Occupational risk control in the eyes of an environmentalist

Dr Mike Mentis

At Xmas 2018 I shook hands with Derek Viner. We’d last seen each other 56 years previously when we finished school. ‘What have you been up to?’ we each asked. Derek started his career as an aeronautical engineer and over time worked his way into occupational risk control. Via my environmental interests I’d invested time in environmental risk control. We’d each written a book on our respective interests. Our modes of thinking also converged in several ways: applying principles, adopting standards, and always doing things to the highest intellectual level.

During our school days Derek had a scholarly aura about him.  In my renewed acquaintance this perception was reinforced. I looked forward to nosing into his book. I wasn’t disappointed. I found the book (Occupational Risk Control: Predicting and Preventing the Unwanted, Routledge, 2016, ORC for short) a treasure.

The principles of risk control are as universal as the laws of physics. It does not matter whether one is building bridges, digging for diamonds or managing elephants, you need to identify and understand the risks, assess the extent to which damages or losses might affect you, determine whether control is warranted, if it is warranted how you can control, control, and then watch what you are doing. I know of no other single work that is as encompassing, generic, and thorough in its explanations of risk control. Every page is erudition. Save repeating the whole book, it must suffice here to pick a few gems, and of course the ones that particularly catch the attention of an environmentalist.

ORC defines a risk as an uncertainty that an adverse consequence (of a given size) will occur. There are words in this definition that carry special weight. First, there must be uncertainty. There is no risk when the outcome is known with certainty. It’s then simply a management issue. The sun will set tonight. If we are working night-shift, we will need lighting – not a shadow of doubt.

A second matter is that the consequence is adverse. Some people regard uncertainty about a beneficial outcome arising as a risk. However, this is unconventional in both popular and technical talk. One does not hear about ‘the risk of winning the lotto’. This is not to deny that beneficial outcomes can happen, yet in the real world the management focus is not on the benefit per se, but on the constraints or obstructions that might prevent its realization. One is reminded of Goldratt’s allegorical bestseller, ‘The Goal’. Completing the schoolboy hike on time requires chivvying along the slowest-moving schoolboy. Put him in front and have the rest of the group attend to his every need, to ensure he keeps moving. At the factory it’s the same. Find the bottleneck, and ease it to squeeze out the best possible production rate. In life generally, if you want to do something, find out what might stop you. It is in the possible obstructions that the uncertainties and risks lie and on which interventions are imposed, not in the achievement itself. If my car won’t start it doesn’t get me to work to fill the already half full fuel tank when the battery is flat.

A third issue about the definition of risk is consequence ‘of a given size’. ORC explains a common pattern of higher frequency of low- than high-consequence events. For example, many slips or trips on the stairway result in no lost time injury, occasionally broken bones, and only rarely a fatality. Yet this pattern is not universal. There is no single fixed relation between the high-frequency low-consequence and the low-frequency high-consequence events that might permit the one to be predicted from the other. While the stairway might typify many situations, a low-consequence dam failure is less common than the high-consequence case.

Of interest here is discussion in ORC of common resort to lost time injury frequency rate (LTIFR) or similar measure. The majority of these data relate to minor incidents, and organizations attach importance to changes in LTIFR using the data to index overall company safety performance. Management fretting about even the tiny detail might look like caring about safety and, by extrapolation, applying controls to avoid the high-consequence events. However, ORC points out, without any established relation of the frequent low-consequence and the high-consequence events, the validity of caring about safety and thereby preventing the big disasters is in doubt. As a parallel, if market crashes were to be predicted by applying normal statistics to daily market share price changes, then the 2008 global financial crisis is so improbable as to be unlikely since the Big Bang. Yet global financial crises happened not only in 2008 but on many previous occasions. Normal statistics doesn’t enable financial market crashes to be foreseen or their frequency predicted. What does enable prediction? Among the problems with extreme events is that there are few data on which to build and test predictive models. Extreme event theory is fascinating stuff, but it must suffice here to support ORC’s point that ‘look after the pennies and the pounds will look after themselves’ is not enough. Monitoring the pennies might tell nothing of the fate of the pounds.

ORC has a chapter on identifying and describing risks. Plainly, it needs to be known what could happen, and by what mechanisms, if effective risk control is to be applied. Environmentalists are sorely in need of this. In the typical environmental impact assessment (EIA), impacts (not quite the same as, but similar to, risks) are arrived at somewhat incidentally. They are ascertained as a combination of what individual specialists suck out of their left thumbs (usually no method of identification described) and what stakeholders are concerned about. This identification process is more happen-stance than a deliberate and systematic assessment of the project to detect possible damages and losses. The upshot is that current EIA practice does not conform to science which requires a method described to the degree that it can be repeated and yield consistent answers. Nor is current practice likely to stand scrutiny if it were cross-examined in a court of law. What EIA needs is methods such as those that ORC describes: an energy damage model (EDM) and a threat vulnerability model (TVM) to use in risk identification and description. In the physical world things happen because of release, loss, transfer, gain, receipt or absorption of energy of one form or another. So where in the project do energy transfers take place? The project must be combed systematically to identify the energy sources, transfers, losses and receipts so that potential damages might be recognized. Of course, not all impacts, and their attendant risks, are energy-based. For example, losses can arise from corruption or theft. Hence ORC’s TVM. Again, the principle is to work through the project systematically to identify the threats, the vulnerability pathways and the assets that might be affected.

Above it was mentioned that in relation to a single aspect there can be incidents with a range of outcomes or consequences. The fact of the range, and common lack of awareness of it, is perhaps a main contributor to divergent views on the significance of any given risk. For example, most people might consider incidents on the staircase trivial, but for the few that have experienced a highly consequential fall, a staircase is a hazard. ORC urges bracketing the range with recognition of a likely least consequence (LLC) at the lower extreme and a likely worst consequence (LWC) at the upper extreme. On matters where copious data exist (eg a staircase) it is feasible to construct a frequency-consequence diagram that typically would show high frequency of incidents with no or low consequence, and low frequency of highly consequential events. But often, not least in the environmental field, there are insufficient data to construct the frequency-consequence relation. There are many reasons why extrapolating from low-consequence data is unreliable – fat-tailed distributions (rare events more frequent than normal statistics predict), non-linearities (beyond a threshold the system flips into a different mode of behavior), event-driven (system changes only upon big events), idiosyncrasy or lack of stationarity (every system is unique with different mean and variance), and so on. This is risk. Things are uncertain. How might we proceed?

Consequences of events are easier to understand than their probabilities. So, having identified the risks, why not focus on the consequence, in particular LWC? As ORC says repeatedly, if a thing can happen, it will. It is only a matter of when and where. Plainly some damages and losses are so severe as to be unaffordable, even if the chance of them happening is low. An airliner crash is an example. The reputable airline companies will do ‘everything’ to prevent a crash, regardless that the chance of a crash is tiny. Their fanaticism about this has transformed the dodgy Kitty Hawk into a reliable Boeing or Airbus that, with the risk averse crew, is the safest form of travel invented. Another example is car travel. The chance of accident on any single trip is remote. However, over a lifetime the small chances are additive, so over decades of traveling you are likely to have an accident. But you don’t know when or where. The prudent thing to do is always to buckle-up and drive safely.

The take-home message is that your assessment must focus on the risks with high LWC, and those that the law requires you to control. Possible consequences might not be difficult to foresee, though probabilities are bound to be hard to estimate. Nevertheless, you need to apply controls for these LWCs. Perhaps you cannot fund all the necessary direct controls. Maybe you can transfer risk for some of them by taking out insurance. Even then there are likely to be a host of risks that you can’t manage. You have options. You can accept these risks, hopefully they are only ones with low LWCs, and put in place surveillance to detect if and when the unwanted arise, and preparedness to address when they do arise. If this isn’t realistic then consider redesigning your business or shutting down. ORC can guide you through all this, whether you are building bridges, digging for diamonds or managing elephants.