Verisk: Trailblazing in the Big Data Jungle

Andrew  Wasynczuk; Francesca  Gino; Karim  Sameh

Case | HBS Case Collection | September 2018

Verisk: Trailblazing in the Big Data Jungle

by Andrew Wasynczuk, Francesca Gino and Karim Sameh

Abstract

This case revolves around Verisk Analytics' initiatives to drive innovation throughout the firm's many business verticals. Verisk, originally named ISO, started life as an insurance rating agency in the early 1970s, acting as an intermediary between insurance companies and state governments. Over time, the firm transformed from being a non-profit to a for-profit entity, while expanding its lines of business to realms other than insurance. By both exploring the history of the insurance industry and Verisk's unique position within it, the case provides readers with an understanding of the firm's growth strategy and why innovation is so crucial for its success. The case leaves readers to ponder Verisk's innovation and growth strategy, challenging them to assess its strengths and weaknesses.

Keywords: Verisk; Argus; Wood Mackenzie; Insurance; energy; analytics; data; big data; Acquisitions; acquisition strategy; innovation; organic growth; Innovation Strategy; Innovation Leadership; Technological Innovation; Acquisition; Growth and Development Strategy; Insurance Industry; Energy Industry; Consulting Industry; United States; United Kingdom; New York (state, US); England;

Language: English

Format: Print

15 pages

Educators Purchase

Citation:

Wasynczuk, Andrew, Francesca Gino, and Karim Sameh. "Verisk: Trailblazing in the Big Data Jungle." Harvard Business School Case 919-014, September 2018.

In six studies, we show that after experiencing a threat to their abilities, individuals who misrepresent their performance as better than it actually is boost their feelings of competence. We situate these findings in the literature on self-protection. We show that this “counterfeit competence” effect holds when threat is measured (Study 1), manipulated (Study 2), and when the opportunity to cheat is randomly assigned (Study 3). We extend our findings to a workplace context, showing that threatened individuals who lie on a job application feel more capable than those who report them honestly (Study 4). Finally, consistent with the argument that counterfeit competence is driven by self-protection, we find individuals do not predict they would experience such a boost (Study 5) and that cheating after threat offers benefits similar to those provided by other established methods of self-protection (Study 6). Together, our findings suggest that, after threat, misrepresenting one’s performance can function as a mechanism that helps to restore positive self-evaluations about one’s capabilities.

Faculty & Research

Verisk: Trailblazing in the Big Data Jungle

Abstract

Citation:

About the Authors

More from these Authors