# via Uncertainty

Have you ever experienced uncertainty? I think most of us have, except those lucky souls who can control/manage future through quantifying mathematical equations, generally referred as risk managers. Uncertainty is a state of being unpredictable, volatile, stressful, random, disorderly, unstable, summing up into everything which moves us away from our comfortable state of thinking linearly. It’s not just absurd, but devastating to think you can predict events using perfect market phenomena of rationality, erroneously assuming cause and effect to have measurable, proportional and defined and operating auto correcting itself to equilibrium.

Uncertainty is overtly misused by managers to justify adverse deviations from expectations. Most of such deviations are a product of planning fallacies, a phenomena where a manager deliberately overestimates success and underestimated adverse outcomes, often accolade and celebrated as overconfidence.

So how do we define uncertainty and is it measurable?

As described in the first few lines, uncertainty has many forms and various words can be used to describe it. I find the word “nonlinear” helpful in linking words used earlier i.e. unpredictable, volatile, stressful, random, disorderly, unstable etc. Nonlinear events cannot be measured with certainty, linear events can be measured. An oversimplified definition of linear relationship is when input have a proportionally measurable relation with output. This can be plotted as a straight line, and although I find it a very romantic system, it’s unusable. Absence of this dramatic linear relationship causes uncertainty.

If you ask about uncertainty from a sophisticated(traditionalist) risk professional, say John, he will quickly draw a convincing graph, something like the one illustrated below;

As you become less intrigued with complicated relationships and colors, you can ask John to explain how this “awe-full” matrix is used to measure uncertainty. John’s will show you how to plot an event’s likelihood on its x-axis and impact on y-axis based on your’s (or John’s) best judgement, and taking the product (of x and y axis) to measure an event’s riskability.

There is a fundamental flaw in John’s explanation which is referred a few paragraphs back in relation to non-linearity of events. John is trying to predict a future event’s riskability using linearity i.e. he is estimating risk level of an event assuming a constant likelihood and impact. Consequently John’s technique mostly end up in colors which remind us of danger, traffic lights, and accidents.

Let’s test john’s technique in an a daily life activity. If you drive, and pay attention to details in environment, you would find many colorful tail lights, which are brighter at night. Yet accidents happen. Those who have had this unfortunate experience can tell you that the event was out of their control and unavoidable. How will you determine risk of an accident using John’s technique? The moving traffic is exemplified as an uncertain event, especially in Riyadh, and using John’s risk ranking system by estimating likelihood and impact of an accident can be done momentarily, and in the exact next moment environment changes (randomness), should be avoid while driving.

Non-linearity is central to understanding and managing uncertainty. Determine what are the stressors that will cause a breakdown (non-linear event), and degree of their effect on changing existing stable condition. It can be used to measure effects of uncertainty on target systems, assets, products, processes etc. Non-linear events can be scaled up to test cascading effects of breakdowns. This will provide you specific and detailed input on treating effect of uncertainties (non-linear events).

Let’s test this using earlier example of driving, the difference is not subtle it’s a different system. Instead of estimating risk on the objective, using likelihood and impact, we will test effect of stressors through variability on objectives. You tend to drive fast and carelessly with less traffic on road, why? You see the environment with less uncertainties (stressors), which provides you with feedback that you could do more (within allowed speed limits of course), without causing an accident. The stressors will tell you how much uncertainty (stress) can your system accept as traffic increases, the feedback system would advise you to manage uncertainty by taking corresponding actions i.e. driving carefully, moving to slower lane or taking an alternative route.

I hope you apply this in your work and find it useful in understanding risks, btw I used the example of driving as it quiet closely resemble to strategy and also involves various processes including decision making, efficiency, risk in reaching a specific destination (objective). One more thing, John’s technique has a different purpose, which is hazard management, but does not work effectively with uncertainty.

(Opinions expressed are solely my own and do not express the views or opinions of my employer).

Idealism the highest truth which we must lack to be human

Idealism the highest truth which we must lack to be human