A University of Texas at Arlington civil engineer and some of his students have written a book about using data analytics to solve chronic problems in the construction industry, such as cost and time overruns and rising material costs.
The authors of “Construction Analytics: Forecasting and Investment Valuation” are Associate Professor Mohsen Shahandashti and students Bahram Abediniangerabi, Ehsan Zahed and Sooin Kim. They cover time series basics, models and forecasting approaches, investment valuation and how to apply such concepts to solve construction engineering problems.
“Construction costs for critical infrastructure and new buildings are highly variable, and the people hired to estimate and manage those costs often lack training in modeling and forecasting that leads to accurate valuations,” Shahandashti said.
“As a country, we spend billions of dollars on infrastructure, so we need to improve the business side,” he said. “Why are so many construction projects running behind with cost estimates that are not accurate? These are hard questions to answer and difficult decisions to make, and many construction engineers aren’t prepared to look at valuation through data analytics because it is not taught at schools.”
According to Shahandashti, this is the first book that provides a thorough look at construction forecasting and investment valuation with hands-on examples and computer codes. It covers several theories and includes codes for real-world situations. These tools will allow construction engineers to look at investment valuation and answer questions to determine if a project is worth the expenditures or not.
“This is an exciting opportunity because it’s a proactive way of thinking,” he said. “We know the advantages and the limitations of data analytics, and now we’re exploring the possibilities.”