22 February 2015

Fear: The Elements of Prediction...

"Just as some things must be seen to be believed, some must be believed to be seen." "...so one way to reduce risk is to learn what risk looks like." --Gavin De Becker

These words from his book The Gift of Fear reminds us of how many people talk about Operational Risk Management (ORM), mitigation and implementing risk controls and don't have any context. In order to truly understand something, you actually have to come face-to-face with it, experience it and feel it.

For every 100 people in your organization, how many are a risk?  By that we mean, the factors are high that an individual will do something or be the target of an incident that causes irreversible harm to themselves and or the institution during their tenure as an employee.

The actuaries behind the insurance you purchase for different kinds of hazards or incidents in the workplace could give you some answers here. How likely is it that this kind of event occurs in this industry over the course of one year as an example? Certainly the ratios are known, otherwise the insurance product would not exist to protect you.

Predictive Analytics and processing of information to predict what has a high chance of actual occurrence is a whole other matter. In order to be predictive, you have to have actual experience and it has to be so innate that it now becomes more than just an intuition.

Some call it "Self-talk" and others a gut feeling but whatever it is, it got there because of your past experience. If it's more powerful than that, now you may just be experiencing something we all know as "Real Fear". You have to realize that when you get that tingle sensation up the back of your neck, you are way beyond self-talk and into a whole new dimension of emotion.

DeBecker's elements of prediction can help us figure out the likelihood of a prediction actually occurring:

1. Measurability - How measurable is the outcome you seek to predict?

2. Vantage - Is the person making the prediction in a position to observe the pre-incident indicators and context?

3. Imminence - Are you predicting an outcome that might occur soon, as opposed to some remote time in the future?

4. Context - Is the context of the situation clear to the person making the prediction?

5. Pre-Incident Indicators - Are there detectable pre-incident indicators that will reliably occur before the outcome being predicted?

6. Experience - Does the person making the prediction have experience with the specific topic involved?

7. Comparable Events - Can you study or consider outcomes that are comparable- though not necessarily identical- to the one being predicted?

8. Objectivity - Is the person making the prediction objective enough to believe that either outcome is possible?

9. Investment - To what degree is the person making the prediction invested in the outcome?

10. Replicability - Is it practical to test the exact issue being predicted by trying it first elsewhere?

11. Knowledge - Does the person making the prediction have accurate knowledge about the topic?
This OPS Risk professional has realized that these 11 elements exist in many of the risk management methodologies and systems experienced over the years. What is remarkable is the degree that we see time and time again, these elements being left out, avoided or just plain not utilized in organizations of all sizes and industry sectors.

It's time that CxO's revisit all of these elements in each of the Operational Risk Management (ORM) systems that are in place in their enterprise. From the front door to the intrusion prevention system, in the HR process from interview to termination and from the training room to the board room.

Predictive Analytics is a science that comes in the form of an art. Make sure you have the people who are masters of the art and experts in implementing the science.

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