Dynamic modeling of product development processes

Ford, David N.; Sterman, John D.

doi:10.1002/(sici)1099-1727(199821)14:1<31::aid-sdr141>3.0.co;2-5

Cited by 244 publications

(165 citation statements)

References 26 publications

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“…In our data set, the value of dependency k is 0.8%. The estimates of the development duration and rework rate were much simpler because both of them can be directly derived from previous projects (Ford and Sterman, 1998;Repenning, 2001). The costs of functional interaction and rework are largely dominated by the engineering hours spent on the activities.…”

Section: Data Collectionmentioning

confidence: 99%

Optimal overlapping and functional interaction in product development

Lin

Chai

Brombacher

et al. 2009

European Journal of Operational Research

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Section: Data Collectionmentioning

confidence: 99%

Optimal overlapping and functional interaction in product development

Lin

Chai

Brombacher

et al. 2009

European Journal of Operational Research

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“…A number of formal models of cooperative processes have been proposed to predict the number of iterations required for completion, or to suggest optimal concurrency and iteration schemes which minimize the overall time or cost (e.g., Ahmadi and Wang (1994); Ha and Porteus (1995); Krishnan et al (1997); Jin and Levitt (1996); Ford and Sterman (1998); Roemer et al (2000); Loch et al (2001); Peña-Mora and Li (2002)). One example of these approaches is the work transformation matrix (WTM) model (Smith and Eppinger, 1997), which is an extension of the design structure matrix model (see Browning (2001) for a review).…”

Section: Introductionmentioning

confidence: 99%

Performance Variability and Project Dynamics

Huberman

Wilkinson

2005

Comput Math Organiz Theor

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We present a dynamical model of complex cooperative projects such as large engineering design or software development efforts, comprised of concurrent and interrelated tasks. The model contains a stochastic component to account for temporal fluctuations both in task performance and in the interactions between related tasks. We show that as the system size increases, so does the average completion time. Also, for fixed system size, the dynamics of individual project realizations can exhibit large deviations from the average when fluctuations increase past a threshold, causing long delays in completion times. These effects are in agreement with empirical observation. We also show that the negative effects of both large groups and long delays caused by fluctuations may be mitigated by arranging projects in a hierarchical or modular structure. Our model is applicable to any arrangement of interdependent tasks, providing an analytical prediction for the average completion time as well as a numerical threshold for the fluctuation strength beyond which long delays are likely. In conjunction with previous modeling techniques, it thus provides managers with a predictive tool to be used in the design of a project's architecture.

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“…A policy that increases starts can become advantageous in case the complexity of projects is reduced to some extent (whenever possible), since this will enable an extra amount of projects to go through the pipeline quickly, without accumulations. There is a need to follow a complete and balanced sequence of activities in the development process (Ford & Sterman, 1997). Therefore, we posit that the optimal number of starts is increased when the complexity of projects at all stages is reduced.…”

Section: Hypothesismentioning

confidence: 99%

The Effect of Longer Development Times on Product Pipeline Management Performance

2015

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ResumoNa indústria farmacêutica, valor é destruído devido a maiores tempos de desenvolvimento dos produtos. Como as patentes, em geral, são fixadas em 20 anos de duração, o efeito de aumentar o tempo levado para a comercialização é evidente: maiores custos de P&D e menor tempo de comercialização até a entrada dos medicamentos genéricos. As implicações para o gerenciamento são grandes: uma tendência a estabelecer parcerias, licenciamento ou aquisição de outras empresas de biotecnologia. Neste trabalho, construiu-se um modelo de dinâmica de sistemas do funil de desenvolvimento de produtos farmacêuticos, calibrado para uma única companhia. O estudo demonstra que na presença de perda de valor devido a lead times mais longos é mais vantajoso: (a) trabalhar mais rápido para reduzir o acúmulo de projetos na cadeia, (b) aumentar o número de projetos iniciados, sempre que for possível reduzir a complexidade dos projetos e (c) a decisão ótima de alocação de recursos aos estágios independe da perda de valor devida a longos lead times.Palavras-chave: dinâmica de sistemas; indústria farmacêutica; funil de desenvolvimento de produtos; gerenciamento de portfólio de projetos; patentes. AbstractIn the pharmaceutical industry, value is being destroyed through longer product development times. Given that patent lives are (normally) fixed at 20 years, the double hit of increasing time to market is evident -higher R&D costs and less time at market before generic competitors are able to be released into the marketplace. The Policy implications are massive: A huge and permanent shift away from internal R&D towards partnerships, licensing deals and acquisitions of more innovative biotechnology companies. In this study, we build a system dynamics model of the product development pipeline for a single company operating in the pharmaceutical market. The study shows that in the presence of loss of value due to longer lead times, it is more advantageous to: (a) work faster to reduce the backlog of projects; (b) increase the number of projects started whenever it is possible reduce complexity in the pipeline; and also (c) the optimal decision on resource allocation is independent of the loss of value due to longer lead times.

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Dynamic modeling of product development processes

Abstract: The authors thank the Organizational Learning Center and the System Dynamics Group at the Sloan School of Management, and the "Python" organization for financial support. Special thanks to the members of the Python project for their interest, commitment and time. :7/97

Cited by 244 publications

References 26 publications

Optimal overlapping and functional interaction in product development

Optimal overlapping and functional interaction in product development

Performance Variability and Project Dynamics

The Effect of Longer Development Times on Product Pipeline Management Performance

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