusions can be drawn from this research: (1) large software projects are very complex and thus cost estimating is also; and (2) the devil of cost estimating is in the details of knowing which of the many possible variables are the important ones for each particular enterprise and project. This points to the importance of organizations keeping software project metrics and the historical calibration of cost-estimating practices. Project managers must understand the relevant details and their interaction and importance in order to successfully develop a cost estimate for a particular project, even when rational cost models are used. This research also indicates that software cost estimating has political as well as rational influences at play.