Introducing a Taxonomy for Classifying Qualitative Spreadsheet Errors

Abstract

Most organizations use large and complex spreadsheets that are embedded in their mission-critical processes and are used for decision-making. Identification of the various types of errors that can be present in these spreadsheets is, therefore, an important first step to creating controls that organizations can use to govern their spreadsheets. While a considerable amount of research on quantitative error taxonomies exists, there is comparatively little research concerning qualitative error taxonomies. In this paper, we propose a taxonomy for categorizing qualitative errors in spreadsheet models that offers an exploratory framework for evaluating the quality of a spreadsheet model before it is released for use by others in the organization. The classification was developed based on types of qualitative errors identified in the literature and errors committed by end-users in developing a spreadsheet model for Panko's (1996) “Wall Problem.” A principal component analysis of the errors reveals four logical groupings thereby creating four categories of qualitative errors. The usability and limitations of the proposed taxonomy and areas for future research are discussed.