Research and Development(R&D) was once considered to be a unique, creative and unstructured process that was difficult, if not impossible, to manage and control. The standard management and control techniques used in other parts of the organization were therefore considered inappropriate for R&D. Ho...
Research and Development(R&D) was once considered to be a unique, creative and unstructured process that was difficult, if not impossible, to manage and control. The standard management and control techniques used in other parts of the organization were therefore considered inappropriate for R&D. However recent changes in the business environment - intensified competition, splintered mass markets, shortened product life cycles, and advanced technology and automation, etc. - have focused R&D's contribution to competitive advantage. Today, R&D is no longer considered to have a mere supportive role to the primary business processes, but to be a vital part of it. These changes challenge companies to improve their R&D processes in terms of efficiency, internal and external customer focus, time to market and innovation. R&D decisions impact the entire enterprise. Therefore, decisions must not be based solely on R&D's perception of what is important or worthwhile. R&D contributions are difficult to measure separately from other functional organizations such as manufacturing and marketing. While some firms are attempting to overcome perceived limitations in traditional accounting-based performance measures using ROI, EVA^(□), others are embracing the use of non-financial measures for decision making and performance evaluation. In particular, many firms are implementing "Balanced Scorecard(BSC)" systems that supplement traditional accounting measures with non-financial measures focused on at least three other perspectives-customers, internal business processes, and learning and growth. Kaplan and Norton(1992) contend that BSC provides a powerful means for translating a firm's vision and strategy into a tool that effectively communicates strategic intent and motivates performance against established strategic goals. It is assumed that not all strategies are equally important to an enterprise. Likewise, not all strategic metrics are equally adept at measuring the impact against a particular strategy. To account for this weights are calculated for each strategic metric. While many technologies can be used to develop these importance weights, experience has shown the Analytic Hierarchy Processes (AHF') developed by Satty(1988) is a valuable tool for this task. AHP is a popular multi-attribute decision making model that allows for the development of importance rankings. The AHP has been applied in a wide variety of practical settings to model complex decision problems. One of its major strengths is its ability to compare arid rank decision alternatives based on both qualitative and quantitative factors. Questionnaire was made up of AHP Statistical Package, Expert Choice, was used for questionnaire analysis from Several R&D Organization for Profit Organization. The former, determine Perspectives and the Key Performance indicator(KP1) through the former research, the latter compose the questionnaire for determine the weight of perspectives and KPIs. And then, make a survey with researchers about 4 perspectives and 18 KPIs. The results will be simulate with Expert Choice 2000 for determine the weights. This results helps establish the firm's business strategy and technology strategy. The firm should establish the business strategy to consider market position, business growth potential, and technological capabilities.
Research and Development(R&D) was once considered to be a unique, creative and unstructured process that was difficult, if not impossible, to manage and control. The standard management and control techniques used in other parts of the organization were therefore considered inappropriate for R&D. However recent changes in the business environment - intensified competition, splintered mass markets, shortened product life cycles, and advanced technology and automation, etc. - have focused R&D's contribution to competitive advantage. Today, R&D is no longer considered to have a mere supportive role to the primary business processes, but to be a vital part of it. These changes challenge companies to improve their R&D processes in terms of efficiency, internal and external customer focus, time to market and innovation. R&D decisions impact the entire enterprise. Therefore, decisions must not be based solely on R&D's perception of what is important or worthwhile. R&D contributions are difficult to measure separately from other functional organizations such as manufacturing and marketing. While some firms are attempting to overcome perceived limitations in traditional accounting-based performance measures using ROI, EVA^(□), others are embracing the use of non-financial measures for decision making and performance evaluation. In particular, many firms are implementing "Balanced Scorecard(BSC)" systems that supplement traditional accounting measures with non-financial measures focused on at least three other perspectives-customers, internal business processes, and learning and growth. Kaplan and Norton(1992) contend that BSC provides a powerful means for translating a firm's vision and strategy into a tool that effectively communicates strategic intent and motivates performance against established strategic goals. It is assumed that not all strategies are equally important to an enterprise. Likewise, not all strategic metrics are equally adept at measuring the impact against a particular strategy. To account for this weights are calculated for each strategic metric. While many technologies can be used to develop these importance weights, experience has shown the Analytic Hierarchy Processes (AHF') developed by Satty(1988) is a valuable tool for this task. AHP is a popular multi-attribute decision making model that allows for the development of importance rankings. The AHP has been applied in a wide variety of practical settings to model complex decision problems. One of its major strengths is its ability to compare arid rank decision alternatives based on both qualitative and quantitative factors. Questionnaire was made up of AHP Statistical Package, Expert Choice, was used for questionnaire analysis from Several R&D Organization for Profit Organization. The former, determine Perspectives and the Key Performance indicator(KP1) through the former research, the latter compose the questionnaire for determine the weight of perspectives and KPIs. And then, make a survey with researchers about 4 perspectives and 18 KPIs. The results will be simulate with Expert Choice 2000 for determine the weights. This results helps establish the firm's business strategy and technology strategy. The firm should establish the business strategy to consider market position, business growth potential, and technological capabilities.
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