Decision Analytics in Design and Construction

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Aflatoony, Leila
Ashuri, Baabak
Bartlett, Chris M.
Rakha, Tarek
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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.
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