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Learning from Near-Miss Incidents

Learning from Near-Miss Incidents. An Initiative for the Bulk Power System. Source: Wiegmann , D.A. and Shappell , S.A. (2003). A human error approach to aviation accident analysis: The Human Factors Analysis and Classification System. Surrey, England: Ashgate Publishing Limited. P. 18.

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Learning from Near-Miss Incidents

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  1. Learning from Near-Miss Incidents An Initiative for the Bulk Power System

  2. Source: Wiegmann, D.A. and Shappell, S.A. (2003). A human error approach to aviation accident analysis: The Human Factors Analysis and Classification System. Surrey, England: Ashgate Publishing Limited.P. 18. • “Given that most human factors safety programs are not data-driven, it only stands to reason that they have produced intervention strategies that are only marginally effective at reducing the occurrence and consequences of human error.”

  3. How can we move toward “data-driven” safety and training programs? • By collaborating to create a North American Near-Miss Database (NMDb) • Such an NMDb would facilitate the capture and analysis of near-miss incident data from the industry in order to: • Improve understanding of human performance factors, and • Identify and address challenges that could impact the reliability of the bulk electric system (BES)

  4. A near-miss is an incident in which no injury property damage or system reliability lapse occurred • “You got lucky.” • There is currently no nationwide database for near-miss incidents in the BES • The resultant uncoordinated data is of little value to the industry as a whole

  5. Proposed NMDb • WECC’s Human Performance Work Group (HPWG) has been collaborating with EPRI, NERC, NATF, BPA, Dominion (and more) to produce a white paper • Released July 19, 2012 • The goal is to develop and maintain an industry-wide Db as a large source of human performance, personnel safety, and BES reliability information

  6. Features of the Proposed NMDb • Voluntary and Confidential report entry system • Processes to review and polish entered data to ensure anonymity and data value • A framework for analysis of reported incidents leading to “lesson learned” • Broadcast of the “lesson learned” to the entire industry • Regulatory agencies would be asked to remain at arm’s length

  7. Models for our NMDb • Aviation Safety Reporting System • http://asrs.arc.nasa.gov/ • National Fire Fighter Near-Miss Reporting System • http://www.firefighternearmiss.com/ • Federal railway Administration • http://www.closecallsrail.org/

  8. Funding • The task group will prepare a proposal to secure funding for the implementation (the first 2 years) and ongoing support of the NMDb from: • Department of Energy, • Homeland Security, and/or • Other interested parties

  9. Source: Reason, J. (2008). The Human Contribution: Unsafe Acts, Accidents, and Heroic Recoveries. Surrey, England: Ashgate Publishing Limited. P. 240. • “Since catastrophic failures are rare events in well-defended complex systems, collectively mindful organizations work hard to extract the most value from what little incident and accident data they have.” • “They actively set out to create a reporting culture by commending, even rewarding, people for reporting their errors and close calls.”

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