Buffer.com (B)

Susanna  Gallani; Tiffany Y. Chang; Brian J. Hall; Jee Eun  Shin

Supplement | HBS Case Collection | May 2017

Buffer.com (B)

by Susanna Gallani, Tiffany Y. Chang, Brian J. Hall and Jee Eun Shin

Abstract

Buffer decided to release its salaries and compensation calculation formula to the public, and the public reaction was greater and more positive than they would have imagined. The company experienced both an increase in volume and a change in the kinds of inbound applications they received. As the company continued to grow, Buffer's senior leaders continued to revise the compensation formula based on feedback both internally and from the public. Particularly, they hoped to strengthen the link between pay and performance, which in the current version of the formula was incorporated using a loosely defined "experience level" component. However, defining clear performance metrics and experience levels was not an easy task.

Keywords: compensation; compensation design; company values; culture; transparency; attraction; selection; performance measurement; performance measures; performance metrics; startup management; Compensation and Benefits; Organizational Culture; Values and Beliefs; Performance Evaluation; Measurement and Metrics;

Language: English

Format: Print

10 pages

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Citation:

Gallani, Susanna, Tiffany Y. Chang, Brian J. Hall, and Jee Eun Shin. "Buffer.com (B)." Harvard Business School Supplement 917-020, May 2017.

Using detailed information on Institutional Shareholder Services (ISS) assessments of firms’ compensation practices, we examine whether these assessments identify poor compensation practices as measured by subsequent performance. While prior research provides consistent evidence of an association between shareholder voting outcomes and ISS recommendations, the evidence is mixed over whether their recommendations convey information about poor compensation policies. We find that ISS “Against” recommendations are associated with worse future accounting performance, consistent with ISS being able to detect suboptimal compensation packages. However, workload compression has an effect, as we find that the relation between assessments and future performance is stronger during off-season (for firms with non-December fiscal year end).

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Buffer.com (B)

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