Evaluation and Simulation Methods for Ambidexterity Engineering of Digital Supply Chain Systems

Abstract

Global mergers and faster business cycles create weakly harmonized supply chain (SC) systems. Industry 4.0's smart digitalization opportunities significantly alter business model innovation rates. Consequently, the complexity of aligning value exploration and exploitation has increased, often missing the needed integration level. A holistic systems engineering (SE)-driven methodology for innovation, transformation, and optimizing smart SC systems is not available so far. Case studies at SAP SE's development organization for Industry 4.0 SCM solutions and three automotive companies explored objectives, obstacles, and methods for digital transformation. The results were synthesized into a holistic SC business model transformation and optimization methodology. Complementary to traditional SCM, the study proposes SE-driven meta-modelling to improve the performance, resilience, and synchronization of end-to-end supply chains. Moreover, holistic simulations and evaluation methods for the ambidexterity of SC business models have been developed, enhancing the effectiveness of value exploration and exploitation, and innovation productivity by holistically viewing emergence and convergence throughout SC capabilities' life cycles. Ambidexterity management and dynamic capabilities are addressed by SE methods like capability engineering and complex dynamic systems theory, integrated into a concise SE model.