Recent changes in available data sources, methodology and technology have led many statistical organizations to reconsider the practical alignment of quality measures with the value delivered to key data users, and related stakeholder communication. That has led to important developments in the assessment and improvement of data quality, but has produced less progress in connecting measures of data quality with stakeholder value. To address that question, this roundtable will review:
(1) Practical reasons to seek additional insights into the connection between multi-dimensional measures of data quality and stakeholder value
(2) Methods to assess the value of intangible products like statistical information, including distinctions between “use value” and “option value”
(3) Some strengths and limitations of previous work with (1) and (2)
Following that introduction, participants will be encouraged to discuss specific statistical information products (e.g., tables, model parameter estimates, or more complex analytic results) for which they need to explore practical connections between data quality measures and stakeholder value.