Anyone in business knows through painful experience the pervasive problems that exist because our knowledge of organizations is imperfect. Key information fails to flow to those who need it, departments fight with one another, and managers make decisions on fine-sounding theories rather than real information. Most mergers and acquisitions never realize the “synergies” that were envisioned. All this experience, and more, suggests that there is good reason for believing, as organizational theorist Elliott Jaques asserted a decade ago, that “management is in the same state today that the natural sciences were in during the 17th century.… There is not one single, well-established concept in the field of management on which you can build a testable theory.”
But what if sensors and networks of sensors could transform organizational research much as microscopes and new forms of dissection transformed medicine in the 18th and 19th centuries? Instead of revealing the cell and microbe, these devices would uncover patterns of activity that usually go unobserved in organizations: the dynamics of person-to-person relationships and the ways they affect managerial decisions and organizational practices. Imagine, for example, an automatic system that could detect a breakdown in the trust on which a creative team depends and flag specific steps that could fix it, or one that could map out the complete flow of information and knowledge within an organization — even what happens at the coffee machine or during social gatherings — and identify key hubs of exchange or bottlenecks.
At the MIT Media Lab, Pentland leads a team of about a dozen researchers who have developed a range of small, wearable electronic devices that can easily and accurately gather the kinds of social data needed for such analyses. These devices track not just the physical location of the people who wear them, but also the finer details of a person’s movement— in effect, his or her body language — and several distinct features of his or her vocal behavior. And by taking note of people’s proximity to others and the patterns of their movement, the team can foster new insights into collective human behavior: the subtle differences between effective and ineffective teams, and the structures and incentives that either improve or block collaboration.
For example, computer scientist Tanzeem Choudhury — a former student of Pentland’s currently dividing his time between Intel Research and the University of Washington — and several colleagues have begun to experiment with “dense sensors,” wearable stickers equipped with radio frequency identification (RFID) transmitters or motion detectors. The data from these sensors can be analyzed and compared to broader community data, such as crime and traffic statistics, to build models that describe and even predict the daily patterns of people’s lives, and their ever-evolving social networks. Choudhury’s team is exploring the idea of designing “smart environments” that would respond intelligently to people’s needs — automatically introducing crucial information into a discussion, for example, even when no single individual might recognize its vital relevance.
And in a still more ambitious study earlier this year, Pentland, teaming with David Lazer and Nancy Katz of Harvard University’s Kennedy School of Government, put sensors on hundreds of volunteers and recorded streams of data as they went about their business, from their morning commute through the lunch hour and into evening, capturing data about each meeting and encounter. The data revealed precisely who interacted with whom, how frequently, and whether the interactions happened in the workplace or elsewhere — over a few beers, for example. If someone gave a presentation to a group, the sensors would show how stressed he or she felt, as reflected in variations in the rhythms and pace of his or her speech; they would also reveal if the person felt confident and appeared that way to others, and who in the room responded with genuine interest.