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A Project Staffing Model to Enhance the Effectiveness of Knowledge Transfer in the Requirements Planning Phase for Multi-Project Environments

A Project Staffing Model to Enhance the Effectiveness of Knowledge Transfer in the Requirements Planning Phase for Multi-Project Environments

Donald P. Ballou, Salvatore Belardo, Harold L. Pazer
Copyright: © 2010 |Volume: 6 |Issue: 2 |Pages: 21
ISSN: 1548-0666|EISSN: 1548-0658|EISBN13: 9781609603922|DOI: 10.4018/jkm.2010040101
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MLA

Ballou, Donald P., et al. "A Project Staffing Model to Enhance the Effectiveness of Knowledge Transfer in the Requirements Planning Phase for Multi-Project Environments." IJKM vol.6, no.2 2010: pp.1-21. http://doi.org/10.4018/jkm.2010040101

APA

Ballou, D. P., Belardo, S., & Pazer, H. L. (2010). A Project Staffing Model to Enhance the Effectiveness of Knowledge Transfer in the Requirements Planning Phase for Multi-Project Environments. International Journal of Knowledge Management (IJKM), 6(2), 1-21. http://doi.org/10.4018/jkm.2010040101

Chicago

Ballou, Donald P., Salvatore Belardo, and Harold L. Pazer. "A Project Staffing Model to Enhance the Effectiveness of Knowledge Transfer in the Requirements Planning Phase for Multi-Project Environments," International Journal of Knowledge Management (IJKM) 6, no.2: 1-21. http://doi.org/10.4018/jkm.2010040101

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Abstract

When the systems analysis phase produces faulty requirements, it can often be traced to the failure of the requirements determination team and the client to communicate effectively. This failure is frequently a consequence of inadequate knowledge of the client’s domain possessed by the development team. This paper presents concepts and procedures designed to facilitate communication between requirements determination teams and clients across a full set of IS projects with potentially differing priorities. A systematic framework for staffing requirements determination teams is provided. The importance and interdependence of two types of knowledge, explicit and tacit, to the success of the requirements determination phase is extensively explored. A metric for explicit knowledge coupled with a model that captures the impact of various levels of tacit knowledge upon the acquisition rate of explicit knowledge serve as key inputs to our Project Staffing Model. The appropriately weighted area under an explicit knowledge curve captures the totality of explicit knowledge. Summing such values, weighted to reflect project importance, provides a mechanism for evaluating alternative staffing assignments. An illustrative case highlights implementation issues and suggests procedures when uncertainty exists concerning key inputs. A research agenda is recommended for the estimation of factors required by the analysis.

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