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News and thoughts. Read at your own risk!

Corporate world vs startups/small business vs public sector

29/1/2020

 
Commenting on something broader than risk. See it on LinkedIn.

Laugh or cry?

29/1/2020

 

Sometimes a risk consultant doesn't know whether to laugh or cry. Or both.

"This is to inform you that we have suspended our RFP for the project [Framework and pilot for comparison and prioritization of identified risks]. We do not have sufficient budget at this time to mitigate any risks that might be identified as priority, and so have been instructed to not prioritize them. [...]"

Etymology of probability

9/3/2019

 
The word "probability", in English as well as in Romance languages, comes from the Latin verb "probare", which means "to test or inspect" (it also can mean to prove/demonstrate, or approve, but that seems to be in different contexts).

In my mother tongue, Czech, the word is "pravděpodobnost", meaning "similarity to the truth", probably inspired by the German "Wahrscheinlichkeit", the property of giving the appearance of trust, or being likely to be true. I am told that in Hindi it is, "संभावना", more about chance or possibility than verifiability or truth.

As I work with clients around the world, I'm not sure there's a clear correlation between cultural background and the natural preference to consider probability from a frequentist of subjectivist perspective, but I'm pretty sure linguistic connotations matter.

Surviving and thriving as an independent professional...with some hilarity

19/1/2019

 
A while back, I did an interview for Will Bachman's Umbrex podcast, "How to survive and thrive as an independent professional". He's recently kindly posted a transcript, which includes the transcriber's well intentioned but hilarious mis-hearing. My book project, "Be Your Own Risk Manager", got turned into "Veer On, Risk Manager!" -- which some would say is a pretty accurate verb for risk management, especially around the 2008/2009 crisis. Cynics would say even now!  Full transcript below.
unleashed_interview_transcript.pdf
File Size: 185 kb
File Type: pdf
Download File

Two conference presentations this month

2/1/2019

 
Happy New Year; had a busy fall and I see I didn't get around to posting.

Two upcoming conference presentations this month, in both of which I'll focus on parallels between the private and pubic sectors with an emphasis on risk management on organizations that straddle that dividing line in terms of governance, and therefore decision processes and risk appetite.
  • January 18, Canadian pension funds' risk managers' roundtable (invitation only, organized by the CPPIB), Toronto. I'm presenting on "hard to measure" risk, focus on macroeconomic and geopolitical investment risks.
  • January  22, Risk management for the public sector, Ottawa. Panelist on risk management transformation programs; lessons learned from such programs at public and quasi-public institutions around the world.

Risk management as a public relations "on message" exercise?

3/7/2018

 
The request was innocuous and not atypical. Can you help our company develop risk reporting, and put in place a "small risk function" to drive it? Sure, mature risk organizations frame their raison-d'être more broadly, but many successful risk programs have as their genesis a request for better risk reporting.

However, further detail (through an intermediary) was not encouraging. The risk function was to organizationally report to the head of public relations, so as to stay "on message" with stakeholders. Not exactly what a risk professional brought up on a diet of risk management independence, three-lines-of-defense is keen to hear. I nearly declined to initiate discussions, suspecting strongly this might be a perversion of risk management into risk whitewashing instead.

​But, a couple of conversations later, we're reshaping it into something that does make sense. It's a company that has been stuck in deterministic, head-in-the-sand, don't-ask-don't-tell thinking. Stakeholders are getting restless, and when they're not getting good answers to their risk-related questions, supplying their own, less-than-perfect answer. Not clear yet if there is a professional collaboration to be had, but we've progressed to a much more mutually satisfactory conversation about how to pragmatically start having a top-management-and-stakeholders dialogue about risk, not focused on staying "on message" but instead broadening the message. For me as consultant, it's a good lesson in humility. Just because the initial framing of the issues rubbed uncomfortably on some core tenets of risk management as conventionally framed doesn't mean there isn't a meaningful opportunity for better engagement with risk and uncertainty.

Estimate ranges: avoid the "if all you've got is a hammer..." syndrome

26/2/2018

 
[Another excerpt from my book. A bit unpolished, but sharing as-is since I've seen several companies falling into this trap recently. Footnotes have ended up just pasted in smaller font with FN: before them]

In [a previous section, not included in this excerpt], we discussed the usefulness of considering a range of expert opinions — predictions, if you will — for important drivers of uncertainty in your business. We also discussed the benefits of bringing experts together, and engaging in a dialogue about the rationale behind their opinions. We even discussed formalized techniques where the dialogue is interspersed with iterative polling, to see whether the discussion increases consensus or hardens into concrete lack of consensus that can underpin useful alternate scenarios to consider.

Unfortunately, there is the old saying, “if all you’ve got is a hammer, everything looks like a nail”. Thoughtful executives who decide to bring probabilistic thinking to their decisionmaking routinely tend to abuse expert polls like this to bootstrap a probabilistic range in a flawed way.

Consider the example in the following table, showing the range of near-term Canadian to US dollar exchange rates forecasts published by major Canadian banks in late February 2018. These numbers represent the expected (or in some cases, most likely) exchange rates from the banks’ models, which are often quite complex and based on various macroeconomic, financial (e.g. interest rate), and momentum/sentiment-driven indicators the banks monitor or predict as well. 
​
Bank
2018 Q2 USD/CAD prediction
Scotia
1.27
RBC
1.30
TD
1.24
BMO
1.22
CIBC
1.30
National bank
1.21
An executive needing to stick in a base-case assumption into their short-term financial plan could do a lot worse than to put in the average or median number from these figures, or even just consistently use the prediction of one bank they have chosen, without cherry-picking. But suppose they have now “got religion” about probabilistic thinking, and want not just a point-estimate single base case prediction, but a probability distribution, or at least error bars on the base case estimate. They have a hammer - probabilistic thinking - and see 6 nails: 6 bank estimates. 

It seems beautifully set up to do something like the following: throw out the extremes (1.21 and one 1.30 for Q2) as potential outliers and create a range from the rest. “The dollar will most likely be between 1.22 and 1.30”. Or do something mathematically fancier, like calculating quartiles [FN: In this case, this yields roughly the same range. By the way, there are different algorithms for calculating quartiles and other percentiles; if you really want to do this, you should for instance read up on the difference in Excel between the QUARTILE.INC and QUARTILE.EXC function. But in this instance, the issue is elsewhere.] from the  “sample” and using them as whiskers around the median: “P25/median/P75 = 1.22/1.26/1.30”.

This is, however, alchemy. It looks impressive, but is meaningless. Each of the banks’ estimates is in itself the expected value of their respective probability distribution of the outcome. They may not have actually calculated it probabilistically, or even refer to it in that way, but implicit in their prediction is a sense that this is the “best single guess” that balances out reasons it might be lower or higher. It systematically averages away any thinking they may have done about plausible ranges of outcomes.

If you’re not persuaded, think of this thought experiment. Suppose there were only one bank, which as a result of its internal deep analysis decided the dollar was exactly equally likely to have a value of 1.0 and 1.5, precisely. If asked for a single point prediction, it would be quite reasonable for the bank to say, “1.25”, the average. The alchemy described above would take that one data point as gospel, and say a dollar will be worth exactly 1.25, when in fact the analysis done would actually be saying 1.25 has zero likelihood, it’s either much lower or higher. This example is extreme, but layers of that type of thinking on a smaller level underpin each bank’s prediction.

So - what can you do?

First, looking at the range of predictions and using heuristics like throwing away the extremes and seeing what is left is a good *qualitative* indicator for the level of confidence you should have in any prediction. As it happens, usually the banks’ average predictions end up being fairly close to each other, within a couple of cents.[FN: The fact at this point in time they were not has hit the popular press, for instance https://www.theglobeandmail.com/report-on-business/top-business-stories/crazy-as-a-loon-the-chasm-in-forecasts-for-the-canadiandollar/article38019810/] The fact the range is now 8+ cents is itself indicative of a greater degree of uncertainty.

Second, if you can, go to the source (or to other sources) to gain a true range of predictions, ideally with scenarios and rationales. For a Canadian company at this time, it is much more important to understand *how low or high  could the Canadian dollar plausibly go*, based on how different factors evolve. If you want, you can use sampling on scenarios to give you a range, in the manner discussed in Section [X.X]. As mentioned there, there are all sorts of biases associated with selection and weighting of the scenarios, but you are not falling into the trap of reducing the range of uncertainty just because you don’t see it.

Third, look for something else than nails, and bring out your screwdriver or glue or whatnot. For instance, looking at historical US/Canadian dollar exchange rates, it turns out that about 20% of the time, the rate changes by more than +-5% of the time over a 3 month period. And on average every second year, over some 3 month period the rate jumps by about 10%. Some version of this type of analysis is probably more useful in terms of putting semi-probabilistic error bars around any chosen single prediction than alchemy on the range of banks’ expected value predictions. 
​[FN: Warning: as discussed in [xxx], a bug as well as feature is that the outcomes of such analysis depend on the choices you made in structuring it. In this instance, it is based on looking at the ratio of month-end exchange rates to the rate 3 months previous, over the past 10 years. And the 20% figure refers to 10% of the time having a decrease of 5% or more, and 10% of the time an increase of 5% or more. Whether this is right framing to use depends on the business problem this is being applied to. For instance, the ideal analysis is different if the goal is to estimate how much quarterly financial results will be influenced by (unhedged) currency exposures integral in the business, compared to if it is to stress test how much could be gained or lost on a single contract that generates a revenue-cost currency mismatch open over a period of 3 months. That is outside the scope of this book.]

Barbara Corcoran, drunks under streetlights, and how entrepreneurs make dinner

11/10/2017

 
[Another excerpt from the book I'm writing, currently quite enjoyably at a monastery-turned-conference centre in Tuscany. Chapel to explore during teaching and writing breaks is at right.]

“The left [rational] side of the brain is totally overrated in business. I’m not a believer in the MBA-type stuff. Most of the times I ever lost a lot of money with somebody, they graduated from Harvard.” These blunt words come from Barbara Corcoran, who founded a real estate brokerage she sold 28 years later for $66 million, before becoming a “Shark” investor on the T.V. show, “Shark Tank”. They are representative of an important anti-analytical, anti-over-intellectual opinion much more broadly shared within the business world. How does one reconcile that with thoughtful, repeated, systematic risk management? Even if performed very non-bureaucratically and linked to business decisions, as recommended in this book?

One of the core strengths of entrepreneurs is their commitment to their trajectory. While they may not dither with endless tradeoff analyses, they do very much think about threats and opportunities in their business. Their commitment and concentrated exposure forces them to go all-in, but also to respond, pivot, somehow deal with adversity, and to maximally exploit flexibility and opportunity. In fact, speaking with successful entrepreneurs, I am often struck that they are much more clearly able to articulate what precisely are the big bets of their business model than cog-in-the-machine executives. The difference is that while a cautious, analytical executive may articulate their bets (if they bother to) as questions, concerns, or worries, the entrepreneur will articulate them as positively-held beliefs about the world. These assumptions are articulated (perhaps over optimistically) as fact, but also modified or jettisoned without regret if circumstances change or the bet turns out to be wrong.

What Barbara and other like-minded passionate entrepreneurs are really railing about is two things.

First, overly analytical and risk-averse “intellectual”/MBA business people over-think and under-act. They are always second-guessing themselves, don’t commit, and take decisions late by an excessive hunt for an analytical fact base. They are not fast enough to pull the trigger using heuristics and retreat too quickly rather than hustling.

Second, they over-analyze what is analyzable rather than what the real issues. There’s a well known joke about a drunk looking for his keys (hopefully house keys, not car keys!) under a street light. “Where’d you lose them?”, asks a bystander. “Back down the block.” “Shouldn’t you look for them there, then?” “No, it’s too dark back there to see anything.” If Barbara’s strawman Harvard MBA analyzes merely the issues where he has plentiful access to data and well-established analytical methodologies, but ignores his gut about the shadowy issues that really matter, then he is wasting his time indeed.

Self-reflective entrepreneurs-in-spirit, whether they are the founder of a startup or a line executive in a larger company who doesn’t want to miss the forest for the trees, do make time for “MBA-type stuff”, and by extension analytical frameworks and methodologies like risk management — where they are relevant enough! As I write this, I am working with two talented, driven startup founders-turned-CEOs. They can articulate their big bets, and have at their mental fingertips a solid understanding of the handful of most crucial risks that may derail them from their objectives. They have actively through through ways to anticipate some of those risks, how to be resilient to others, and how to turn some of them into opportunities at the right time. They may not have formal risk reports, risk metrics, heat maps, and their companies’ organizational complexity is a far cry from what would require naming an explicit Risk Manager. But crucially they both reflect that their best thinking on this occurs when they detach their minds from the mundane. “I think about that sort of stuff when I fly back [in his case, regular trips from his home to work with an accelerator in Silicon Valley] and am not getting pinged by my team all the time”, says one of them. “I try to divorce my mind from the details once in a while and think in scenarios, usually when making dinner”, says the other. That’s what good risk management is (though I’m not sure how it impacts dinner!)   
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Upcoming conference presentations

13/9/2017

 
I'm making two upcoming conference presentations, both keynote speeches, one followed by moderating an executive panel. I will hopefully will be able to post material soon afterwards; contact me if interested earlier.
  • "Industry trends in risk management and their implications", Openlink NEXT conference, London UK, Sept 26. Focus is on trends such as VUCA, strategic vs merely trading/financial exposures, digital enterprise, and their implication for risk management and risk taking in the financial, energy, and commodity sectors.
  • "Being a good risk coach rather than a hovering parent" followed by a facilitated leadership panel, onRisk 2017 (Ontario public sector risk management): The Intersections of Risk, Toronto, November 16.

Scenario planning and stress testing

22/6/2017

 
My former colleagues at McKinsey have just published an article on stress-testing for nonfinancial companies. Unsurprisingly, I very much agree with them. Whether the goal is stress-testing (a specific risk-management centred viewpoint) or strategic planning, companies need to think more in scenarios to effectively get their arms around the uncertainty they need to navigate. 

I've written about this on these blog pages and in an article planned for a Canadian mainline business publication (where it ultimately ended up on the cutting room floor after internal conflict in the editorial board in which I was collateral damage) in the context of the election of Mr Trump as president. 

Ultimately, stress testing, scenario planning, and risk management live in the same ecosystem, just in different ecological niches. Ideally they work together, and which one is a priority to exercise for a given company, or provides the best path towards a more holistic approach, depends on the circumstances.

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    Principal, Balanced Risk Strategies, Ltd..

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