Time to Act
Charlie Goodrich 
Hello,

 

Risk and Uncertainty, while often used interchangeably, are not the same thing.

Today's newsletter explains the difference and offers several practical lessons and suggestions for applying this in your work.
 
I appreciate your comments. Just click "reply" to send them to me.

 

Regards, 

 

Charlie
Charlie Goodrich 

Founder and Principal

Goodrich & Associates
 
 
June 2014 Vol. 3 No. 6
 
 
In this issue...
Risk Vs. Uncertainty, And Why the Well-Prepared Business Person Needs to Understand the Difference
Heard on the Street
About Us
 
 
 
Goodrich & Associates
in[email protected]
www.goodrich-associates.com
781.863.5019
 
Risk Vs. Uncertainty, And Why the Well-Prepared Business Person Needs to Understand the Difference

In 1921, renowned University of Chicago economist, Frank Knight, published his now classic book, Risk, Uncertainty and Profit. In that book, Knight drew an important distinction between risk and uncertainty, one that previously had not been recognized in economics.

As Knight explained:

The essential fact is that "risk" means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; . . . It will appear that a measurable uncertainty, or "risk" proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all. We shall accordingly restrict the term "uncertainty" to cases of the non-quantitive type.

In other words, "risky" refers to events with measurable frequency and therefore, predictability. Uncertain events, on the other hand, are those whose frequency can't realistically be measured and which are therefore inherently unpredictable.

This distinction is not just academic - understanding the difference in business can lead to far better decisions. It is also one of the foundations of Deming's Total Quality Management (TQM) approach, as I will explain later.


The uncertainty of war

When I was in the rent-a-car business, back in the early 90's, forecasting demand, the amount we could charge for our cars, and the number of cars needed was critical for success.

Fortunately, there was both strong seasonality and strong correlations with the moving average for the last several months. We could predict, with reasonable certainty, how much to charge and how many cars we needed to have on hand to make a profit. There was some risk of variation, of course, but within that range, we could develop flexibility in our fleet of cars to adjust supply as needed. These were risk-based calculations.

What we could not predict or plan for was the Gulf War and the ensuing recession that turned crowded planes into empty buses, few people to rent our cars and crashing prices. The war and its fallout were uncertainty.


Practical lessons learned

What's it mean in practice, for your business? Some lessons learned:
  1. Don't waste time trying to predict the odds of something whose frequency can't be measured, hence predicted.

    This is one cause of paralysis by analysis: postulating expected frequencies of outcomes when there is no basis on which to do so. The odds of a location on the East Coast getting nailed by a hurricane, for example, are predictable. Hurricanes have been recorded for a long period of time, they happen with some frequency and so odds or risks can be assessed.

    But, the exposure of the same East Coast location to a tsunami? Well, that is a different beast. Known tsunamis on the East Coast are exactly none ... but, like a war, they could happen.
  1. What may be uncertain and hence unpredictable to you may be a predictable risk to others with a larger data set.

    More experience is a larger data set. For example, the creditors or investors of many of my distressed clients are often surprised as events unfold. However, for me, having been through many similar situations, there are obvious tell-tale signs, many of which are quite measurable (see my October 2013 newsletter on financial ratios for more on what some of these are). The vantage point of greater experience allows for better prediction.

    Increasing the time frame also increases the data set. The deleveraging of economies, for example, as the United States has been experiencing since 2009, happens in 30 to 100 year cycles and hence is a predictable risk in the larger sense. If we only consider the most recent 20 years of economic history, on the other hand, none have happened, so they are an uncertainty.
  1. There is a difference between predictable variation and unpredictable variation (a spin on Knightian uncertainty).

    In the words of TQM guru, W. Edwards Deming, "common causes" are the normal, measurable variation in a system and "special causes" are those which have not been observed or measured before. If an observed variation is within the normal bounds, then nothing is unusual. Otherwise, the observation is a noteworthy exception. (Interestingly, this applies to patterns in social behavior in an organization too, but here the measurements are far less precise.)
  1. While risk can be transferred - because it is measureable and diversifiable - uncertainty is difficult to transfer, because a potential transferee will have trouble diversifying and managing the risk.

    You can buy hurricane and flood insurance for a building on the east coast. But good luck buying tsunami insurance (and if you do, good luck collecting on it).
  1. "Black swans" - Donald Rumsfeld's "unknown unknowns" - are a subset of uncertainty. Obviously, what you don't know, you can't predict.

Some tips to heed going forward:
  • Step back and ask yourself if the potential event is truly predictable. What is the basis for predicting it?
  • Don't limit yourself to your own data set. Talk to those with a bigger data set, including experts, greybeards in the organization, etc. Extend the time frame of the data set when possible.
  • Go with Big Data (or at least bigger data). Today, in the rent-a-car business, pricing is driven by statistical models and changes very quickly. The high-frequency trading that Michael Lewis writes about in Flash Boys, is based on sophisticated risk predictions using massive data sets and complicated statistics. How can you take advantage of this too?
  • When you are dealing with true risk, collect the data and really be able to measure it. In business, this means tracking meaningful data.
  • Keep reserve resources to cope with uncertainty, be it capital, liquidity, people, etc., as not all needs can be predicted. Lehman Brothers and Bear Sterns may have had adequate capital for the risks they took on. But, they lacked capital to cover the uncertainty of a bubble bursting and the subsequent deleveraging.
Overall, remember Frank Knight's near-century old insight and make sure you understand the difference between risk that is measurable and uncertainty that is not. Then make good decisions accordingly.

Heard on the Street
There has been much talk about the high number of students with loans and the high amount of debt many of these students have. But what are the facts?

Alexander Monge-Naranjo, Research Officer with the Federal Reserve Bank of St. Louis, has found that deferment or forbearance may be masking the true student loan default rates in recent years. 

You can read his short article on the subject, here.


About Us
Goodrich & Associates is a management consulting firm. We specialize in helping our business clients solve urgent financial problems. Our Founder and Principal, Charlie Goodrich, holds an MBA in Finance from the University of Chicago and a Bachelor's Degree in Economics from the University of Virginia, and has over 30 years experience in this area.


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