In 1999, I began working with Steve Barley at Stanford on a large study of advanced information technology in modern engineering work. Paul Leonardi, now on the faculty of UC Santa Barbara, worked on this project and led our continued study of the global distribution of engineering work. We focused on three occupations: (1) structural engineers who design buildings, (2) hardware engineers who design microprocessor cores and their peripherals, and (3) automotive engineers who work in body design, safety and crashworthiness, and noise and vibration. The study has spanned 7 firms across 15 sites in 8 countries and featured a team of 27 researchers. We conducted hundreds of hours of observation of working engineers, wrote reams of fieldnotes and collected more than a thousand work artifacts (e.g., screenshots, calculation sheets, digital files, and the like). Our most recent focus examines how digital technologies made possible the global distribution of engineering work. For this research, our team traveled to engineering sites in the US, Mexico, India, Korea, Sweden, Germany, Australia, and Brazil.


Novel Methods

Early on in our research, I developed novel data collection methods for identifying and recording technology use in context and for preparing field notes. The methods reflect the intense, grounded measurement that is characteristic of industrial engineering with the rich narrative that is associated with ethnography. Overall, our methods resemble those of ethnography, but whereas ethnographers look for meaning and themes and seek to portray the insider's perspective, we often parse our fieldnotes into distinct units of analysis whose frequency can be counted and whose distributions can be analyzed. Thus, we often offer an etic rather than an emic analysis of action. The value of our approach is that it allows us to document actions precisely over time and space, which is difficult to achielve when analysis targets meanings and themes. 


Research Team

Over a dozen students and ten R&D members from IAC worked with us on this project. We thank students Julie Gainsburg, Fabrizio Ferraro, Menahem Gefen, Mahesh Bhatia, Lesley Sept, Carlos Rodriguez-Lluesma, Jan Chong, Alex Gurevich, Daisy Chung, Will Barley, Vishal Arya, Aamir Farooq, Paul Leonardi and Kurt Sandholtz for their research assistance. We also are indebted to IAC R&D personnel Hallie Kintner, Jan Benson, Bill Jordan, Susan Owen, Dan Reaume, Randy Urbance, John Cafeo, R. Jean Ruth, Mark Neale, and summer intern Mike Johnson.



Our work was made possible by funding from the National Science Foundation under grants CISE IIS-0070468, ITR- 0427173, and SBE-0939858/9. We thank Suzi Iacono of the NSF for her help, enthusiastic support and mentorship over the course of this large and ambitious project. We also thank Julia Lane of the NSF for providing our most recent support for our global research. General Motors Corporation supplied additional funding. We thank David VanderVeen, Jan Benson, Bill Jordan and Hallie Kintner for their superb support and guidance.