The Level of Math in Risk Management March 28, 2015Posted by Edwin Ritter in Project Management.
Tags: decision matrix, decision process, decision theory, known unknown, risk, risk management, uncertainty, unknown unknown
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Managing risk and selecting the best mitigation choice can be hard. There are many factors that will influence what choice is selected. Using data to manage risks and assess choices is always good. Having a process to use that data to evaluate choices is better. Having good data to assess risks and a process to determine choices is the point of this post.
Some background first. Decision theory is a complicated subject and is used in many different fields in business and leisure (i.e. – games). There are 4 basic elements in decision theory: acts, events, outcomes, and payoffs. A formal definition is “the mathematical study of strategies for optimal decision-making between options involving different risks or expectations of gain or loss depending on the outcome.” An informal definition of decision theory could be “identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision.”
Got that? Good. Sorting out between what is known and unknown can assist in which risk mitigation choice is best. It is always preferable to be in the magic quadrant and deal with knowns rather than unknowns. Consider these groups in a matrix:
- Known Known – circumstances or outcomes that are known to be possible, it is known that they will be realized with some probability.
- Known Unknown – circumstances or outcomes that are known to be possible, but it is unknown whether or not they will be realized. This is known as a Risk.
- Unknown Known – circumstances or outcome a modeler intentionally refuse to acknowledge that he/she knows.
- Unknown Unknown – circumstances or outcomes that were not conceived of by an observer at a given point in time. This is known as an uncertainty.
In short, those things we know we don’t know are risks and those things we don’t know what we don’t know are uncertainties. In the magic quadrant, both are below the line.
Still with me? The uncertainties, the unknown unknowns, are the hardest pieces to deal with. With decision theory, assigning values of probabilities helps determine which choice is best. As an example, consider the following image. Getting the data to assign the options and organizing into a concise arrangement is where the math comes in.
Not all risks require this level of math and analysis to determine the best mitigation choice. The level of math should be appropriate to the complexity of the project and the potential risks involved. It is worth noting that the difference between an issue and a risk is :
– an issue is something that has occurred which impacts* the project.
– a risk is something that may or may not occur that can impact the project.
* impact can be positive or negative.
I prefer to stay above the line and deal with knowns and those risks that are relatively small on my projects. It makes for simple math and for projects where my preferences matter, I find those are the best projects to manage.
Glad I did not lose you and you got this far. How do you manage risks? What is the level of math required for risks? Simple? Complex? Hybrid? Comments invited.
Ruminations on Risks and Black Swans March 10, 2012Posted by Edwin Ritter in Behavior, Project Management, Trends.
Tags: black swan, danger, extreme impact, investment, risk management, risk tolerance, risks, uncertainty
Whatever we do, we deal with risks. Despite our best laid plans and intentions, there are always those uncertain and unwanted events that happen which are beyond our control. In a previous post, I talked about risks on projects. This post deals more with risk behavior. Risk management (or, risk tolerance) covers the spectrum from total avoidance at all costs to a laissez-faire, what-does-it-matter attitude. A low risk tolerance leads to ‘safe’ choices that eliminate, or substantially reduce, an unlikely event with a negative impact occurring. Likewise, a high risk tolerance leads to choices where outcomes are unpredictable and not guaranteed. In this scenario, the chances for unlikely risks occurring are higher. Financial investors know their level of risk tolerance and how it influences their investment choices.
There is a related effect with investors called the ‘Black Swan‘ that describes what happens when a uncertain, unstable event does occur. In a 2007 book by Nasim Nicholas Taleb, titled ‘The Black Swan – the impact of the highly improbable‘, it is defined as :
- an event that is unpredictable (an outlier),
- has a massive or, extreme impact and
- after it happens, we create rational to make it more predictable (less random).
Taleb makes a living betting on the occurrence of Black Swans. He is a contrarian when compared to the typical financial investor who avoids risk by seeking the small gains in the stock market. The positive effect of a Black Swan is seen over time. Likewise, a negative Black Swan happens very quickly. For most investors, the preference is to avoid the downside risk of a negative Black Swan. Managing risk can be a tricky business. Taleb has 2 observations related to risk assessment I want to highlight:
- We have more confidence in what we know is wrong than in what we know is right.
- We over-estimate what we know and conversely, underestimate our uncertainty.
The first point bears repeating. We are more certain about something we know is wrong. Our intuition, skills and experience tells us what is wrong. Sometimes, we know something is wrong when we see it. That confidence drives our behavior with money, work and our personal life more than we may want to admit. I think that is because we are better at dealing with failure than success. We plan for success, of course, but realize we have to deal with a minimal level of failure.
The other facet on uncertainty I have seen at work many times. Providing accurate estimates is a skill built on experience and dealing with knowns. When faced with new challenges, it is tempting to minimize complexity. How hard can this possibly be? More than likely, it is harder than you are able to imagine at this point in time.
When a risk is deemed highly improbable, we tend to not spend much time and energy thinking about it. When a negative Black Swan strikes, the risk mitigation(s) you have defined will be quickly tested. If your tolerance is low, you will have well thought out and documented options. Your sponsors, stakeholders and clients will benefit from and appreciate your efforts. The path forward that is selected is based on their risk tolerance of those negative Black Swans. Positive Black Swans can only make things better, right?
What’s your risk tolerance? What method(s) do you use to deal with uncertainty?