From Data to Stochastic Modeling and Decision Making: What Can We Do Better?

In the past decades we have witnessed a paradigm-shift from scarcity of data to abundance of data. Big data and data analytics have fundamentally reshaped many areas including operations research. In this paper, we discuss how to integrate data with the model-based analysis in a controlled way. Specifically, we consider techniques to quantify input uncertainty and the decision making under input uncertainty. Numerical experiments demonstrate that different ways in decision making may lead to significantly different outcomes in a maintenance problem.