MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Implicit costs of data and analytics

Author(s)
Kapicka, Bryan A. (Bryan Anderson)
Thumbnail
DownloadFull printable version (2.601Mb)
Other Contributors
Sloan School of Management.
Advisor
Erik Brynjolfsson.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Firms have been able to utilize data and analytics to achieve a variety of economic benefits. To realize this value, firms have to invest in the necessary information technology, process updates, and employee training. These costs are straightforward, but firms also incur implicit costs, the costs of mitigating potential risks and maximizing firm value from data and analytics. These costs are less well understood. This paper focuses on two of these costs, the mitigation of the adverse effects of metrics and the investment required to effectively complement people with information technology. The first cost is the adverse effects of metrics and refers to the potential for metrics and analytics to compromise business objectives that they were originally intended to enhance. The analysis of this cost primarily utilizes Holmstrom and Milgrom's Multitask Principal-Agent Model to evaluate the impacts that incentives, metrics, measurability, and job design have on the firm's payoff. This model and ensuing analysis provide guidance for firms to avoid the pitfalls that accompany an increased reliance on data and analytics. The second cost refers to the firm's investment to complement people with information technology to maximize their payoff from data and analytics. The evaluation of this cost discusses the conditions under which it is appropriate to complement, or substitute, humans with technology. In the scenarios where people are complemented by technology, this paper outlines additional practices and examples to highlight ways in which a complementary relationship between people and information technology can be cultivated. This discussion covers the efforts to shift people away from solely relying on intuition, while preventing them from blindly accepting data and empowering them to deal with the inherent complexity of new information afforded by data and analytics. The analysis and discussion of each cost references existing research and case examples. This paper intends to further the understanding of these costs as well as identify future opportunities for research.
Description
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 69-72).
 
Date issued
2014
URI
http://hdl.handle.net/1721.1/90221
Department
Sloan School of Management
Publisher
Massachusetts Institute of Technology
Keywords
Sloan School of Management.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.