30 Pages Posted: 9 Aug 2017
Date Written: August 4, 2017
Through a multi-modal empirical analysis of the data-management experiences of large institutional investors (‘Giants’), we find that these entities are struggling to:
1) utilize data efficiently; and
2) consistently achieve desired levels of data quality.
We use these findings to design a new tool for helping Giants more efficiently manage data quality: data budgets. Data budgets augment the current budgetary framework available to Giants by being able to ‘plug in’ to it directly, in a way that more comprehensively highlights how data quality links to other organizational resources to drive value, performance, and innovation among Giants. We present five practical illustrations of how data budgets can help Giants better manage overall resources.
Keywords: data management, institutional investing, resource accounting, strategic efficiency
Suggested Citation: Suggested Citation
Monk, Ashby H. B. and Nadler, Daniel and Rook, Dane, Data Management in Institutional Investing: A New Budgetary Approach (August 4, 2017). Available at SSRN: https://ssrn.com/abstract=3014911