Title:
Decision Analytics in Design and Construction

dc.contributor.author Aflatoony, Leila
dc.contributor.author Ashuri, Baabak
dc.contributor.author Bartlett, Chris M.
dc.contributor.author Rakha, Tarek
dc.contributor.corporatename Georgia Institute of Technology. College of Design en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Architecture en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Building Construction en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Civil and Environmental Engineering en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Industrial Design en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Mechanical Engineering en_US
dc.contributor.corporatename Georgia Tech Research Institute en_US
dc.date.accessioned 2019-10-21T17:49:24Z
dc.date.available 2019-10-21T17:49:24Z
dc.date.issued 2019-09-26
dc.description Presented on September 26, 2019 from 11:00 a.m.-12:00 p.m. in the Caddell Building, Flex Space, Georgia Tech. en_US
dc.description Forum panelists are: •Baabak Ashuri -- Associate Professor in the School of Building Construction and the School of Civil and Environmental Engineering •Leila Aflatoony -- Assistant Professor in the School of Industrial Design •Chris Bartlett -- Research Scientist in the School of Industrial Design, School of Mechanical Engineering, and the Georgia Tech Research Institute •Tarek Rakha -- Assistant Professor in the School of Architecture and faculty at the High Performance Building Lab. All panelist are associated with the Georgia Institute of Technology. en_US
dc.description Runtime: 52:07 minutes en_US
dc.description.abstract Decision analytics stands to have a profound impact on how design and construction disciplines are woven together to solve today's most complex problems. Rigorous data collection and analysis are core to design and construction decision making. The nature of analysis is to study complexity and deduce a reasonable summary that will then inform design and construction decisions. Decision analytics is distinguished from analysis by the emphasis on causality and prediction. The proliferation of computing power and access to rich data sets has driven innovation in the analytics tools market, lowering the barrier for entry to powerful analytics tools for designers and constructors. This means that decision-makers can more accurately identify causality and leverage the predictive power of analytics to inform design and construction decisions that anticipate and solve for problems much further into the future. Opportunities are growing to align decision analytics across multiple disciplines to minimize economic waste, maximize energy efficiencies, and enhance the lives of individuals and communities. An intuitive example of this opportunity lies in new building design and construction. Construction Analytics is a distinctive discipline, bridging the fields of building construction, civil and environmental engineering, economics, and operations research. Designers and decision-makers use descriptive analytics to identify indicators to cost overruns, diagnostic analytics to predict construction market resiliency after natural disasters, predictive analytics to identify future building trends, and prescriptive analytics to optimize resource allocation during construction projects. Building performance analytics explores various performance measures linked to building energy investigations, including measuring existing building performance through detailed audits to achieve substantial energy savings in deteriorating infrastructures, as well as simulating and visualizing new building and urban energy-flows to formulate informed design decisions empowered by data analytics for a sustainable and energy efficient future. In the example of new hospital construction, human-centered analytics can produce powerful insights and unlock empathy for the people (pediatric doctors, nurses, patients) who actively use the hospital space. Merging and visualizing several sources of quantitative and qualitative data draws out causality and enables predictive decision making aimed at improving the experience and performance of the people using the space. en_US
dc.format.extent 52:07 minutes
dc.identifier.uri http://hdl.handle.net/1853/61955
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.relation.ispartofseries College of Design Research Forum
dc.subject Analytics en_US
dc.subject Big data en_US
dc.subject Construction en_US
dc.subject Construction analytics en_US
dc.subject Construction cost en_US
dc.subject Construction productivity en_US
dc.subject Data analytics en_US
dc.subject Decision analysis en_US
dc.subject Decision analytics en_US
dc.subject Design en_US
dc.subject Design research en_US
dc.subject Forecasting en_US
dc.subject Hospitals en_US
dc.subject Human centered design en_US
dc.title Decision Analytics in Design and Construction en_US
dc.type Moving Image
dc.type.genre Lecture
dspace.entity.type Publication
local.contributor.author Rakha, Tarek
local.contributor.author Ashuri, Baabak
local.contributor.author Aflatoony, Leila
local.contributor.corporatename College of Design
local.relation.ispartofseries College of Design Research Forum
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relation.isAuthorOfPublication 61494ab3-3f45-44e8-abe2-b57df371eada
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relation.isSeriesOfPublication 057f41aa-4440-43d1-a19e-657b821f5d98
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