Abstract:We propose a sensor-based organisational design and engineering approach that combines behavioural sensor data with other sources of information such as e-mail, surveys, and performance data in order to design interventions aimed at improving organizational outcomes. We discuss relevant theory and technology backgrounds and describe the general requirements of a sensor-based organizational design and engineering system. We present an experimental platform that combines sensor measurements, pattern recognition algorithms, statistical analysis, social network analysis, and feedback mechanisms to study the relationship between social signalling behaviour and face-to-face interaction networks, with job attitudes and performance. We describe three case studies that we have conducted in several organisations using our experimental platform and the methodology that we have followed. The first study looks at e-mail and face-to-face networks in a marketing division of a bank. The second study analyses the effects of nurses" social behaviour on patients" length of stay in the postanaesthesia care unit of a hospital. Finally, the third study analyses the effects of retail bank employees" social behaviour on sales performance. Keywords: Organisational design; organisational engineering; organisational behaviour; sociometric badges; social sensors; interventions.Reference to this paper should be made as follows: Olguín Olguín, D. and Pentland, A. D. Olguín Olguín and A. PentlandAlex (Sandy) Pentland is a pioneer in wearable computers, mobile information systems, technology for developing countries, consumer health, and computational social science. He is one of the most-cited computer scientists in the world, and has won numerous international awards in the Arts, Sciences and Engineering. He is a co-founder of the Wearable Computing research community, the Autonomous Mental Development research community, the Center for Future Health, and was the founding director of the Media Lab Asia. He was formerly the Academic Head of the MIT Media Laboratory and is now MIT"s Toshiba Professor of Media Arts and Sciences. He is the founder and current faculty director of the Human Dynamics group. Pentland"s focus is on the development of human-centred technology, and the creation of ventures that take this technology into the real world. His work provides people with a clearer picture of their social environments, and helps companies and communities to reinvent themselves to be both more human and more productive.

This paper demonstrates a novel approach that combines generative models of organizational dynamics and sensor network data with a stochastic method. Generative models specify how organizational performance is related to who interacts with whom and who performs what. Sensor network data track who interacts with whom and who performs what within an organization, and the stochastic methodology fits multiagent models to data through the Monte Carlo method. The data set used in this paper documents how employees in a data service center handle tasks with different difficulty levels -tracked with sociometric badges for one month -and documents links between performance and behavior. This paper demonstrates the potential for improving organizational dynamics with body sensor network data, and therefore also shows the need to systematically benchmark differential organizational dynamics models on data sets for different types of organizations.