The Selection and Training Framework for Managers in Business Innovation and Transformation Projects

Authors: Antoine Trad, Damir KalpićKalpić

Abstract: The riskiest factor in transforming a traditional business environment (BE) into a lean and automated BE is the role of the profile and the corresponding TOGAF managerial recommendations of the business and (e-)business transformation managers (BTM); the influence they have on the concrete implementation phase of business transformation projects (BTP). The basic profile and “The OpenGroup Architecture Framework” (TOGAF)[66] managerial recommendations of such a business transformation manager has not been sufficiently researched in a holistic manner in order to hammer the BTM’s profile and the corresponding TOGAF managerial recommendations; and that is the main goal of the authors’ research [52][37][38]. In fact, currently there are no TOGAF managerial recommendations and educational curricula for such BTM profiles. This research paper deals with the TOGAF managerial recommendations for the BTM selection and education; who has to manage the technical implementation phase of complex business transformation projects; knowing that the BTPs’ implementation phase is the major cause of very high failure rates [20][21]. The implementations of such business transformation projects require a specific set of enterprise business architecture knowledge. The authors have based their research on the main fact that only around 12% of business organizations successfully terminate innovationrelated business transformations projects [8]. “We know that those organizations that are consistently successful at managing innovation-related changes outperform their peers in terms of growth and financial performance” [7]. Therefore, there is an essential need for more research on the BTMs’ profiles and the TOGAF related managerial recommendations. This research project presents an original set of factors and fulfills the need for an efficient tree reasoning model, in the form of a real world framework and recommendations, which affect the BTM’s selection techniques. BTM selectors, professional analysts, project managers, auditors and advanced computer science students, will benefit from this research project.

Pages: 37-44

DOI: 10.46300/91010.2022.16.6

International Journal of Energy, E-ISSN: 1998-4316, Volume 16, 2022, Art. #6