In an effort to better understand barriers, benefits and the implementation process of risk management on construction projects, Keith Molenaar, professor of construction engineering management at CU-Boulder; Amy Javernick-Will, assistant professor of construction engineering management at CU-Boulder; and CU-Boulder graduate student Chris Senesi along with industry members of a Construction Industry Institute Research Team recently investigated probabilistic risk management within the engineering and construction industry.
Specifically, the study finds that respondents rely on three basic levels of analysis: identification, deterministic analysis and probabilistic analysis; however, the first two levels are often enough. For higher project costs, exotic delivery methods, original designs and difficult locations, respondents are more likely to use probabilistic risk analysis. Interpreting results remains a challenge for respondents, though, as they report lacking organizational support and technical expertise to executing the analysis.
With more firms focusing on risk management and statistics gaining ground in various public industries, there is a push to improve forecasting among professionals, the study finds.
“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,” Molenaar says.
The study also reveals that of the construction companies replying on probability risk analysis, 90 percent say they have seen a return in investment of at least one in 10. Another one-third of respondents say their ROI reached one in 100.
“Although tools to perform risk analysis have been around for decades, the greater awareness of risk and uncertainty on project outcomes have made the use of these tools more prevalent throughout the industry with touted benefits including higher ROIs, increased collaboration, increased ability to manage risks, costs, schedules and increased confidence in project decision making,” Javernick-Will says. “Due to these benefits, many recommend that basic risk management, starting with level one, risk identification, should be implemented on all projects with additional analysis required for more complex projects that require a higher level of certainty.”