Purpose The field of supply chain management (SCM) evolves dramatically due to factors of globalization, innovation, sustainability, and technology. These changes raise challenges not only to higher education institutions, but also to students, employing organizations, and third parties like SCM-related professional bodies. To understand the challenge, the purpose of this paper is to examine the gap between demand and supply of SCM-related knowledge areas, answer-related design questions, and make recommendations to close the gaps. Design/methodology/approach To compare the demand and supply of SCM-related knowledge areas, demand data is collected from a professional career website and supply data is gathered from operations management (OM) and SCM course syllabi from AACSB-accredited business schools in the USA. Cluster analysis identifies how supply and demand are matched on the data collected. Findings First, gaps exist between SCM talent requirements from industry and the knowledge/skill training by US business schools. This paper identifies matching, under-supplying, and over-supplying knowledge areas. Under-supply in emerging areas such as SCM information technology and certain logistics management topics are found. Some traditional OM topics are over-supplied due to out-of-date industry applications and should be revised to reflect the field’s transition from an OM to SCM view. Last, this paper makes recommendations to different stakeholders in this matching supply with demand process. Originality/value This study contributes to the literature in two ways. First, it provides an up-to-date understanding on demand and supply of SCM talent in USA. Second, it provides insights and recommendations not only to educators on curriculum design, but also to potential candidates interested in SCM careers, to companies’ job recruiters, and to professional organizations (such as APICS and Council of Supply Chain Management Professionals) to reduce the gaps between demand and supply.
Please scroll down for article-it is on subsequent pagesWith 12,500 members from nearly 90 countries, INFORMS is the largest international association of operations research (O.R.) and analytics professionals and students. INFORMS provides unique networking and learning opportunities for individual professionals, and organizations of all types and sizes, to better understand and use O.R. and analytics tools and methods to transform strategic visions and achieve better outcomes. For more information on INFORMS, its publications, membership, or meetings visit I n recent decades, the project-scheduling practice known as critical chain project management (CCPM) has been successful in industrial applications, yet remains a subject of disagreement among scholars and is only sporadically taught in business schools. The purpose of this paper is to assess what aspects of CCPM are appropriate in operations courses, whether dedicated project management classes or broader introductory operations management classes. To answer this, we survey academic literature on traditional project management problems that gave rise to CCPM to understand if these issues are real. We also examine whether the CCPM methodology should, according to scholars, correct these problems, and survey project success stories attributed to CCPM. We conclude that CCPM is an appropriate project management methodology for student consideration on the basis of motivating critical thinking-especially about behavioral issues-rather than on formal scientific proof of its merit. In so doing, we survey teaching resources as well as articles in the trade press on the subject. We then present a sequence of numerical practice problems that are designed to motivate further critical reflection about CCPM. Throughout are a number of open questions about CCPM that the academic community has not yet answered and that instructors should keep in mind.
We propose a paradigm shift in how the performance of outpatient clinic appointment schedules is evaluated in practice and academia. Our research addresses the traditional dilemma between patients' wait times and providers' idle time and overtime, but with operational performance metrics that assess their respective probabilities of exceeding established thresholds, instead of optimizing a presumed cost function. Using a stochastic model, we introduce a new way of analyzing appointment schedules that is absent from the literature but appealing to practitioners. We take into account the variable nature of patient consultation times, known differences in the duration of diverse consults, and patients' propensity to miss their appointments. Analysis shows that traditional scheduling systems have serious shortcomings in terms of providing consistent service levels, and we conclude that the managerial decision space so far investigated in the appointment scheduling literature is not adequate for exercising operational control over appointment system performance.
In this paper, we evaluate the effectiveness of policies for assigning interdependent workers to teams. Using a computational simulation, we contrast distributing workers equitably across teams based on prior individual performance with policies that distribute workers based on how well people work together. First, we test a policy that clusters workers into teams by finding natural breakpoints among them where their mutual support is weak. Then we test two other policies that both protect the strongest interdependent core of high performers but differ in that one policy separates workers who give little support to interdependent partners and the other separates workers who receive little support from their partners. All three policies outperform the equitable-distribution approach in some circumstances. We make recommendations to managers for harnessing interdependence when forming teams, whether the managers are familiar or unfamiliar with how well their people work together.
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