Home > Risk > Thoughts about risk analysis

Thoughts about risk analysis

I have been asked to post excerpts from my new book. It devotes a lot of space to the discussion of risk analysis, including risk appetite, tolerance, and criteria (including why I acknowledge the need to understand risk appetite, while definition of risk criteria is crucial to intelligent decisions).

These are from the chapter on risk analysis:

A single number for level of loss does not enable effective decision-making when one of the possibilities is unacceptable but the calculated overall level appears ok.

A [more complex] example is when there is the potential for (net) gain as well as (net) loss. Consider a situation where management is considering bringing a new product to market. Let’s say that break-even will be achieved if sales reach 10,000 units in the first quarter and the likelihood of different outcomes is estimated as follows.

  • 10% likelihood of 5,000 or fewer sales – net loss of $300,000 or more
  • 25% likelihood of 5,000 to 10,000 sales – net loss of $100,000
  • 20% likelihood of 10,000 sales – break-even
  • 20% likelihood of 10,000 to 15,000 sales – net profit of $100,000
  • 25% likelihood of more than 15,000 sales – net profit of $200,000 or more

You can use models ….. to help calculate the likelihood of each of these results. Some (especially for financial risk) might use a model to put a single value on the range of potential consequences.

But, does it make sense for management to look at a single number[1] (+$15,000 if you take the sum of the P X I calculations) when deciding whether to go ahead with the launch? I believe a world-class organization would make its decision by considering all the possibilities. Is management willing to take the risk of a $300,000 loss because of the potential for a $200,000 gain? Does it have the liquidity to sustain such a loss? Does the potential for reward justify taking the risk of a loss? That decision can only be made intelligently when all possible outcomes and their likelihood are understood.

By the way, ‘traditional’ risk management only considers the downside. That is not helping management make intelligent decisions, as is readily seen in this example.

Another problem with trying to put a single number on the level of risk is that the calculation of P X I ignores other attributes of the risk, such as the speed of onset, duration, and so on.


World-class organizations understand that if they are to make intelligent decisions, all relevant information about a risk needs to be obtained in the analysis phase and considered in the risk evaluation phase. The level of risk is not a single number; it is the composite of all information necessary to make an intelligent decision about whether to accept the risk and, if not, what action to take.

I always welcome your comments.

[1] Martin Davies of Causal Capital has an interesting perspective. He says that “Risk practitioners who evaluate risk as a single number will miss the shape of uncertainty”. A December 2014 post, http://causalcapital.blogspot.sg/2014/12/the-shape-of-risk.html, explains.

  1. June 19, 2015 at 5:26 PM

    Norman, this makes a lot of sense. The additional questions you ask are the right ones. Does your book discuss how to get those on the table consistently as part of decision making? Looking forward to reading your book.

  2. DavidJ
    June 21, 2015 at 12:00 AM

    Based upon the definition of risk as the “effect of uncertainty on objectives”, and the difficulty of expressing uncertainty as a single number (which implies a higher degree of certainty) then I believe we must consider the overall shape and interaction of each risk-factor in the decision-making process.

    Tender and bid management is a good example for me. If there are likely to be five bidders (already we have uncertainty as to how many bids will be submitted) then simplistically my bid has a 20% chance of winning. My focus is on ways in which I can better understand my prospect’s business objectives and that organisation’s risk associated with any one of the bids in an effort to significantly increase my probability of winning the business. Given the opportunity cost of responding, I would not bid with a 80% probability of losing.

  3. Gary Lim
    June 21, 2015 at 8:04 AM

    The table presented is a very subjective, it can be anything the person in charge wants, of course there will be justifications for the table. In a competitive market, there are so many variables which would make the table unreliable or unattainable, again PIC will give the explanations.

  4. Donelle
    June 22, 2015 at 6:25 AM

    This is an an excellent analysis and example of Risk Appetite; and the ability to make risk intelligent decisions. Eventually targets created will drive those
    at the lower levels.

  5. June 23, 2015 at 11:11 PM

    Norman I enjoyed the read, some decision makers have an intrinsic ability to be more analytical than others, resulting in more effective decision making processes. I am of the view that most of us may have a blindspot, things that we do not consider. How do we bring more objectivity in risk management processes?

    Example used on tenders above. There is a level of uncertainty on the number of prospective bidders that will respond. HOW do you improve your risk assessment and analytical processes in absence of the level of uncertainty?

    Practical, not all entities requesting tenders will have compulsory briefing meetings or allow you a list of the number of possible respondents. In economic challenging times we see more and more service providers trying their hand at almost everything. How would you as a business owner manage the risk of responding/not responding to a tender opportunity and estimate your likelihood of success in the maze of uncertainty?

  6. June 26, 2015 at 9:37 AM

    Norman, you are absolutely right that risk should not be reduced to a single number. But the problem is not with numbers and modeling, it is with human behavior.

    If the management team thinks of risk analysis as a compliance burden, they are unlikely to consider more than one number. And if there is no rigor in the data, then the shape of uncertainty will be prone to subjective massaging according to whether an individual manager wants to push ahead with a project, or to block it.

    The way forward is for large businesses to employ impartial statisticians much like governments employ impartial statisticians. However, debates over economic policy show that even the most impartial statistics can be subverted…

  1. June 25, 2015 at 6:04 AM
  2. July 1, 2017 at 9:41 AM
  3. January 17, 2020 at 1:25 PM
  4. August 25, 2020 at 8:45 AM

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