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The movement toward the increased use of analytics in organizations has generated much discussion by academics and professionals about the impacts and opportunities that analytics offers. Although operations research (OR) has been a driving force in applying quantitative and analytical models for organizational decision making, it is less clear how we as OR practitioners can take advantage of the surging interest in analytics to promote the OR profession and expand its reach. In this paper, we discuss the drivers of the analytics movement, an example of an analytics project, and the opportunities and implications for OR, i.e., the problem scope, models and methods, implementation issues, organizational role, professional skills, and education.

This article comprehensively assesses Six Sigma healthcare applications and impact.

The results of an empirical study on the current usage of quantitative techniques for R&D project management in "Fortune 500" industrial firms are presented. A nonrandom sample of 40 respondents from 29 firms were selected to represent a mix of industrial sectors and geographic regions. The information was obtained via personal interview of R&D budget heads and some high level staff. Extensive demographic data on the respondent and his company were collected and related to familiarity and usage of project management techniques. Data were also collected on the perceived impact of techniques on project decision making, and any recent/planned changes in the cadre of techniques. Heavy use and high perceived impact of financial methods for project selection, selective use of network models, some dissatisfaction over the methods available for project scheduling and control, and no usage of mathematical programming models for R&D resource allocation were key findings. As a result, R&D managers must have a thorough understanding of the capital budgeting techniques used by their organizations. Also, the initial training for R&D managers in project management should provide a broad-based introduction to the available methods and techniques, while emphasizing organizational "fit" considerations. Finally, it is suggested that R&D managers enlist the support of management scientists in the development of decision support systems for R&D project management, especially for multi-project planning and control.research and development, project management, professional, OR/MS implementation