دانلود مقاله ISI انگلیسی شماره 373
عنوان فارسی مقاله

چارچوب مدیریت ریسک عملکرد گرا برای پروژه های نوآورانه R & D

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
373 2010 11 صفحه PDF سفارش دهید 8660 کلمه
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عنوان انگلیسی
A performance-oriented risk management framework for innovative R&D projects
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Technovation, Volume 30, Issues 11–12, November–December 2010, Pages 601–611

کلمات کلیدی
& مدیریت & - مدیریت ریسک - مدیریت پروژه - کارت امتیازی متوازن - استقرار عملکرد کیفیت - کارت امتیازی متوازن - مقالات سیستم ارزیابی عملکرد
پیش نمایش مقاله
پیش نمایش مقاله چارچوب مدیریت ریسک عملکرد گرا برای پروژه های نوآورانه R & D

چکیده انگلیسی

Uncertainty is one of the major inherent difficulties in developing innovative products, due to their highly dynamic markets and technologies. The presence of a large degree of uncertainty leads to high R&D risks, resulting in many R&D failures. Therefore, it is important to manage R&D risks through all R&D stages to improve R&D project success rates. This paper proposes a new risk management framework that aligns project risk management with corporate strategy and a performance measurement system to increase success rates of R&D projects and to accomplish corporate strategic goals. The balanced scorecard is used to identify major performance measures of an R&D organization based on the firm vision and strategy. Quality function deployment is adapted to transform organizational performance measures into project performance measures and a systematic procedure is developed for risk identification, assessment, response planning, and control. The proposed risk management framework enables an R&D project to be focused on achieving the corporate goals and provides a more effective way to identify, assess, analyze, and monitor R&D risks along the project cycle. The proposed methodology is illustrated with a drug development project.

مقدمه انگلیسی

In the increasingly competitive and globalized marketplace, technological innovation is one of the important key strategies for high technology firms to survive and achieve corporate growth (Teece, 1986 and Freeman and Soete, 1997). However, various types of innovation (Dewar and Dutton, 1986 and Henderson and Clark, 1990) involve different degrees of uncertainty in technologies and markets that may cause failures of R&D projects (Doctor et al., 2001, Raz et al., 2002 and Lee et al., 2010). For example, in the pharmaceutical industry, the success rate of a drug development project from the first study in humans to launch is less than 10% (CMR, 2006). Therefore, it is important to manage risks for innovative R&D projects through all the development stages to improve their success rates (Smith and Merritt, 2002, Keizer et al., 2002, Bush et al., 2005 and Pisano, 2006). Risk management is a structured approach for the identification, assessment, and prioritization of risks followed by planning of resources to minimize, monitor, and control the probability and impact of undesirable events (Smith and Merritt, 2002). It has been widely applied in many disciplines, such as management, engineering, insurance, finance, environment, politics, etc. In R&D management, the major purpose of risk management is to increase success rate of an R&D project, which will lead to corporate success. Most literature in the R&D risk management literature is more focused on an individual project level, and so the ways to identify, assess, and prioritize risks are limited within a single project scope (Smith, 1999, Browning et al., 2002, Keizer et al., 2002, Raz et al., 2002, Saari, 2004 and Keizer et al., 2005). The main problem is that if the identified risks are improperly identified and prioritized, then time and cost can be wasted in dealing with risk of losses. Therefore, there is a need to link individual project risk management with the corporate strategic management to ensure that managed risks are coped with by the corporate strategy and corporate objectives can be eventually achieved. This research considers risk to be an event having a negative impact on project outcomes (Browning et al., 2002, Raz et al., 2002, Smith and Merritt, 2002, Keizer et al., 2002, Keizer et al., 2005 and Perminova et al., 2008) and develops a new risk management framework that aligns project risk management with corporate strategy and a performance measurement system to increase success rates of R&D projects and to accomplish the corporate strategic objectives. The proposed framework, which follows the risk management process that have been widely used in industry, integrates the balanced scorecard (BSC) (Kaplan and Norton, 1992) and quality function deployment (QFD) (Hauser and Clausing, 1988) to help project managers organize risk management activities in a top–down manner. The BSC is used to identify major performance measures of an R&D organization based on the firm vision and strategy. Furthermore, QFD is adapted to transform organizational performance measures into project performance measures and a step-by step procedure is developed for risk identification, assessment, response planning, and control. The proposed risk management framework enables an R&D project to be focused on achieving the corporate goals and provides a more effective way to identify, assess, analyze, and monitor R&D risks along the project cycle. To our best knowledge, there has been no research study that provides an integrated risk management framework based on the BSC and QFD to link R&D risk management with corporate strategy and a performance measurement system. This paper is organized as follows. Section 2 reviews the related literature. The proposed risk management framework is developed in Section 3. In Section 4, the proposed methodology is illustrated with a hypothetic drug development project. Section 5 concludes the paper.

نتیجه گیری انگلیسی

The example reported in Section 4 demonstrates that the proposed risk management framework provides a systematic approach to align the project risk management with corporate strategy and a performance measurement system to actively identify and manage critical R&D risks throughout the entire project. Although, due to limited space, the example only demonstrates the preclinical testing phase from the internal process perspective, the proposed approach can be extended to other development stages and perspectives as well. It is worth noting that the implementation of the proposed risk management approach needs to consider the following aspects. Firstly, the proposed risk management framework should be based on the multi-disciplinary team approach. The team should consist of individuals from different perspectives to address risks from all possible facets of the project. As we have mentioned in Section 3, though the team diversity can bring some advantages, if the team is not properly managed, then the advantages may become disadvantages. These can lead to negative group dynamics and increase information uncertainty and ambiguity in R&D. A number of group decision making techniques (Souder, 1977 and Hwang and Lin, 1987), such as multi-voting, nominal group, nominal-interacting group, and consensus decision making techniques, can be used in the proposed risk management process to avoid negative group dynamics and improve efficiency and effectiveness of team decision making (Keizer et al., 2002 and Forsyth, 2006). This would help the team gather and share required information, create and identify alternative courses of action, choose among these alternative by integrating the diverse perspectives of members, and enhance group commitment to implement the decisions. Secondly, the entire risk management is an iterative, rather than a one-shot, stepwise process. The proposed risk management approach should start concurrently with the creation of the project schedule, budget, and specifications, proceeding through each step, continuously monitoring and controlling the risks and then going back to the first step to identify new risks as regularly as required. Thirdly, the risk management team should meet periodically to review current project outcomes and results from ongoing risk assessments, and to discuss upcoming changes in product markets and technologies. Since an innovative R&D project may contain great uncertainty in its market and technology, it is important to regularly reassess the project for unforeseen risks and deviation from the original plan. Furthermore, creative thinking techniques (Michalko, 2006), such as brainstorming, can be used to generate a broad range of possible options (e.g., performance measures, risk sources, and action plans), rather than predefined solutions (Sutton and Hargadon, 1996). These will enhance the possibility to develop more resource-effective options for better R&D risk management. Finally, a knowledge management system can be built to capture, store, and disseminate company-specific knowledge for R&D risk management (Cooper, 2003 and Keizer et al., 2005). It would help the team to identify issues that occur in the past and have more time to think of less obvious issues. In addition, the QFD planning chart could be adapted to document the entire risk management process for knowledge storage and retrieval. In summary, the proposed performance-oriented risk management framework has the following benefits. Firstly, linking R&D risk management with the firm’s strategy could prevent local measurements from driving inappropriate behaviors. In addition, due to great uncertainties in technology and market for an innovative R&D project, there are unforeseen risks that may be difficult to be identified at early R&D stages. The performance-oriented risk measure is able to help the team update and monitor critical risks efficiently through the R&D process. Finally, the proposed framework that can be integrated with the corporate performance measurement system provides a more objective way to identify and manage risks from the performance perspective and to improve success rates of R&D projects. Since the major cause of the risk is uncertainty which may lead to positive or negative outcomes (Perminova et al., 2008), future research will extend the current R&D risk management framework to manage both opportunities and threats, and study how to gain values from uncertainty based on the real options analysis (Dixit and Pindyck, 1994 and Jacob and Kwak, 2003). In addition, further study is required to investigate the effects of group decision making in the proposed risk management framework.

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