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Precursor Analysis and Field Safety Engagements

Precursor analysis was designed and tested to predict and prevent serious incident and fatality (SIF) events. The method was developed through a 3-year industry-academic collaboration, over $1M in investment, and experimentally validated across over 100 cases. Precursor analysis has proven to identify the warning signs of SIF events before they occur through a brief but targeted field safety engagements. Intended for high-risk work, precursor analysis focuses on elusive human factors (e.g., work pressures, tendency to improvise, and fatigue) that are often consequences of safety culture. The method requires about 8 minutes to implement and complements industry-standard pre-job meetings, audits, and job hazard analyses.

Recent Work

In 2019, we collaborated with the Edison Electric Institute to adapt precursor analysis to the Electric Power Generation and Delivery Sector. After completing a rigorous 12-month team effort, the work resulted in a customized precursor analysis method that is now being adopted broadly. Please watch the video below for a brief overview of the industry perspectives on precursor analysis.


Example Field Safety Engagement

What we offer
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In-Person Keynote Presentation

Dr. Matthew Hallowell offers keynote presentations on this topic and has delivered to audiences ranging from 100 to over 2,000. His presentation includes a number of engaging audience activities and generates a vibrant discussion.

Speaker Bio


In-Person Workshops

Workshops on precursor analysis and field safety engagements is offered for all levels. Typically, we recommend that an organization host a leadership introductory session to explore whether precursor analysis is something that the organization would like to pursue. Subsequently, field-level management can be trained across the organization and implementation plans can be established.

Workshop Description

Client List

We have delivered precursor analysis and field safety engagement keynote addresses and/or workshops to the following organizations:

  • ​Ameren

  • Aecon

  • AEP

  • CEPA Foundation

  • Chevron

  • Danaher

  • Department of Energy

  • Edison Electric Institute

  • Enbridge

  • Entergy

  • Eversource

  • Exelon

  • INGAA Foundation

  • Mastec

  • Minnesota Safety Council

  • National Academy of Construction

  • Pembina Pipelines

  • Price Gregory International

  • Rocky Mountain Electric Institute

  • Stanford University

  • TC Energy

  • Technip FMC

  • Tennessee Valley Authority

  • Wolfcreek Group

Research Evidence 

Precursor analysis was originally developed by NASA in response to a series of high-profile catastrophes. The method revealed that extreme events could be predicted and prevented by examining anomalies in their systems. In 2014, our team began to explore how precursor analysis could be adapted to construction and adjacent industries. Through a series of controlled experiments using case data from serious injuries and fatalities (SIF), potentially serious injuries and fatalities (pSIF), and successful work, we were able to identify the factors that distinguished success from failure. Although we examined nearly a hundred potential predictors, our research showed that human factors like a distraction, fatigue, and improvisation were the most powerful predictors. Once adapted to construction, the method was further refined for specific sectors like electric power generation and delivery, building trades, and healthcare.

Publications (available on request)

  • Alexander, D., Hallowell, M.R., and Gambatese, J.A. (2017). “Precursors of construction fatalities I: Iterative experiment to test the predictive validity of human judgment.” Journal of Construction Engineering and Management, ASCE, 04017023-1 to 04017023-12. 

  • Alexander, D., Hallowell, M.R., and Gambatese, J.A. (2017). “Precursors of construction fatalities II: Predictive modeling and empirical validation.” Journal of Construction Engineering and Management, ASCE, 04017024-1 to 04017024-12. 

  • Hallowell, M.R., Alexander, D., Gambatese, J.A. (2017). “Energy-based safety risk assessment: Does magnitude and intensity of energy predict injury severity?” Construction Management and Economics, 2017, 1-14. 

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