Fit, Bias, and Enacted Sensemaking in Data Visualization: Frameworks for Continuous Development in Operations and Supply Chain Management Analytics

Data visualization has a critical role in the advancement of modern data analytics. Visualization lends assurances to data validity and completeness, as well as to the effectiveness of cleaning and aggregation tactics. It provides the means by which to explore and discover relationships otherwise hidden from default assumptions in statistical modeling. Strong visualization is also fundamental to end‐result conveyance and audience interpretation. But how can one ensure that strength? How can one avoid developing representations that are marginal in value, or worse misleading? In this paper, I will discuss theory, evidence, and practical approaches to managing data visualization development, viewing data visualization not simply as an outcome but as a continuous process and facet of organizational culture.