SOURCE: MIT Sloan Management Review

MIT Sloan Management Review

November 17, 2015 16:00 ET

MIT Sloan Management Review: Study of Internal Email and Social Messaging Data Helps Identify High Performing Teams

Data Identifies Key Criteria That Distinguish High-Performing Organizations From Underperforming Ones and Highly Innovative Teams From Less Creative Ones

CAMBRIDGE, MA--(Marketwired - November 17, 2015) - Research findings from an article published today in MIT Sloan Management Review indicate that the study of employees' aggregated email and social data can give managers insights about how groups should be organized and led -- as well as about optimal participation and communications patterns.

The article, titled "What Email Reveals About Your Organization," was written by Peter A. Gloor, a research scientist at the MIT Center for Collective Intelligence at the MIT Sloan School of Management. For over a decade Gloor and his colleagues have studied hundreds of organizations through the lens of their employee networks as portrayed by email and other electronic archives.

Key findings from their research include:

Strong leadership matters. Teams with strong leaders were found to be more creative and to produce a higher volume of quality work.

Rotating leadership is the best predictor of creative teams. Teams in which different individuals took turns leading the group were more creative than teams in which one person was consistently in charge.

Team-wide participation improves outcomes. Teams whose core members were each contributing a similar number of email messages were more creative than teams in which a few individuals were contributing most of the messages.

Response times are indicators of employee and customer satisfaction. Slower response times usually meant decreased satisfaction among team members.

Tone of messages correlates with engagement. In one project studied, the researchers found that the more positive language a salesperson used with a customer, the less happy the customer was. Also, people who were most likely to leave their jobs became less emotional in their use of language in the three months leading up to their resignations than people who were not planning to resign.

Shared context is important. High-functioning teams tend to define their own language.

In their study, the researchers insured employee privacy by doing anonymized analysis and by restricting most of their content analysis to email header information -- sender, the receivers, subject, and timestamp. They did use machine-learning software to evaluate entire messages for sentiment and emotionality, but looked only at sentiment and patterns of new word usage, not the content of individual messages.

Gloor and his colleagues have used the findings to develop a process for analyzing and improving the performance of organizations. By looking at the various signs of collaboration from electronic communication records, managers have been able to get a unique view into the nervous system of their organization -- allowing them to optimize communication for superior collaboration and innovation.

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