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Organizational Engineering using Sociometric Badges

Organizational Engineering using Sociometric Badges. Benjamin N. Waber, Daniel Olgu ín Olguín, Taemie Kim, Akshay Mohan, Koji Ara, and Alex (Sandy) Pentland MIT Media Laboratory – Human Dynamics Group NetSci 2007. Motivation. Quantification of social systems Surveys Subjective Inaccurate

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Organizational Engineering using Sociometric Badges

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  1. Organizational Engineering using Sociometric Badges Benjamin N. Waber, Daniel Olguín Olguín, Taemie Kim, Akshay Mohan, Koji Ara, and Alex (Sandy) Pentland MIT Media Laboratory – Human Dynamics Group NetSci 2007

  2. Motivation Quantification of social systems • Surveys • Subjective • Inaccurate • Human observation • Subjective • Does not scale • Electronic communication (E-Mail, IM, etc.) • Incomplete • Representative of face-to-face interaction?

  3. Sociometric Badge Sociometric Badge (Olguín et al., 2007) • Multiple sensing capabilities • Communication capability • Bluetooth enabled

  4. Experiment • Deployed the Sociometric Badge for one month in a German bank’s marketing division • 22 employees • Interesting physical layout • Obtained e-mail records from a concurrent study (Oster, 2007) • Subjective performance and satisfaction survey administered daily

  5. Total Communication Ad campaign planning: Face-to-face communication on top, email on bottom

  6. Total Communication Ad campaign execution: Face-to-face communication on top, email on bottom

  7. Total Communication Full Month Visualization

  8. Results: Total Communication • Total communication highly negatively correlated with job and interaction satisfaction (r = -0.48, -0.53, p < 0.05) • Betweeness was negatively correlated with interaction satisfaction (r = -0.49, p < 0.05) • Inter-status communication was also negatively correlated with interaction satisfaction (r = -0.64, p < 0.005) • Proximity was highly negatively correlated with e-mail communication (r = -0.55, p < 0.01)

  9. General Findings • Face-to-face ties had a moderate negative correlation with e-mail ties(r = -0.19, p < 0.05) • Individual inter-status availability ties and e-mail ties were highly positively correlated when both were present (r = 0.64, p < 0.0001)

  10. Future Work • Analyze data at finer level of detail to identify mirroring and turn taking behaviors • Implement a social network optimization framework that operates on this data • Create individual feedback tools (Kim et al., 2007) • Perform additional experiments • Data Server Configuration firm • Student group exercises at Harvard (with Katz and Lazer)

  11. Conclusions • The Sociometric badge is a powerful and efficient data collection platform • E-Mail data is not representative of face-to-face interaction • Total communication is an important predictor of perceived productivity and satisfaction

  12. Thank You! Questions?

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