The adoption of processes to support HSSE within the Oil and Gas industry offers an opportunity for valuable insight into the culture of organizations, facilities, groups and individuals. Information and data generated by HSSE processes and captured in various information systems can be analyzed statistically to identify anomalies and trends. Many of these processes are now mandated through regulations. The much-discussed offshore SEMS regulations introduced by BOEMRE in 2010, as well as other pre-existing regulations such as Coast Guard regulations are heavily HSSE process centric and are a good example of this. When these processes are supported by the appropriate information management tools, the data generated by these processes can be captured with little or no effort on the part of workers, causing minimal operational impact.

Taking an investigative approach to assessing this data, with careful planning a set of Key Cultural Indicators (KCIs) can be identified within the data set. Using advanced statistical analysis techniques based on the 6-sigma business management strategy, KCI data from single (point-in-time) and multiple (periods of interest) data sets can be analyzed to help identify areas of excellence, and areas of risk. The same data can also be used to quantify an HSSE Cultural Index number for the data set under evaluation. This index can be used for comparison and trend evaluations against comparable data sets (e.g. Facility ‘A vs. Facility ‘B’). This approach can be extended to the evaluation of location-based (spatial) data. Statistical evaluation of spatial data can be used to produce heat maps identifying physical locations with anomalous behavioral performance within a data set(s).

These conclusions can be used to plan further investigations into operational behavioral patterns, focused on delivering behavioral improvements. This approach to evaluating HSSE culture is applicable across the HSSE spectrum.

This discussion will consider the potential of this approach to understanding HSSE culture and the benefits this may bring, as well as exploring problems with this approach that must be considered when planning a behavioral evaluation program.

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