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CapTech partnered with a top oil and gas production company to build an industry-leading tool that leverages predictive analytics to reduce the number of safety incidents on the job. Utilizing data from multiple sources, CapTech built a scalable predictive model and intuitive dashboard that identifies risks in upcoming work and provides users with recommended mitigation tactics to reduce those risks.


From operating heavy machinery to harsh physical environments, employees in the oil and gas industry face the risk of incidents in the field every day. Accidents resulting from incorrect or incomplete risk mitigation create varying levels of damage and loss, both to the company and its people.

One significant challenge the company faced was having its health and safety data stored in disparate systems with no cross-platform associations. This structure made it difficult for field workers to locate and follow the appropriate safety procedures and guidelines.

Additionally, while this oil and gas company follows industry standards and best practices for health and safety, it was looking for additional insights to further protect its employees, by reducing the number of incidents across the organization.


CapTech leveraged its expertise in data management, data engineering, and data science to design and develop a successful product to help mitigate risk in the field. Beginning with data consolidation, CapTech enhanced the company’s ability to store and access health and safety data across the enterprise.

Additionally, CapTech saw an opportunity to improve the quality of health and safety data collected from the field. By implementing an end-to-end incident management system and providing training to field users, CapTech improved the quality of incident data at the source. Using this centralized and refined data, CapTech employed predictive analytics to identify the highest-risk areas for a possible safety event. An intuitive dashboard was then built to present this fundamental safety information to users in the field.


This dashboard engages ~85 site leaders daily, elevating the three highest risks and corresponding mitigation tactics for current and upcoming activities. By extension, leaders within the company now have clearer visibility into ~93,000 safety risks annually, empowering them to proactively engage with their teams to reduce the likelihood of employee harm. With data collected by the National Council on Compensation Insurance (NCCI) quantifying the average direct medical costs per injury at $41,000, and indirect costs up to 2.5 times higher, each of one of these 93,000 proactively identified risks represents an opportunity to prevent an unnecessary cost to the company of $143,500. 

Overall, this new tool has created increased visibility and vigilance to reduce potential employee harm by enabling:

  • A machine learning model that informs the oil and gas production company of new and tailored steps they can take to reduce risk across all levels of the organization.
  • A system that can build, train, and deploy machine learning models at scale to continuously improve risk predictions.
  • Trend and pattern identification visualized in a dashboard that informs users on how to reduce the risk of incidents in the field.
  • Improved work schedule alerting and systematic mitigation tactic deployment based on upcoming risk.