This workshop is aimed towards introducing the emergent field of predictive analytics in operations management research. Emergence of large secondary datasets in several areas of operations management such as new product development, product failures, retail operations, healthcare management, manufacturing operations and service operations have not only enabled researchers to address new questions in operational management but also, enabled researchers to have a new look at traditional questions. Real operations management is promised to undergo unpreceded metamorphosis due to incorporation of predictive analytics, decision support systems and artificial intelligence in several fields. However, to enable the potential of predictive analytics in operations management practice and research, it is essential to be able to use new types of data such as text data from social media, image and videos based data, sparse genetic data, etc., and new analytical methods such as machine learning and non-parametric statistics based methods.
This workshop is aimed at providing an overview of predictive analytics and the state of research using predictive analytics on complex and large datasets. There are two broad components to the workshop. First, the workshop will discuss general topics related to predictive analytics such as the difference between explanatory causal modeling and predictive analytic modeling of data, characteristics of big data, and general methods that can be used for predictive analytics. Second, the workshop will introduce a few illustrative examples of research using predictive analytics. Specifically, we intend to discuss three examples from healthcare analytics, product management, and social medial analytics. This workshop will hopefully motivate researchers to look into predictive analytic methods as a potential tool for research in operations management. Additionally, this will introduce predictive analytics in operations management to aspiring researchers who intend to delve into predictive analytics using large and complex datasets.
University of Illinois