Learning from the Best New Product Developers

Davidson, Jeffrey M.; Clamen, Allen; Karol, Robin A.

doi:10.1080/08956308.1999.11671289

Cited by 48 publications

(19 citation statements)

References 1 publication

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“…We also thank Joseph Mahoney for his insights, and three anonymous referees and an associate editor for their helpful comments. 1, 9, 11 (1) Davidson et al (1999); (2) Rummler and Brache (1995); (9) Senge (1990); (10) Upton (1996); (11) Witcher and Butterworth (2001).…”

Section: Acknowledgementsmentioning

confidence: 99%

“…Conceptual development. In order for an organization to build dynamic capabilities, it must systematically record and track the results of its repeated cycles of knowledge creation (Bendoly and Swink, 2007;Davidson et al, 1999;Tatikonda, 2000, 2008). The effective deployment of a CI initiative that includes standardized processes and improvement-seeking techniques thus demands continual assessment, which in turn requires the gathering and dispersion of information in an efficient and timely fashion.…”

Section: Information Technology Supportmentioning

confidence: 99%

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Dynamic capabilities through continuous improvement infrastructure

Anand

Ward

Tatikonda

et al. 2009

J of Ops Management

415

385

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We examine the content of continuous improvement strategies and identify infrastructure decision areas that are important for continuous improvement initiatives. We present a framework of infrastructure based on the idea that continuous improvement can serve as a dynamic capability when it includes a comprehensive organizational context. Further, we study continuous improvement initiatives in five companies to investigate the practices used by them in each of the decision areas of our framework. This research adds to the conceptual understanding of continuous improvement and results in grounded propositions about critical areas of infrastructure for continuous improvement.

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Section: Acknowledgementsmentioning

confidence: 99%

Section: Information Technology Supportmentioning

confidence: 99%

Dynamic capabilities through continuous improvement infrastructure

Anand

Ward

Tatikonda

et al. 2009

J of Ops Management

415

385

View full text Add to dashboard Cite

show abstract

“…The components that were used for the benchmarking exercises were synthesized from many previous best practices studies (Sherman 1985, Dimancescu and Dwenger 1996, Davidson et al 1999, Dooley et al 2002, Eckermann et al 2002, Cooper et al 2004a, b, c, Cormican and O'Sullivan 2004, including market and product strategy, product champions and leaders, multi-functional teams, open communication, collaboration, resources, pace slack time, employee suggestions, top management support, shared vision, clear goals, alignment with strategy, experimentation and testing, market and technical assessment, market focus, customer contact, performance metrics, risk taking, together with other components that were not captured by these previous studies such as functional competencies, core visionary motivators, and so on. Based on the finding of a number of previous best practices studies (Sherman 1985, Cooper 1990, Crawford 1994, Ackenhusen et al 1996a, b, Dimancescu and Dwenger 1996, Rosenau 1996, Coyne 1997, Griffin 1997, Markides 1998, Davidson et al 1999, Zairi 1999, Figueroa and Conceicao 2000, APQC 2001, Belliveau et al 2002, Conceicao et al 2002, Cooper et al 2002, Dooley et al 2002, Eckermann et al 2002, Reed 2002, Cooper et al 2004a, b, c, Cormican and O'Sullivan 2004, these world best practices in NPD can be categorized along the four key factors NPD model.…”

Section: Best Practice Npd Modelmentioning

confidence: 99%

A world class new product development best practices model

Shum

Lin

2007

International Journal of Production Research

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Past research provides evidence of a wide range of antecedent variables to explain new product development performance. The reported determinants are a combination of strategic, development process, organizational, and market factors. However, these research efforts are fragmented and focus on one or two key factors. Researchers look at this issue from a narrow disciplinary perspective. So the results are quite discipline-biased. Apart from the lack of a multidisciplinary approach, there is a real gap in subjecting these factors to rigorous empirical tests, and incorporate modern proven best practices of world class innovative companies to guide practitioners in their innovation journey. There is a real need to broaden the range of factors considered and develop an integrated model with high predictive power to guide new product development (NPD) efforts. This paper aims to address this research issue. In this research study, four key factors have been identified in modelling financial performance in NPD. They are strategic fit and shared vision, market orientation, stimulus and slack time, organization for collaboration and communication. Regression analysis was performed to validate their importance and estimate the parameters of these four key factors. The result shows that all these four factors are statistically significant in determining financial performance in NPD. This framework can be used practically to assist managers to improve in their NPD efforts so as to achieve higher financial return on investment.

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“…Many recent studies have witnessed that successful companies do employ formal project portfolio management systems to align product development with business objectives [Cooper, 1997a;Cooper, 1997b;Davidson, 1999]. Especially in the latter stages of product development, or product development as a whole, portfolio analyses and reviews have been well aligned and integrated with a project process and company goals.…”

Section: Product Developmentmentioning

confidence: 99%

“…The different stages of R&D take place simultaneously, and they should all contribute to the goals of the firm. Therefore, two critical success factors in R&D are process clarity and the alignment of R&D with business objectives [Davidson, 1999;. Concurrency of the different stages makes R&D management complex.…”

Section: Stages Of Research and Developmentmentioning

confidence: 99%

Project Portfolio Management in Telecommunications R&D

Aalto

Martinsuo

Artto

Handbook of Product and Service Development in Communication and Information Technology

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Research and development in telecommunications is increasingly conducted through target-oriented projects. Project management systems and tools have been implemented to improve efficiency and general manageability of activities. In a dynamic business environment, however, the biggest challenge is in deciding what to do, in addition to how. Project management discipline has recently expanded its scope towards multi-project management, frequently referred to as project portfolio management. Since projects in the same organization compete for the same resources, they together should be steered to fulfill strategic business objectives.Project portfolio management is about managing the entire set or subset of projects towards strategic objectives. During the past decade, project portfolio management literature has introduced tools and frameworks for steering R&D project portfolios effectively towards business goals. These methods are no longer merely about rational and numerical decision making, but more about skilled, multi-disciplinary criteria, evaluation and strategy-driven choices.Due to the contingent nature of human decision-making, it is likely that project portfolio management should be different at the different stages of R&D: research, technology development, and product development. Such research has not been reported earlier.

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Learning from the Best New Product Developers

Cited by 48 publications

References 1 publication

Dynamic capabilities through continuous improvement infrastructure

Dynamic capabilities through continuous improvement infrastructure

A world class new product development best practices model

Project Portfolio Management in Telecommunications R&D

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