In 1931, HW Heinrich published his findings from a review of hundreds of thousands of safety incidents. His data showed that on average, for every 300 near-miss events without injury, there would be 29 minor to moderate injuries and 1 major injury or fatality. Similar studies done since 1931 have yielded similar results. The data is deceptively, compellingly simple -- the meaning, however, is not. What is implied by a 300:29:1 ratio of near-misses to moderate injuries to major injuries? Why do we care? Is there some deeper, underlying pattern to this data?
The late Per Bak wrote an interesting book that might yield some insight in this area. Titled "How Nature Works: The Science of Self-Organized Criticality," (1996) the book provides an easy-to-understand, hard-to-stop-reading account of research into the nature of complex systems. In a nutshell, the theory states that systems of many types may evolve themselves (self-organize) to a state susceptible to disturbance (at, or near, criticality). When a disturbance does occur at this state, an event ensues -- and the magnitude of this event is determined by the state of the system, not the nature of the initial disturbance.
This sounds profound, but what does it actually mean? Consider a simple example: you are working on a platform some twenty feet above the floor, and you accidentally drop a hammer.
- The hammer falls, bounces once, but doesn't leave the deck of the platform.
- The hammer falls, bounces off the deck of the platform and over the edge. No one was working below the platform, and the hammer falls harmlessly to the floor.
- The hammer falls, bounces off the platform, and strikes a worker below you. Luckily, she was wearing a hard-hat, which protected her from serious injury.
- The hammer falls, bounces off the platform, and strikes a worker below you. He had just taken off his hard-hat to scratch his head. He receives a serious injury.
- The hammer falls, bounces off the platform, and strikes a worker below you. The worker, having taken off his hard-hat, is stunned by the impact and stumbles backwards into a high-voltage electrical panel. The panel was supposed to have been de-energized for personnel protection, but there was a miscommunication with other workers and another panel 10 feet away was de-energized instead. The worker is electrocuted.
This example is somewhat contrived, but it illustrates the point: the same initiating event can result in several different outcomes, and the magnitude or severity of these outcomes are dependent entirely upon the state of the system. Furthermore, as the potential severity increases, the probability of an event occurring with that severity decreases. Heinrich's data (300:29:1 ratio of near-misses to moderate injuries to major injuries) now makes perfect sense.
Note that the above says nothing about the underlying causes for events of varying magnitude. Considering the example above, its evident that the causes of high and low severity events initiated by the same disturbance might be completely unrelated. This stands in stark contrast to the conventional viewpoint of Heinrich's data promoted by many Industrial Safety professionals, namely that the root causes are the same for an event yielding potentially different outcomes.
It now seems clear that in order to limit the frequency of events (of any severity), it is necessary to correct immediate behaviours and conditions that lead to event initiation. However, it is equally important to correct underlying, systemic, root causes in order to limit event severity. A safety management program that does not do both is a program that will never achieve substantial improvements in worker safety.
by Bill Wilson