Analyzing Open-Source eXtensible Business Reporting Language (XBRL) Financial Statement Data: A DuPont Analysis

Abstract

In this case, students will (1) develop an understanding of the data structure and format of financial statement data filed using the eXtensible Business Reporting Language (XBRL) framework; (2) extract, clean, and transform this XBRL data in order to conduct DuPont analysis; and (3) communicate the analysis findings in a professional written report that incorporates relevant visualizations. To complete this activity, students should make use of an appropriate process workflow automation tool, (i.e., Alteryx, Python, R), which facilitates the extract, transform, and load (ETL) process for large datasets in a structured manner. Although DuPont analysis is the focal point for this activity, students and instructors can answer a wide range of accounting and finance questions that leverage the XBRL data. As such, this activity serves as an introduction to XBRL and to process automation tools in general and may facilitate integration of analytics throughout the accounting or business school curricula.