Data Quality Information (DQI) is metadata that can be included with data to provide the user with information regarding the quality of that data. As users are increasingly removed from any personal experience with data, knowledge that would be beneficial in judging the appropriateness of the data for the decision to be made has been lost. Data tags could provide this missing information. However, it would be expensive in general to generate and maintain such information. Doing so would be worthwhile only if DQI is used and affects the decision made. This work focuses on how the experience of the decision maker and the available processing time influence the use of DQI in decision making. It also explores other potential issues regarding use of DQI, such as task complexity and demographic characteristics. Our results indicate increasing use of DQI when experience levels progress through the stages from novice to professional. The overall conclusion is that DQI should be made available to managers without domain-specific experience. From this it would follow that DQI should be incorporated into data warehouses used on an ad hoc basis by managers.
It is well known, of course, that the assessment of this month's economic activity will improve with the passage of time. The same situation exists for many of the inputs to managerial and strategic decision processes. Information regarding some situation or activity at a fixed point in time becomes better with the passage of time. However, as a consequence of the dynamic nature of many environments, the information also becomes less relevant over time. This balance between using current but inaccurate information or accurate but outdated information we call the accuracy-timeliness tradeoff. Through analysis of a generic family of environments, procedures are suggested for reducing the negative consequences of this tradeoff. In many of these situations, rather general knowledge concerning relative weights and shapes of functions is sufficient to determine optimizing strategies.