A Measurement Theory Perspective on Business Measurement
Abstract
During the last five centuries, the traditional accounting model has evolved into a wide set of business practices and measurement conventions. In general, these models have served business well, but are now gradually losing relevance. The Public Company Accounting Oversight Board (PCAOB) (2011) consideration of a more informative audit report and the Financial Accounting Standards Board (FASB) (2011) reconsideration of a more precise concept of income clearly illustrate a growing disconnect with the traditional model. This paper explores the possibility of enhancing financial reporting with a wider frame of business representations and measures. It begins by discussing business measurement from the perspective of measurement theory, and then considers the potential that contemporary information technology and data processing offers by providing more relevant, timely, and reliable financial information. For example, some of the possible changes could be implemented through modified XBRL tagging. In this paper, we discuss the limitations of the current reporting system and propose a generic business measurement model that includes three layers: the disclosure value chain, the point measurement of each datum, and the level of desired contingency measurement. The disclosure value chain includes environmental conditions, business plans, lead actions that augment current business activities measurement and, where feasible, information on consequent events. In examining the point measurement of each datum, we argue that measures often are not deterministic, but are contingent on time factors, the nature of the decision being supported, the level of desired precision, related future events, and inherent uncertainty. We present two structures combining these parameters. Finally, our explorations suggest that the level of the desired contingency measurement determines the appropriate information structure and that this measurement is needed in each specific decision context.