A Value-Driven Model for Data Manufacturing: An Application for Optimal Error-Correction Policy

摘要

Data is an essential resource to the modern business. Corporate investments in data management solutions are increasing along with growing concerns regarding their cost and contribution to profitability. A data-related factor identified as having a significant effect on cost and profitability is the quality of the organizational data resources [Redman, 1996]. The Data Quality Management (DQM) literature addresses the quality issue at different levels - from the high-level paradigm of Total Data Quality Management (TDQM) [Wang, 1998], to specific monitoring and improvement methodologies [e.g., Redman, 1996, Ballou et al., 1998]. Research, however, has not examined to the same extent, the economic contribution of DQM initiatives to business-value and profitability. The high costs of DQM initiatives make their contribution important to understand. To what extent do organizations gain value from data quality improvements? Does the value gained offset costs? How should considerations of value and cost affect DQM decisions?