Long before statistical whiz Nate Silver predicted the outcome of the 2012 presidential election and "Moneyball" became a household word, structural engineers employed the Monte Carlo method of simulating failures to fine-tune their designs of tall buildings and other critical structures. Now probabilistics is finding broader use among project estimators, planners and risk managers looking to cut down on schedule and cost variables that can suck valuable time, money and profit out of construction work.

Roughly 56% of firms involved in construction use probabilistic methods to manage risk, according to a 2012 study from the Construction Industry Institute. Over the course of two years, CII's research team surveyed more than 100 companies and found that 90% of the respondents received a return on investment of at least 1:10, while around a third saw an ROI of 1:100. "With such high returns on their investments, it is not surprising to find that many organizations are expanding their business practices to include probabilistic approaches to improving management of both project and corporate risk," the study says.

Participating organizations use three basic levels of analysis (see flow chart). The first two levels, identification and deterministic analysis, may satisfy the needs of most projects, the CII study says. The higher the project cost, the more likely firms are to use probabilistic risk analysis. Exotic delivery methods, novel designs and challenging locations may also trigger its use. On the flip side, firms report difficulty interpreting results, lack of organizational support and lack of technical expertise as barriers to executing the analysis.

Still, as statistics have become more visible in the public domain—such as in politics, finance and sports—and with more firms placing an emphasis on risk management, professionals have sought to become better forecasters. "There is much greater awareness in the general public and construction engineering and management community of risk and how risk and uncertain events can impact society at the project level," says Keith Molenaar, a construction engineering professor at University of Colorado, Boulder, and a CII report author. Several software companies, such as Primavera, now offer Monte Carlo simulators that can run on an everyday laptop.

Using statistical analysis to predict project risks helps firms make confident decisions, users say. "It's got some real meat-and-potatoes stuff behind it that will pass the red-face test with management," says Craig Relyea, manager of capital projects planning for Indianapolis-based Eli Lilly and Co. and another CII study author. Large-scale teams using it today include those building One World Trade Center in New York City and the Panama Canal expansion.

While not every owner or contractor may have the resources to run a computer simulation, they should perform a basic risk analysis, Molenaar says. "There is a level of sophistication that you have to have to be able to use the tools," he explains. "Anybody can interpret one number from an estimate, but to be able to look at a range of estimates and make a prediction from that output is a little bit challenging."