Prevalence and success of portfolio management systems in south african new product development companies

AFRICON 2007 ◽  
2007 ◽  
Author(s):  
Alan D. Van Gerve ◽  
Jasper L. Steyn
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanderson César Macêdo Barbalho ◽  
Gladston Luiz Silva

PurposeThis paper aims to explore how new product development (NPD)-based project management offices (PMOs) work, their drivers to deliver performance and their project success impact.Design/methodology/approachThe study used a survey of 35 Brazilian and multi-national companies that identified the effort to perform a list of PMO functions, some PMO drivers in the company and five project performance perception indicators. The authors apply a specific set of statistics to uncover the relations between these dimensions of interest.FindingsThe factorial analysis allows us to find the main functions influencing each other. The project teams’ perception of project management (PM) performance is suggested as a success factor that drives PMOs when working on portfolio management issues, managing project files and promoting PM over the company.Practical implicationsThis paper contributes to a contingency approach for designing a project machine involving PMOs to support NPD projects. Managers can set the most suitable PMO functions avoiding mimicry when structuring their NPD efforts.Originality/valuePMOs have impacted team satisfaction and control of project data but not indicators related to triple constraints.


2015 ◽  
Vol 7 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Mishelle Doorasamy

Abstract The aim of this article is to provide reader with a comprehensive insight on the theories, empirical findings and models of Product Portfolio Management (PPM) during new product development. This article will allow for an in-depth theoretical approach on PPM and demonstrate to managers the importance of adopting PPM as business strategy during decision making. The objective of this paper is to present a literature review of models, theories, approaches and findings on the relationship between Product Portfolio Management and new product development. Relevant statistical trends, historical developments, published opinion of major writers in this field will be presented to provide concrete evidence of the problem being discussed.


Author(s):  
Nassim Belbaly ◽  
Hind Benbya

The objective of this chapter is to provide an analytical tool to assist organizations in their implementations of Intelligent Knowledge Management Systems (IKMS) along the new product development (NPD) process. Indeed, organizations rely on a variety of systems using Artificial Intelligence to support the NPD process that depends on the maturity stage of both the process and type of knowledge managed. Our framework outlines the technological and organizational path that organizations have to follow to integrate and manage knowledge effectively along their new product development process. In doing so, we also address the main limitations of the systems used to date and suggest the evolution towards a new category of KMS based on artificial intelligence that we refer to as Intelligent Knowledge Management Systems. We illustrate our framework with an analysis of several case studies.


Author(s):  
Nassim Belbaly ◽  
Hind Benbya

The objective of this chapter is to provide an analytical tool to assist organizations in their implementations of Intelligent Knowledge Management Systems (IKMS) along the new product development (NPD) process. Indeed, organizations rely on a variety of systems using Artificial Intelligence to support the NPD process that depends on the maturity stage of both the process and type of knowledge managed. Our framework outlines the technological and organizational path that organizations have to follow to integrate and manage knowledge effectively along their new product development process. In doing so, we also address the main limitations of the systems used to date and suggest the evolution towards a new category of KMS based on artificial intelligence that we refer to as Intelligent Knowledge Management Systems. We illustrate our framework with an analysis of several case studies.


2001 ◽  
Vol 31 (4) ◽  
pp. 361-380 ◽  
Author(s):  
Robert Cooper ◽  
Scott Edgett ◽  
Elko Kleinschmidt

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