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dc.contributor.authorGowland, Darren
dc.date.accessioned2015-10-09T21:24:25Z
dc.date.available2015-10-09T21:24:25Z
dc.date.issued2015-10-09
dc.identifier.urihttp://hdl.handle.net/2299/16519
dc.description.abstractThe intention of the programme was to evaluate Product Development (PD) strategies within the automotive industry and to identify areas in which improvements could be made in PD project performance that would also provide a business opportunity for the author’s employer RLE INTERNATIONAL (RLE). The research is principally concerned with the automotive industry but also has broader applications within similar industries. The research was undertaken via three projects. Project 1 involved a study of the structure, drivers and trends within the automotive industry. The aim was to assess the implications for PD in the automotive industry and identify significant issues where opportunities for improvement existed. The outcome was a portrayal of an industry under extreme competitive pressure and waiting for something to change but without a clear future state. What was apparent was that the competitive pressures, and thus the need to deliver more products without significantly increased resources, were not going to abate in the near future. PD has to ‘deliver more with less’ but a definition of success and its associated measures in terms of the PD process is difficult to frame. Therefore, the aim of project 2 focused on performance measurement of the PD process by assessing four internationally diverse development projects carried out by the author’s employer with four discrete customers. The projects were all different in their content and were carried out in different countries, i.e. USA, Germany, India and Sweden. Whilst customer specific and cultural aspects of the projects differed, the significant issue identified via the research was common across all the projects. Traditional Key Performance Indicators (KPIs) of cost, time and scope were used but failed to predict issues in project delivery. The key finding was that if project information did not flow as originally planned then resources were wasted resulting in time and cost over-runs. Project 3 researched alternative solutions to the issue of monitoring information flow and proposes a specific method of indicating the likelihood of success in a project by identifying new PD measurement techniques to be used within the automotive PD process. This new measurement criterion of information flow provides a predictive tool that significantly enhances the project control process. The predictive method of information flow tracking developed is new to the automotive PD profession. It was trialled on an existing project and was shown to identify specific issues with the Work-in-Progress (WIP) not found by traditional project management methods. The resulting indication of issues enabled the organisation’s management to have a substantially different insight and understanding of project performance at a given point in time and therefore enabled immediate changes in resource allocation to improve project performance. The implementation of these changes as a result of the adoption of information flow monitoring resulted in significantly improved project KPI performance. The contribution of this new PD management method has the potential to significantly impact the competitiveness of any company involved in the design and development process. Its benefits include improved understanding of project performance indicators, powerful predictive attributes resulting in better utilisation of company resources and reductions in both project costs and lead times.en_US
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectInformation flowen_US
dc.subjectDigital processen_US
dc.subjectVirtual value chainen_US
dc.subjectProduct development process improvementen_US
dc.subjectPerformance measurementen_US
dc.subjectCumulative flow diagramen_US
dc.titlePerformance Measurement in the Product Development Processen_US
dc.typeinfo:eu-repo/semantics/doctoralThesisen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnameEngDen_US
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