(5c) Safeocs: An Innovative Approach to Understanding Industry-Wide Safety Event Data | AIChE

(5c) Safeocs: An Innovative Approach to Understanding Industry-Wide Safety Event Data

Authors 

Collia, D. - Presenter, Bureau of Transportation Statistics
In this age of "big data," it is important to recognize the role effective and innovative data management have in improving safety performance. The conclusions of several reports and studies is that there is a clear need and benefit for pooling of data in order to have a complete picture of the safety in any industry sector. To do this effectively, it is important to recognize the need for common definitions to facilitate data and experience sharing. The inclusion of near misses in safety event databases is necessary because important lessons can be learned from them. A related challenge is that of avoiding double-reporting of events in different organizations (i.e., regulatory authorities, international associations). Aggregation of data is absolutely necessary for disseminating knowledge on past events, obtaining a clear overall picture of the risk of possible safety event types, understanding the effectiveness of barriers, determining what constitutes a leading indicator, and analyzing trends with the objective of trying to anticipate the next major event.

Following the Deepwater Horizon oil spill in April 2010, the oil and gas industry, regulators, and other stakeholders recognized the need for increased collaboration and data sharing to augment their ability to identify operational and process safety risks and address them before an accident occurs. The SafeOCS Industry Safety Data (ISD) Program is a voluntary confidential reporting program that collects and analyzes data to advance safety in oil and gas operations on the Outer Continental Shelf (OCS). This presentation focuses on the unique challenges and processes developed to capture, transform, aggregate, and analyze safety event data on an industry-wide basis for companies working in the U.S. Gulf of Mexico. The aggregated data are then utilized to identify industry-wide trends for advancing safety in oil and gas operations.

The objective of this presentation is to discuss the process used to successfully map data from separate companies to a single database thereby addressing the technical challenge associated with collecting, mapping, and aggregating data from different company-specific databases. Also included will be demonstrations of interactive dashboards developed to allow companies to compare how they are doing vs. the aggregated industry results. Finally, the presentation will address how this safety data management framework can be used to support other industry sectors.

Methods/Procedures/Process

Two distinguishing elements of the SafeOCS ISD program are 1) the source data protections offered under the Confidential Information and Statistical Efficiency Act (CIPSEA), and 2) the ability of participating companies to submit safety event data in whatever format currently used internally for company stewardship purposes without having to reformat or redact information prior to uploading it to SafeOCS.

Specific challenges to be addressed include:

  • the importance of common terminology and definitions,
  • the process developed to transform input from unique company data bases,
  • software considerations based on desired program features, expected volume of uploaded data, and the number of individual program participants,
  • identification and merging of multiple records related to the same safety event,
  • cybersecurity concerns as they relate to protection of data confidentiality,
  • visualization alternatives for aggregated data to ensure that analyses are presented in a meaningful manner that is understandable and of value to a mixed group of stakeholders, and
  • the development of participant and public dashboards, including how to address the level of interactivity expected by user.

Innovative Approach for Data Processing

The SafeOCS ISD program has the ability to accept data on safety events with and without consequences from participating companies in a non-standardized format, transform that data using defined analogs and machine learning techniques, then aggregate the data to allow analysis and identification of trends. All of these above steps are executed in a confidential manner that legally protects source data and user information.

Learning Outcomes

The value proposition associated with this approach is the opportunity to share learnings from all incidents and events that occur in an industry. This is particularly important for major hazards and associated prevention/mitigation barriers. Key aspects of this effort include:

  • identifies the type of data that will provide valuable information,
  • gains alignment on incident and indicator definitions,
  • utilizes a secure process for collection and analysis of the data,
  • implements a robust methodology for identifying systemic issues,
  • disseminates the results to stakeholders who can then take actions to reduce or eliminate the risk of recurrence through greater barrier integrity,
  • provides opportunities for stakeholders to network and benchmark performance, both individually and as an organization, and
  • sets up a framework wherein adverse actions cannot legally be taken against data submitters nor can raw data be used for regulatory development purposes.

Checkout

This paper has an Extended Abstract file available; you must purchase the conference proceedings to access it.

Checkout

Do you already own this?

Pricing

Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
Employees of CCPS Member Companies $150.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00