The study and analysis of large and complex data sets offer a wealth of insights in a variety of applications. Computational approaches provide researchers access to broad assemblages of data, but the insights extracted may lack the rich detail that qualitative approaches have brought to the understanding of sociotechnical phenomena. How do we preserve the richness associated with traditional qualitative methods while utilizing the power of large data sets? How do we uncover social nuances or consider ethics and values in data use?
Technical Boundary Spanners and Translation: A Study of Energy Modeling for High Performance Hospitals
High performance buildings—buildings with the aim of reduced energy and resource use— require that engineering analysis be at the center of an iterative and complex design process that assesses trade-offs, goals, and priorities across engineering and other fields of expertise. It has been observed that teams rarely get this right. Historical, cultural, and technical issues all get in the way of open communication and the integration of technical analysis. In this research, we ask what organizational and communication practices are needed for engineering to translate and design teams to synthesize complex energy modeling into the design of hospital buildings? In this paper we introduce a detailed ethnography of energy modeling during the conceptual phase of a new hospital design where energy modeling falls short of its potential. With cross case comparison, we found that a technically-knowledgeable boundary spanner in the owner organization enriches collaboration between the design team and the owner organization for more accurate and impactful energy modeling and improved translation of the model between team and owner. The energy modeling process became almost more important than the results of the energy model wherein the owner and design team had design-critical conversations about the model inputs and clear knowledge about the owner’s goals for the data. We propose that it is in this socially constructed knowledge where real high performance design can occur.
Dossick, Carrie Sturts, Gina Neff, Laura Osburn, Chris Monson, and Heather Burpee. “Technical Boundary Spanners and Translation: A Study of Energy Modeling for High Performance Hospitals.” Cle Elum, Washington: Engineering Project Organization Conference, 2016. http://www.epossociety.org/EPOC2016/papers/Dossick%20et%20al%20_EPOC_2016.pdf.
Finding Connections between Design Processes and Institutional Forces on Integrated AEC Teams for High Performance Energy Design
Engaging the need to better understand the problems of high performance energy design in AEC collaborative practices and delivery methods, this study tested a schema that differentiated between the micro level of everyday design decisions, the meso level of project organization that guides project delivery, and the macro level of institutions—professions, disciplines, and firms— within which AEC practice takes place. Based in observations and interviews of two large projects in a U.S. architectural firm, we used a comparative case study to develop a series of analytical themes that located where issues of meso and macro level forces impacted micro level energy design decisions. This study found that the architect’s disciplinary vision and project management styles were very influential over energy design accomplishment, while firm attitudes promoting high performance design had little effect. Overall, we found no example of micro level design decisions that did not implicate some type of meso or macro level influence. This suggests that industry guides emphasizing technical solutions achieved at the micro level are not adequate for the needs of evolving AEC integrated practices.
Monson, Chris, Carrie Sturts Dossick, Gina Neff, Laura Osburn, and Heather Burpee. “Finding Connections between Design Processes and Institutional Forces on Integrated AEC Teams for High Performance Energy Design.” Cle Elum: Engineering Project Organization Conference, 2016. http://www.epossociety.org/EPOC2016/papers/Monson_et%20al_EPOC%202016.pdf.