In Search of 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 purposes. Identification of the various types of errors that can be present in these spreadsheets is, therefore, an important control that organizations can use to govern their spreadsheets. In this paper, we propose a taxonomy for categorizing qualitative errors in spreadsheet models that offers a framework for evaluating the readiness 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". Closer inspection of the errors reveals four logical groupings of the errors creating four categories of qualitative errors. The usability and limitations of the proposed taxonomy and areas for future extension are discussed.