When information about risk is communicated, it is often presented as an average, such as the chance of being attacked by a shark, the likelihood of being struck by lightening or the probability of contracting a particularly nasty illness. These averages are highly misleading; the risk of suffering one of these fates is dominated by the location the person is in, the activity being undertaken and the risk controls in place.
Exactly the same principle applies to industrial and transport risks, consequently risk management strategies need to be focussed on the specific circumstantial and locational factors. Sotera pioneered the development of location specific risk models where the risk for each location and activity is analysed and managed.
How does it work?
Sotera’s approach to developing a location specific model is to:
- Develop a detailed risk model for each of the relevant system hazard.
- Identifying the relevant locational factors for each hazard, such as equipment design, asset condition, the duty being placed in the system, the exposure of personnel, environmental and ergonomic factors contributing to human error or deliberate violation.
- Breaking-down the system into logical locations (criteria are set for this).
- Rating each of the factors in (2) for each location.
- Determining the relationship between the items in (2) and each model hazard.
- Quantifying the risk for each location.
What are the benefits?
The benefits include:
- ‘Hot Spot’ risk locations and assets are readily identified.
- The importance of each hazard and each location is known, focussing attention on high risk locations, hazards and activities.
- Risk control strategies can be developed and matched to each location based upon risk.
- Additional resources can be deployed in areas that present the highest risk.
- The risk from different assets, operations and activities can be compared and upgrades assessed.
- Areas of good practice and low risk can be identified and the practice rolled-out across the organisation.
- Improved credibility of the risk model with personnel and the regulator as the risks tend to accord better with perception and engineering judgement