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Project

Analytics architecture, prescriptive analytics and organizational learning for intelligent organizations

The objective in this project is to develop a digital twin organization to monitor and simulate performance across organizational processes, facilitating optimization of decision-making at the operational as well as tactical and strategic level, and embodying intelligence at the organizational level. This requires the development of an analytics architecture framework, which integrates data analytics applications across organizational processes, and an organizational learning framework, which provides the ability to actively and continuously collect and learn from data. Both components will be integrated in a digital twin organization framework, allowing simulation of process performance in function of decision variables and facilitating the incorporation of alternative, e.g., operations research based, decision-making methods.
Date:19 Oct 2020 →  30 Sep 2022
Keywords:Business decision-making, Causal machine learning, Analytics architecture
Disciplines:Machine learning and decision making, Data mining