Information systems project manager soft competencies: A project-phase investigation

This article investigates the soft competencies by project phase that information systems (IS) project managers require for project success. The authors conducted 33 qualitative interviews to collect data from a sample of 22 IS project managers and business leaders located in Calgary, Alberta, Canada. The authors identified the key competencies for each of the IS project phases (initiation, planning, implementation, and close- out). The competencies were sorted into competency categories: personal attributes (e.g., eye for details), communication (e.g., effective questioning), leadership (e.g., create an effective project environment), negotiations (e.g., consensus building), professionalism (e.g., lifelong learning), social skills (e.g., charisma), and project management competencies (e.g., manage expectations). Each of the most important competencies is discussed and interconnections among competencies identified. How this research can be used by the practitioner and academic communities and the broader implications of this research are examined. © 2009 by the Project Management Institute

Industrial Engineering Education for Industry 4.0

Industry 4.0, additive manufacturing, digitalization, and the emergence of the circular economy are changing the face of manufacturing. New pedagogical approaches, including web-based delivery, are changing the face of teaching and learning. The major findings of a survey carried out by the IE3 Erasmus Plus project on the ‘knowledge demand’ identified by companies and the ‘knowledge supply’ in master level programs in Industrial Engineering and Management offered from European Universities are presented. Soft skills, digital abilities and experiential learning based programs are identified as the most sought after requirements of industry which are not satisfactorily addressed by many existing university master programs. An integrated model of competence, already available in literature, is suggested as a reference framework for designing new manufacturing or industrial engineering master programs

A case for using both direct and indirect benchmarking to compare university performance metrics

Benchmarking is used in higher education as a means to improve and compare performance. Comparative metric benchmarks may take two forms, based on direct standardization (DS) or indirect standardization (IS). DS can be used to measure variation in performance between institutions, controlling for intrinsic differences at each institution (e.g. controlling for differences in student typologies). IS can be used to measure variation in performance between institutions, compared to average performance overall. Typically, IS has been used to moderate educational output metrics, such as student qualification and satisfaction. We contrast the two approaches with an example dataset for three years of nursing student completion rates from nine institutions. Profiles of benchmarks and actual performance indicated that both approaches provide valuable and different perspectives to comparisons of institutional performance. We discuss the potential merits to stakeholders of each approach and conclude that decision-making can be best informed using both benchmark methods