Part 2 in series about weather analytics and construction decisions

In the McKinsey&Company Capital Projects & Infrastructure article “How analytics can drive smarter engineering and construction decisions,” authors Garo Hovnanian, Kevin Kroll, and Erik Sjödin identify three applications that illustrate how engineering and construction (E&C) companies are embracing data-driven solutions and strategizing future initiatives. The three applications center on the critical questions about evaluating subcontractor bids and assessing project risk in project delivery and value chain.

Further, the authors contrast some of the many challenges in the construction industry when compared to the manufacturing sector. As a project-driven business, engineering and construction companies confront variability, as each project is different — whereas manufacturing companies embrace repeatability and predictability. Construction projects are generally non-repetitive with unique parameters across project delivery and value chain — owner, budget, schedule, site, subcontractors, suppliers, and manufacturers.

“In time, predictive analytics, machine learning, and artificial intelligence solutions will likely usher in bigger changes to the ways E&C firms bid on deliver projects.”

More in the next blog post about weather analytics and construction decisions…

About the authors

Garo Hovnanian is a vice president of major projects in McKinsey’s Philadelphia office; Kevin Kroll is a consultant in Chicago, and Erik Sjödin is a partner in Stockholm.

(Source: Hovnanian, Garo, et al. “How Analytics Can Drive Smarter Engineering and Construction Decisions.” McKinsey&Company Capital Projects & Infrastructure, McKinsey Insights,

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