Constrained bayesian inference of project performance models

Show simple item record Sunmola, Funlade 2015-09-25T10:30:53Z 2015-09-25T10:30:53Z 2013-09-19
dc.identifier.citation Sunmola F. (2013). Constrained bayesian inference of project performance models. Proceedings of the 11th International Conference on Manufacturing Research (ICMR2013), Cranfield University, UK, 19th – 20th September 2013, pp 575-580 en_UK
dc.identifier.isbn 9781907413230
dc.description.abstract Project performance models play an important role in the management of project success. When used for monitoring projects, they can offer predictive ability such as indications of possible delivery problems. Approaches for monitoring project performance relies on available project information including restrictions imposed on the project, particularly the constraints of cost, quality, scope and time. We study in this paper a Bayesian inference methodology for project performance modelling in environments where information about project constraints is available and can be exploited for improved project performance. We apply the methodology to probabilistic modelling of project S-curves, a graphical representation of a project’s cumulative progress. We show how the methodology could be used to improve confidence bounds on project performance predictions. We present results of a simulated process improvement project in agile setting to demonstrate our approach. en_UK
dc.language.iso en en_UK
dc.publisher Cranfield University Press en_UK
dc.relation.ispartofseries Quality and Performance Measurement en_UK
dc.relation.ispartofseries 4 en_UK
dc.subject Bayesian Inference en_UK
dc.subject Project Performance Model en_UK
dc.subject S-Curve en_UK
dc.subject Project Constraints en_UK
dc.title Constrained bayesian inference of project performance models en_UK
dc.type Conference paper en_UK

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