Complementing Decision Support and Forecasting Risk in Supply Chain with Unstructured Data

Abstract

Within this paper, we aim to highlight the potential of unstructured data sources such as blogs to complement and improve data triangulation and to support supply chain decision making. To this end, we combine the fields of supply chain management and control theory to provide a proof of concept for the utilization of unstructured data. An in-depth application example for the monitoring of trends on product features in fashion supply chains is developed using blog based textual data. The application example demonstrates predictive validity and forecasting risks of expert opinions found in textual data.