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Data Management in Institutional Investing: A New Budgetary Approach

30 Pages Posted: 9 Aug 2017  

Ashby H. B. Monk

Stanford University - Global Projects Center

Daniel Nadler

Kensho Technologies; Harvard University

Dane Rook

Stanford University

Date Written: August 4, 2017

Abstract

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

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

Ashby H. B. Monk

Stanford University - Global Projects Center ( email )

United States

Daniel Nadler

Kensho Technologies ( email )

20 University Road
Cambridge, MA 02138
United States

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Dane Rook (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

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