Decision making in HSE can be a complex and difficult endeavor. With so many factors to be considered, where a life can hang in the balance, it is imperative that well-built compliant processes be followed with rigor. Decisions are typically made considering the probability of a risk as well as the consequences of risk. You can know as much as you can know, but not what you don’t know.
Assessment of risk is based on the information known. Institutional knowledge, historical performance, the current operational state, and expected operational state come from a variety of sources. How you assemble this mélange into a useful risk profile can be a challenge as many data sources are digital and in most cases un-reduced to decision making size.
We must be aware that information impacting safety comes from a variety of sources and not just HSE systems. The real time systems that monitor the condition and operating parameters of a plant serve to give operators an up to the minute heartbeat of the emerging collective risk. For example, if there are a high number of DCS alarms, equipment being run outside operating limits, or maintenance items running behind, there can be an essential barriers of protection updated in near real time. This is all part of the digitalization initiatives coming to industrial plants and processes.
The safety imperative is to get to zero recordable incidents and zero harm. In addition to addressing the regulators, it’s essential that safe operations be maintained for the workforce, the community, the environment, and for the continuation of business. Not only the systems and processes need to be in place, a deeply ingrained and persistent safety culture is required. Even though human performance is never guaranteed, we can take steps to assure that the most useful information possible is available. Looking to the potential consequences of events, analytics and predictive methods become ever more important in guiding decision making, provided there is a good understanding of how the guidance is developed.
Dashboards that provide leading rather than lagging indicators help you be proactive to as to anticipate high potential incidents.
Examples of lagging indicators include:
• Downtime for equipment
• Recordable incidents
• Count of near misses
Examples of leading indicators include:
• Significant Rate-of-change increase in control system alarms in a plant area / unit
• Overdue training / certifications
• Excessive limit set excursions in a given area / unit
• Overdue work orders in a given area / unit
• Deferred work orders…
• Overdue MOCs…
Your automation provider or your operational intelligence provider should deliver more than just what has happened. Do not be complacent in merely recording monthly data, be sure to place an emphasis on emerging risk in collective leading indicators i.e. would you really want to be working in an area of plant where all of those leading indicators are in alert status?
Access to the details of those leading indicators is critical as they guide the decision process on the course of action
As the focus of lagging indicators measure failure, you’ll want to focus on leading indicators as they can potential help reduce failure. For all this to be effective it must be used in an enterprise wide safety culture.
More information about leading indicators that support decision making in HSE can be found at the Vizion HSE & PRM page.
