|
After a train collision in June 2009, the National Transportation Safety Board (NTSB) found that among the causes were a flaw in the technology chosen to operate the system and the organization’s inability to institutionalize processes that would aid management in making decisions that could have helped to minimize or prevent this accident.
Our industry has smart people with the right intentions. So why does it appear that they are not using safety in their day-to-day decisions? In my experience, this disparity happens because of two reasons: (1) organizations have financial limitations and (2) safety is usually thought of as “code,” thus management does not have a mechanism to understand how individual parts of a transit system and day-to-day decisions affect safe operation other than by experience.
The first reason is obvious. All organizations have financial limitations; it is what causes us to have to make decisions. The second reason is more complicated because we need to change our safety paradigm from code-based to systems-based—particularly as the system becomes more complex.
Hienrich Model
In the 1930s an insurance investigator named Herbert Hienrich developed an accident model that took into account five elements: the social environment, person, hazard, accident itself, and subsequent injuries. Like dominoes, each of these elements had to be lined up to result in an injury. Conversely, the removal of any element would prevent injury. In the 1950s, Frank Byrd, an industrial safety expert, noticed that nearly 80 percent of all industrial accidents were caused by management decisions. In adapting Hienrich’s model, Byrd developed the following loss (Fig. 1) causation model, which stated that substandard management systems or decisions could lead to losses.
To make good decisions, we need to fully and quantitatively understand how hazards manifest themselves in the highly technical and multifaceted environment of the modern transit system. More importantly, we need a mechanism to tie improvements in safety to financial considerations because, after all, money is finite—and there needs to be a way to determine which choices make our systems as safe as is reasonably practical. Fortunately, there is a way to do this: it is called quantitative risk analysis (QRA).
QRA is a complicated way of saying that we figure out what our hazards are, how often they happen, and figure out the impact. The process of QRA, when applied to a project or change in the system, looks like Fig. 2. By quantifying the risks into an easily digestible number, managers have an easier time of determining if risks are acceptable by organizational policy. Also in the grey areas where it may meet policy but determinations must be made between two options, QRA can be used to determine which is safer. Further, by applying a cost value to this safety, with the help of either the organization’s policy or insurance actuary, a determination can be made on whether or not the better solution is worth the expense. This process helps managers select the solution with the lowest hazard value as is reasonable (As Low As Reasonably Practical or ALARP).
In an operating environment, this model can be monitored and adjusted to actual conditions on a day-to-day basis. With input of not only accident records but also maintenance records and configuration changes, these issues can be brought to the immediate attention of management before they become statistics for the NTSB. Using modern IT, we can even create dash boards or service level agreements for contract operators. Any number of things can be done to provide smart managers with the right tools to make good decisions.
For Consideration
A final thought for consideration. As the number of experienced transit managers goes down (a direct result of Baby Boomers retiring), and the level of technology goes up because companies are always progressing, and finally—and as our budgets and state of good repair continue to decline in our continued economic slump—won’t our increasingly complex transit systems need such a methodology?
|
|
|
|
Figure 1 Illustrates substandard management systems or decisions as factors in loss. |
Figure 2 - Quantitative Risk Analysis |
|
