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  • 2015
  • Case

Fine Harvest Restaurant Group (cases A and B)

By: Clara (Xiaoling) Chen, Kenneth A. Merchant, Tatiana Sandino and Wim A. Van der Stede
  • Format:Print
  • | Language:English
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Abstract

The Fine Harvest Restaurant Group cases A and B examine a company's design of a new system to evaluate the performance (and determine the bonuses) for its restaurant managers. Fine Harvest had traditionally evaluated restaurant managers based on store margins and had not given enough consideration to the performance potential that the stores had when setting targets. In response to several restaurant managers' complaints that the performance evaluation system was unfair and incomplete, the top executives of the company hired a consultant to revise the measures and targets used to evaluate performance. The new performance evaluation plan aimed to (a) account for different drivers of performance at the restaurant level; and (b) assess the performance of each restaurant relative to a peer group operating under similar conditions. Students are provided with detailed databases that can enable them to compare the performance of the restaurants under the existing and proposed system.

Keywords

Incentive Systems; Relative Performance Evaluation; Restaurant Industry; Accounting; Economics; Human Resources; Measurement and Metrics; Labor; Performance; Salesforce Management; Retail Industry; North and Central America

Citation

Chen, Clara (Xiaoling), Kenneth A. Merchant, Tatiana Sandino, and Wim A. Van der Stede. "Fine Harvest Restaurant Group (cases A and B)." University of Southern California, Marshall School of Business Case, 2015.

About The Author

Tatiana Sandino

Accounting and Management
→More Publications

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  • The Impact of Subunit Culture Consistency on Employee and Customer Outcomes By: Jasmijn Bol, Robert Grasser, Serena Loftus and Tatiana Sandino
  • Buurtzorg By: Ethan Bernstein, Tatiana Sandino, Joost Minnaar and Annelena Lobb
  • From Online Content to Offline Results: Effects of a Best Practices Initiative on an Enterprise Social Network By: Shelley Xin Li and Tatiana Sandino
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