Henry Louis Mencken is famous for many things including saying; “for every complex problem there is an answer that is clear, simple, and wrong. Henry was an American satirist and cultural critic who died 1950’s – by all accounts he was free with his opinion and took no prisoners. I suspect he’d be finding easy pickings in today’s political environment. I came across Henry’s quote when listening to an oncologist talking about the complex responses the human body has to various cancer treatments; ‘the human body is a vastly complex biochemical organism’.

Trees don’t have quite so many moving parts as the human body, but I think it’s fair to say trees are also complex biochemical organisms. Of course, trees do not exist in isolation. There is a multitude of separate biochemical organisms living on, in and next to our trees. Those organisms exist in different amounts, in different conditions and at different times, subtlety and/or collectively changing what happens on, in and around our trees. There are also abiotic factors and mechanical forces to consider. It all becomes very complex very quickly and one would be forgiven for getting confused when considering the complexity of it all. Luckily the oncologist had an answer to that as well – although not specifically regarding trees, she pointed out that, ‘those that were not confused, were not paying attention’. At this stage, I became confused and stopped listening to her.

Tree risk assessment can also be a complex problem, not only do you have to consider the tree with its multitude of organisms living on, in and around it, abiotic factors and mechanical forces, you also have to consider the target; where it is, what it is, what’s it worth and what could happen to it in the event of a tree or tree part impacting it. And then, there is the event, could the event actually happen and if so, when? Yep, assessing tree risk can be vastly complex, but luckily there are tree risk methodologies to help us. But which methodology is the right methodology to use – yet another complex question?

A risk assessment is simply the collection and modelling of data to make a prediction, almost every industry and/or activity has at least one method. Jerome Tixier(1) and others reviewed 62 commonly used risk methods used for industrial safety and determined that; ‘there is no one general method to deal with [all of] the problems of industrial risk’. Jeff et al(2) reviewed 12 commonly used risk methods used in the pharmaceutical industry and determined that; ‘each assessment method requires different data and has its unique characteristics and features, as well as strengths and weaknesses’

It would seem that there are good points and bad points to them all. So, maybe there is a type of method that is better; quantitative or qualitative – which one of those should we use?

Quantitative data is information about quantities, information that can be measured. Quantitative data is usually expressed in numbers. Qualitative data, on the other hand, is information about qualities, information that can’t be precisely measured. Qualitative models are usually expressed in words. As far as common tree risk methodologies go we have both types to use. So, which is best?

When it comes to a preferred type of method you’re actually talking about personal preference. A debate about which method is more correct based on how the data is collected and presented is more about human nature than is about the method used. Some people like numbers, some people don’t, some people like cats… Personally, I use quantitative and qualitative methods depending on the wants and needs of the client or situation – sometimes I even use both for the same tree.

So, if no single risk methodology deals with all of the problems and each has as strengths and weaknesses, and the type of method is down to personal preference, what’s the point of using a risk methodology at all? Our next complex question.

As a risk assessor, you need to manage your own risk. By using a recognised peer-reviewed risk methodology you are managing your own risk. You are managing your own risk, by apportioning some of the decision [the risk rating generated] onto the methodology; you add the data, follow the process and the resulting outcome is generated by the methodology not yourself. Of course, the outcome is generated is only as good as the data entered, hence the methodology (and the owner/creator of it) is not actually responsible for your outcome.

But what if you put good data in, follow the steps correctly and it still goes horribly wrong; what if you correctly undertake a risk assessment and failure and impact still occurs? The next complex question.

Exceptional non-foreseen freak occurrences can and do happen, and when they happen, if they are actually outside of anyone’s control, blaming someone is probably pointless, but people love to blame – and blame they will do. By using a risk assessment methodology, the methodology generates the rating – so if you find yourself in the blame game, you could try removing yourself from the equation, and blame the methodology.

With that in mind, the developer and/or owner of the risk methodology needs to manage their risk. Yet more complexity. To manage their risk the developer and/or owner of a risk methodology needs to control the use of their method. To do this the developer and/or owner of the method may choose to train and test, train and not test or not train and not test.

By having users undertake training and pass a test the developer and/or owner can document that users have demonstrated their ability to use the methodology correctly. This is a very tidy way of managing users, but it is not as simple as it sounds. If you are using a test to confirm competency, the testing regime needs to be robust and defendable; i.e. what was tested, how were the questions worded, how was the pass mark generated, how is it marked, what are the conditions of assessed etc. There is a lot of credibility in testing, but there is also a lot of complexity hidden behind it.

A developer and/or owner of a risk methodology could choose the options of training and not testing, or even not training and not testing. Training and not testing or not training and not testing is also a very tidy way of managing your users. By not testing there is nothing to confirm the users were competent to use the methodology in the first place. There less credibility in not testing, but there is also less complexity.

Trees and tree risk assessment can be complicated. Choosing a the best tree risk methodology can be complex but remember, for every complex problem there is an answer that is clear, simple, and wrong. It is OK to be a little bit confused because that probably means you are paying attention and when the time comes to choosing a tree risk methodology, it is unlikely that one single method will do everything, so why be limited to one?

1. Review of 62 risk analysis methodologies of industrial plants. (2002) Tixier T, et al. Journal of Loss Prevention in the Process Industries, Elsevier, 15(4),pp.291-303.
2. A Review of Quantitative Risk–Benefit Methodologies for Assessing Drug Safety and Efficacy (2010) Jeff J, et al [Report: ISPOR Risk–Benefit Management Working Group] – Value in Health 13(5) pp. 657-666

• Written for the ARB Magazine (UK)