https://doi.org/10.24928/2019/0161

A Predictive Method for Benefits Realisation Through Modelling Uncertainty in Front End Design

Joas Serugga1, Mike Kagioglou2 & Patricia Tzortzopoulos3

1PhD Candidate, Huddersfield, HD1 3DH, UK, +44 7553231992, joas.serugga@hud.ac.uk
2Professor of Process Management, Art, Design and Architecture, School., Dean, Univ. of Huddersfield, Huddersfield, HD1 3DH, UK, +44 1484472289, m.kagioglou@hud.ac.uk
3Professor of Integrated Design, Architecture and 3D Design, Depart, Univ. of Huddersfield, Huddersfield, HD1 3DH, UK, +44 1484472281, p.tzortzopoulos@hud.ac.uk

Abstract

Many projects continue to fail to deliver intended benefits amid uncertainty in benefits realisation (BR) programs. This is more so in Front End Design (FED) where processes remain not only understudied but also informal yet reliant on knowledge sharing. As a result, there is an emergent need for new decision support tools to support benefits delivery processes. The paper addresses uncertainty with FED processes as a way of facilitating decision making as an enabler to benefits delivery of construction projects using uncertainty modelling. The paper adopts a Dempster-Shafer approach using probability theory. This is combined with Quality Function Deployment for user and design requirements capture and management. A conceptual model is suggested that forms a basis for future validation and evaluations in action research in various contexts. The Paper introduces a novel approach to uncertainty modelling in FED to support decision making. The Dempster-Shafer Bayesian based approach also contributes to new ways for capturing contextual influences to benefits realisation.

Keywords

Benefits Realisation, Dempster-Shafer Theory, Uncertainty Modelling

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Reference

Serugga, J. , Kagioglou, M. & Tzortzopoulos, P. 2019, 'A Predictive Method for Benefits Realisation Through Modelling Uncertainty in Front End Design' In:, Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC). Dublin, Ireland, 3-5 Jul 2019. pp 1321-1332

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