Application of the fast model from value engineering to capture and communicate project lessons learnt

Purpose - This research investigated the advantages of using a diagramming tool such as the Functional Analysis System Technique (FAST) model to enhance the effectiveness of capturing and communicating lessons learnt onto future projects. The research looked at current ways of capturing tacit knowle...

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Main Author: Mguti, Maclean M M
Other Authors: Jay, Ian
Format: Dissertation
Language:English
Published: University of Cape Town 2018
Subjects:
Online Access:http://hdl.handle.net/11427/27968
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-279682020-12-10T05:11:07Z Application of the fast model from value engineering to capture and communicate project lessons learnt Mguti, Maclean M M Jay, Ian Project Management Purpose - This research investigated the advantages of using a diagramming tool such as the Functional Analysis System Technique (FAST) model to enhance the effectiveness of capturing and communicating lessons learnt onto future projects. The research looked at current ways of capturing tacit knowledge within a projectized organisation to get a clearer picture and propose alternatives on how the knowledge can be communicated and transferred to novice team members in future. The idea is to capitalise on the graphical nature of the FAST model, presupposing the human mind can comprehend graphical tools better than going through long tedious reports. Design - Focus Group Sessions were conducted using two groups from different business units within a project management and consultancy firm in South Africa. The participants represented the various project stakeholders that comprise a project team. The focus group session consists of a presentation on the background of the study and the FAST process. This served as a brainstorming session and a typical project scenario in capturing and communicating lessons learned was presented to the participants. The first diagram showed the activity log list as found on a project site for a particular lesson learnt process. The second diagram showed the same lesson learnt process presented in a FAST diagram. Afterwards, the participants evaluated the effectiveness of the FAST model to capture and communicate lessons learnt in a project environment. The responses were compiled and findings presented in table format. Findings - The analysis of the data and the responses of the participants proved that the FAST diagram can enhance the effectiveness and efficiency of capturing and communicating lessons learnt. This knowledge transfer initiative provides cost benefits as it improves the project execution and competitive advantage of the organisation. Project execution efficiency is improved by codifying tacit knowledge and avoiding repeating the same mistakes on projects. Practical Implications - Developing a culture of capturing lessons learnt on a project as the execution phase unfolds can be a challenging exercise. Most companies pay less or no attention at all to capturing lessons learnt. However lessons learnt documentation must be supported by a quality control system that is robust and allows easy navigation within a repository. The FAST model empowers project custodians through its dynamic structure to document activities on the project. This ensures the FAST diagram is continuously updated to tie in with the changes on the ground as the project unfolds. Limitations: The results were generated in a controlled environment and require confirmation through longitudinal research of the use of FAST for this purpose in practise on live projects. Keywords: lesson learnt, knowledge transfer, data repository, Function Analysis Systems Technique, tacit knowledge, Value Engineering, knowledge management, activity log-list 2018-05-07T14:15:38Z 2018-05-07T14:15:38Z 2018 Master Thesis Masters MSc http://hdl.handle.net/11427/27968 eng application/pdf University of Cape Town Faculty of Engineering and the Built Environment Department of Construction Economics and Management
collection NDLTD
language English
format Dissertation
sources NDLTD
topic Project Management
spellingShingle Project Management
Mguti, Maclean M M
Application of the fast model from value engineering to capture and communicate project lessons learnt
description Purpose - This research investigated the advantages of using a diagramming tool such as the Functional Analysis System Technique (FAST) model to enhance the effectiveness of capturing and communicating lessons learnt onto future projects. The research looked at current ways of capturing tacit knowledge within a projectized organisation to get a clearer picture and propose alternatives on how the knowledge can be communicated and transferred to novice team members in future. The idea is to capitalise on the graphical nature of the FAST model, presupposing the human mind can comprehend graphical tools better than going through long tedious reports. Design - Focus Group Sessions were conducted using two groups from different business units within a project management and consultancy firm in South Africa. The participants represented the various project stakeholders that comprise a project team. The focus group session consists of a presentation on the background of the study and the FAST process. This served as a brainstorming session and a typical project scenario in capturing and communicating lessons learned was presented to the participants. The first diagram showed the activity log list as found on a project site for a particular lesson learnt process. The second diagram showed the same lesson learnt process presented in a FAST diagram. Afterwards, the participants evaluated the effectiveness of the FAST model to capture and communicate lessons learnt in a project environment. The responses were compiled and findings presented in table format. Findings - The analysis of the data and the responses of the participants proved that the FAST diagram can enhance the effectiveness and efficiency of capturing and communicating lessons learnt. This knowledge transfer initiative provides cost benefits as it improves the project execution and competitive advantage of the organisation. Project execution efficiency is improved by codifying tacit knowledge and avoiding repeating the same mistakes on projects. Practical Implications - Developing a culture of capturing lessons learnt on a project as the execution phase unfolds can be a challenging exercise. Most companies pay less or no attention at all to capturing lessons learnt. However lessons learnt documentation must be supported by a quality control system that is robust and allows easy navigation within a repository. The FAST model empowers project custodians through its dynamic structure to document activities on the project. This ensures the FAST diagram is continuously updated to tie in with the changes on the ground as the project unfolds. Limitations: The results were generated in a controlled environment and require confirmation through longitudinal research of the use of FAST for this purpose in practise on live projects. Keywords: lesson learnt, knowledge transfer, data repository, Function Analysis Systems Technique, tacit knowledge, Value Engineering, knowledge management, activity log-list
author2 Jay, Ian
author_facet Jay, Ian
Mguti, Maclean M M
author Mguti, Maclean M M
author_sort Mguti, Maclean M M
title Application of the fast model from value engineering to capture and communicate project lessons learnt
title_short Application of the fast model from value engineering to capture and communicate project lessons learnt
title_full Application of the fast model from value engineering to capture and communicate project lessons learnt
title_fullStr Application of the fast model from value engineering to capture and communicate project lessons learnt
title_full_unstemmed Application of the fast model from value engineering to capture and communicate project lessons learnt
title_sort application of the fast model from value engineering to capture and communicate project lessons learnt
publisher University of Cape Town
publishDate 2018
url http://hdl.handle.net/11427/27968
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