Here is an excerpt from an article written by Matthew Corritore, Amir Goldber and Sameer B. Srivastava for Harvard Business Review and the HBR Blog Network. To read the complete article, check out the wealth of free resources, obtain subscription information, and receive HBR email alerts, please click here.
Credit: Jean-Pierre Attal/Courtesy of Galerie Olivier Waltman
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A business’s culture can catalyze or undermine success. Yet the tools available for measuring it—namely, employee surveys and questionnaires—have significant shortcomings. Employee self-reports are often unreliable. The values and beliefs that people say are important to them, for example, are often not reflected in how they actually behave. Moreover, surveys provide static, or at best episodic, snapshots of organizations that are constantly evolving. And they’re limited by researchers’ tendency to assume that distinctive and idiosyncratic cultures can be neatly categorized into a few common types.
Our research focuses on a new method for assessing and measuring organizational culture. We used big-data processing to mine the ubiquitous “digital traces” of culture in electronic communications, such as emails, Slack messages, and Glassdoor reviews. By studying the language employees use in these communications, we can measure how culture actually influences their thoughts and behavior at work.
In one study, two of us partnered with a midsize technology company to assess the degree of cultural fit between employees and their colleagues on the basis of similarity of linguistic style expressed in internal email messages. In a separate study, two of us analyzed the content of Slack messages exchanged among members of nearly 120 software development teams. We examined the diversity of thoughts, ideas, and meaning expressed by team members and then measured whether it was beneficial or detrimental to team performance. We also partnered with employer-review website Glassdoor to analyze how employees talk about their organizations’ culture in anonymous reviews to examine the effects of cultural diversity on organizational efficiency and innovation.
The explosion of digital trace data such as emails and Slack communications—together with the availability of computational methods that are faster, cheaper, and easier to use—has ushered in a new scientific approach to measuring culture. Our computational-lingustics approach is challenging prevailing assumptions in the field of people analytics and revealing novel insights about how managers can harness culture as a strategic resource. We believe that with appropriate measures to safeguard employee privacy and minimize algorithmic bias it holds great promise as a tool for managers grappling with culture issues in their firms.
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Matthew Corritore is an assistant professor of strategy and organization at McGill’s Desautels Faculty of Management.
Amir Goldberg is an associate professor of organizational behavior at Stanford’s Graduate School of Business. He and Sameer B. Srivastava codirect the Berkeley-Stanford Computational Culture Lab.
Sameer B. Srivastava is an associate professor and the Harold Furst Chair in Management Philosophy and Values at the University of California, Berkeley’s Haas School of Business. He and Amir Goldberg codirect the Berkeley-Stanford Computational Culture Lab.