|
The WordPress.com stats helper monkeys prepared a 2012 annual report for this blog.
Here’s an excerpt:
600 people reached the top of Mt. Everest in 2012. This blog got about 3,700 views in 2012. If every person who reached the top of Mt. Everest viewed this blog, it would have taken 6 years to get that many views.
Posted by foboni on January 10, 2013
http://foboni.wordpress.com/2013/01/10/riskopes-blog-2012-in-review/
In both cases, unfortunately, there were casualties.
In both cases, the blasts were apparently due to sawdust.
In both cases official inquiries are still ongoing, but the media have been filled with hypotheses and discussions. Reportedly (Globe and Mail, April 27th) “the B.C. Government waited until the second catastrophe this week to issue province-wide guidelines, inspection regimes, deadlines and, possibly, new regulations”. Reportedly (same source) “when an explosion and fire tore through the Burns Lake mill, owners of other mills across the B.C. Interior -including Lakeland- looked at housekeeping and upgrades to address the potential risk (NB: improper technical language: should read potential hazard, the difference is important, see below!) of sawdust explosions at mills working with dry wood killed by pine beetles”; “safety experts noted the potential risk (NB: improper technical language: should read potential hazard, the difference is important, see below!) of sawdust after the January explosion at the Burns Lake sawmill”; “the industry has already been struggling with a massive shift since the mountain pine beetle began the widespread destruction of B.C. Forests”.
Also, the Globe and Mail (April 28th ) quotes Margaret MacDiarmid, the province Labour Minister, saying that “Burns Lake fire had appeared to be unique, pointing to the cold snap in January that had forced the mill to close its windows, increasing the hazard of a dust explosion”.
Out of respect for all parties involved, scientific rigour, we will not discuss the general foreseeability of such an event (Globe and Mail, April 26th reports for example: “in 2009 an inspection report found that Lakeland had not been monitoring worker exposure to wood dust…”), possible explosion triggers, possible preventative actions, post-catastrophe measures, possible responsibilities.
Instead we will focus our attention on some Risk Management points.
a) If the environment is overly optimistic looking at hazards is conducive to reject any preventative action on the basis of “it’s just a hazard like another…we live with them every day”…things will remain as they are until an accident happens.
b) If the environment is overly pessimistic then excessive preventative actions will be taken, with potential loss of competitiveness.
a) Well balanced regulations are risk based rather than hazard based.
b) Risk Based Decision Making (RBDM) is a discipline that warrants proper scientific approaches. It is not “improvised”, it requires skills. Methods should be “enforced” rather than resolve to knee-jerk reactions.
-pine beetle size and severity of the outbreak and
-the cold snap
can indeed be considered somehow linked to the global climate change.
We do not believe any serious professional would ever be claiming that such a scenario (starting with climate change….down to saw dust explosions) could have been foreseen. However, if during a Risk Assessment site-visit significant volumes of sawdust would have been seen, a fire or explosion scenario would have been generated (not important to define the cause of the dust), potential consequences evaluated, etc. (see point 1,2 above).
It is time industries start looking at their risks in proper rational ways. Risk Assessment techniques will pave the way to safety, security, competitiveness and long term sustainability.
A sustainable industry is an industry that can keep working without a break. Avoiding catastrophic accidents is the first step toward sustainability.
Posted by coboni on May 9, 2012
http://foboni.wordpress.com/2012/05/09/two-blasts-have-rocked-saw-mills-in-b-c-in-recent-times-one-in-january-leveled-the-babine-mill-burns-lake-the-other-in-april-destroyed-lakeland-mills-prince-george/
Let’s start by asking ourselves if our book « Improving Sustainability through Reasonable Risk and Crisis Management (Oboni F., C. Oboni,, ISBN 978-0-9784462-0-8, 2007, www.oboni.net ) could have been entitled instead “Improving Resilience through Reasonable Risk and Crisis Management “?
First of all let’s note that some authors rightly consider and explicitly state that Risk Assessment/ Risk Management are the first step towards a resilience improvement study, and remain at the heart of any attempt to increase the resiliency of a system. We also note that Riskope’s approach has always covered risks as well as crises, and we have always encouraged our clients to establish Crises Plans/ Business Resumption and Continuity Plans, Disaster Recovery Plans, based on scenarios developed during Riskope’s studies.
After a wide spectrum literature search, it appears that a first major difference between a “classical” (meaning “current”) risk mitigation study and a “pure” (meaning “extreme”) resilience improvement study lies in the fact that the second does not examine in detail the causes of negative outcomes against which the system has to be protected.
That approach sounds however rather simplistic, as shown in the following example: assume that the subject under scrutiny is a ship-loader and that the metric for risk is business/ service interruption (BI). In a risk assessment we will seek to assess the probability of occurrence of certain BIs and formulate scenarios capable of producing them aiming then to define appropriate risk mitigation measures. A resilience improvement study would instead define what should be done to reduce the impacts of a BI of more than, say, 1,000 hours, regardless of the cause. Of course, without knowing what caused the arbitrarily selected 1,000 hours BI, it would be difficult to imagine how to protect the system! Undoubtedly, if the cause was for example a local fire, which would leave the entire adjacent civilian infrastructure intact, we would be in a very different situation than in the aftermath of a major earthquake or a nuclear accident “Fukushima-style”!
The only “excuse” to justify the use of “extreme” resilience improvement studies rather than a risk mitigation study seems to be able to prepare protective plans for events with a very low estimated probability; as a matter of fact, the slogan used by promoters of this approach is “let’s think about the unthinkable”. So, we could say that “extreme” resiliency improvement studies would protect users against the “Human universal optimism” trend in the estimation of probabilities. Unfortunately, we Humans also have very short memory and bad habits such as the one of considering rather common events as Black Swans would push users of “extreme” resilience improvement studies to unsustainable mitigative investments. Let’s not forget that a proper, logical risk assessment process defines scenarios and pushes the reasoning to “think about the unthinkable” as well, where “unthinkable events” have a probability -p- set at the limit of human credibility (10-5 (one in hundred thousand) to 10-6 (one in a million)), a range that is “universally agreed” through many industries . No need to invent “new unthinkable” stuff!
“Extreme” resilience improvement studies ” bypass the risk scenarios definition and look at possible extreme damages (Consequences-C-) caused by unspecified “catastrophes”, placing themselves systematically at –Max C-, with -p- as low as an unspecified “unthinkable” can be, regardless of the scenario that could have led to this point …. asteroid, terrorist attack, etc. Resilience improvement studies thus avoid relying on probability estimates, which, if presented improperly or ill-conceived, might give a false impression of precision. Instead they will look to major consequences scenarios, and discuss how to mitigate them.
If this seems to constitute a very conservative approach, it is very likely that it would lead to higher “unjustified”mitigative costs , and almost certainly to biased allocation of funds, compared to what would result from a proper risks assessment taking into account estimates of the probabilities of occurrence.
Some resilience improvement studies seem to follow a more balanced process analyze the hazards, develop a list of possible scenarios, define p, C for each scenario; however, they generally end up biasing for unspecified small p / large C scenarios.
It can be concluded on this basis that resilience improvement studies and risk mitigation studies are virtually identical except for the phase of risk prioritization and decision making / action plan. Naturally, as already in proper day-to-day practice, risk mitigation studies will address extant mitigative measures and controls (NB: in fact, these controls and mitigations are already part of the system’s resilience).
Resilience is generally defined as the:
“Capacity to maintain the continuity of activities Even In The Face of Threats, disaster, and adversity ….”
So a resilience improvement study has to formally include actions that are already part of good management practices such as Business Continuity and Resumption Plans, Recovery Plans, Disaster Recovery, etc. …
These points having been clarified, the first question still remains open: what distinguishes a risk mitigation study from a resilience improvement study?
In Riskope’s (www.riskope.com) daily practice studies, for example on logistic nodes (critical infrastructure) such as mineral ore ports, risk studies consistently turn in the direction of resilience because, if a disaster strikes the node, it is essential to ensure operations continuity with alternative solutions/routes. We would even say that a good Risk Management approach must necessarily lead to solutions aimed at increasing resilience to avoid massive and too costly insurance contracts. Incidentally, if an industry is hit by disaster, and is unable to react, thus displaying insufficient resilience, it will have its image severely tarnished, perhaps forever!
This view is also supported by other professional groups / researchers, such as, for example, http://www.cmcc.it/research/research-projects/concluded-projects/freeman , T. Mitchell and K. Harris, Resilience: A risk management approach, ODI Background Notes, January 2012; S. McManus et Al., Resilience Management, A Framework for Assessing and Improving the Resilience of Organisations, Resilient Organizations, New Zealand, Research Report 2007/01.
At this point let us note that none of the elements listed above (Business Resumption/ Continuity Plans, Recovery Plans, Disaster Management, etc..) has the power to change the cost of the immediate consequences of an event, but may strongly influence the duration to recovery, which causes a reduction of -C-. Note also that none of the above alters the value of -p-, whatever it might be.
So ultimately it is not really necessary to invent new buzzwords to solve problems that we have known how to solve for a long time!
Posted by coboni on April 4, 2012
http://foboni.wordpress.com/2012/04/04/resilience-a-new-buzzword-discussing-the-differences-between-risk-and-resilience-improvement-studies/
We humans often assess the probability of an event by asking ourselves if there are “cognitively available” examples, (i.e. readily available through memory) as Kahneman (Nobel Prize in Economics) and Tversky demonstrated in a series of papers published between 1971 and 1984, among which the most popular is likely the one entitled “Prospect Theory”.(1979 quoted at page 212 in our book)
The phenomenon highlighted by Kahneman and Tversky is called “availability heuristic” and is one of the very well know cognitive biases that plague us Humans when we are confronted with decisions under uncertainty.
That’s most likely why the 2008 recession was considered unheard of, a Black Swan: just because most people did not remember (were not even born) in 1929! The Black Swan “fad”, as we have demonstrated in earlier blog posts is indeed based on Humans having “short memory” and considering the last events as “unique”.
Sometimes we are forced to use availability heuristics because available data are indeed very scarce and only recently gathered, but reliable statistical evidence will systematically outperform “intuition” when “looking backwards” in time to past events to draw conclusions.
Looking backwards, however, is not enough, actually it is critically limiting and incomplete, when we are confronted with managing risks of corporations and projects. A good risk assessment has to be “looking forward”, examining “classic” scenarios and hypothetical ones, that have not yet occurred, or not yet occurred with larger magnitudes, to make management decisions.
Over the last five decades or so the risk management community has settled on representing the results of Risk Assessments with Probability Impact Graphs (PIGs), risk matrices, “Heat Maps”, which have a number of staggering intrinsic conceptual errors, with potential dramatic consequences on their users. Voices raise in various parts of the world to discuss these fallacies, but they remain for the great par unheard.
The continued “main stream” reliance in using inappropriate techniques like PIGs, and being satisfied of their results, or, using intuition to correct PIGs’ evident fallacies, is simply another manifestation of Kahneman and Tversky explored ways we, Humans, have found to introduce irrelevant criteria in decision-making.
As a matter of fact Kahneman and Tversky have explored in detail how human judgement can be distorted when making decisions under uncertainty: humans tend to be risk-averse when facing the prospect of a gain, and paradoxically risk-prone when facing the prospect of a loss (even if the loss is almost certain to occur)! So, using improper methods like PIGs which almost surely will lead to confusion, losses, poor planning sits well with “main stream” human nature.
So, “now that we know that we do not know how to know better”, the whole idea of building a rational prioritization on top of existing PIGs, as they stand in most industries, or after enhancing them, comes out as a clear winner: by deploying rational prioritization we give a rest to our scientifically proven fallacious intuition, allowing our rational ego to make better informed solutions! Do not be “main stream”: belong to the small elite that adheres t stricter cognitive standards and make you industry thrive and prosper.
We will soon publish a post explaining how you can do that.
Posted by coboni on February 22, 2012
http://foboni.wordpress.com/2012/02/22/our-judgements-are-clouded-by-prejudices-and-misconceptions/
Riskope can also help you solve insurance denial situations adding value to you existing risk assessments, risk registers, ERM in an ingenious way.
The subtitle of today’s post could actually be spelled out as follows: we will show how your “standard” risk approach (risk assessments, risk register, ERM) that your peers and superiors already understand and “own” can be turned into a cutting edge competitive advantage, freeing capitals for business and production development, leading to more easily defensible, justifiable decisions. In other words, the mantra is: stop wasting moneys and efforts in security measures that do not pay off, over-investing in some mitigations and may be under invest in others, with, in both cases, potentially devastating unjustified consequences.Our metric is consistent, unambiguous, and provides context for better understanding risks fo your organization.
The “total” risk for each scenario can be calculated, and when applicable, it is possible to evaluate which portion of that risk lies above the tolerability
Instead of splitting this post in sections, as we have done in several occasions for longer posts in the past, we have decided to publish it as a self standing paper or in PDF, as we would like our readers to get a feeling for the logical continuity, getting to the conclusions in one breath and easily download the paper for reference.
The paper isn’t a thrilling Afghan terror or spy fiction story involving Bin Laden, but when you will get to the end and will appreciate how you and your company could profit from these concepts, we hope you will be breathless and excited, as much as we are in our day to day consulting practice!
As you will see, we have used a real life case study, with names etc. changed to respect client’s confidentiality.
Here you have a summary of the benefits yielded by the approach :
The prevalent critical risks were brought forward in a clear, rational and defensible way
The number of critical issues was shown to be smaller than originally evaluated at Status Quo
The insurance portfolio was shown to be poorly balanced and adjustments were proposed
The new priority list let Management make better decisions in mitigative investments’ allotment and freed moneys that could be better allocated elsewhere
The methodology allow rational updating of the probabilities when new data are gathered.
Posted by coboni on September 15, 2011
http://foboni.wordpress.com/2011/09/15/on-time-on-budget-in-control-showing-your-leadership-with-sustainable-capital-expenditure-even-during-recessions-and-economic-financial-crises/
An update of Whitman’s and ANCOLD tolerability/acceptability curves (casualties from man-made or natural catastrophes, large dams failures) shows evidence for a G8-wide societal acceptability.
Comparison of the various curves, i.e.: Whitman (upper and lower), Ancold (upper and lower), 2011 Riskope's update, constant risk.
We have already discussed many times how well-balanced and sustainable decisions can only be taken if risks are compared to properly defined risk tolerability/acceptability criteria.
The first explicit examples of Risk Tolerability/Acceptability criteria were published in the mid-eighties by Whitman and Morgan. In more recent times the Australian National Committee on Large Dams Incorporated (ANCOLD Inc), for example, also came out with its own criteria.
In general two criteria are defined, a prudent or risk averse one, thus a low bound curve, and a risk prone aggressive, high bound curve.
Operational Risks Tolerability curves are used by Riskope (www.riskope.com ) on a routine basis to support client’s decisions at facility scale.
In our latest paper or in PDF, we built an updated curve for human losses (casualties) at country-wide scale (large-scale societal acceptability). The curve we built is not necessarily the “true” large scale acceptability, as we used a few examples of events that a) caused significant casualties, b) by the generated reactions, clearly showed the events were not tolerable in G8 countries. Furthermore, by the very nature of the considered events, our curve is not the lower bound one, but is most likely located near of just higher than the new upper bound 2011 tolerability/acceptability threshold (to be developed).
As mentioned above we used 2000-2011 events from G8 countries, Japan, USA, Italy as follows:
Several dozens traffic accidents casualties per week-end, several times per year, lead the Italian government to invest a large capital in a continuous real-time speed checking and enforcing system (Traffic Tutor), road safety, as the situation was intolerable.
A quake causing 308 casualties (Aquila), thirty years after another catastrophic one (Irpinia) lead to the conviction of a large number of public officers for mass man-slaughter and various other charges (no such reaction for the Irpinia one, thirty years before).
A terrorist act (9/11, New York) caused approx. 3,000 casualties and the USA “declared war on terrorism”.
A quake and a tsunami (Fukushima) with a wave considered to be larger than the Maximum Credible Event (MCE) have caused an evacuation zone of 20km, then 30km radius, with very large number of afflicted people (which may become ill in the future); Germany and other countries have decided to stop their nuclear energy programs, showing that the event was considered intolerable.
The following remarks can be made on the curve we generated:
Between 1984 Whitman lower bound and 2011 we note a clock-wise (to the right) “rotation” of the curve. This indicates that:
In the G8 countries, when looking at large scale catastrophes (1M casualties and more, country wide scale), societies are less tolerant than in the ’80s
as opposite to the prior point, when looking at events potentially generating less than 1M casualties, societies are more tolerant than in the ’80s
as a side note we remind that scale effects are very significant: for example, when shifting from a country wide scale to a “facility scale”, the acceptability (we are not showing that case today) is significantly lower than in 1984
The Whitman aggressive (upper bound) curve is nowadays in the intolerable region starting at 1,000 casualties, as opposite to being in the tolerable region below 1,000 casualties
When comparing the 2011 curve with a “theoretical constant risk” curve, we note they are almost parallel, meaning that one-casualty-high-probability event is as acceptable as high-casualties-low-probabilities events. Instead, Whitman lower and upper bound were “flatter” than the “theoretical constant risk”, characterising societies getting more tolerant as casualties increase and probabilities decrease.
Posted by coboni on September 6, 2011
http://foboni.wordpress.com/2011/09/06/what-fukushima-2010-nuclear-accident-the-twin-towers-911-terror-attack-deadly-traffic-accidents-and-aquila-earthquake-italy-hurricanes-have-in-common/
We promised to publish the results of our poll (http://foboni.wordpress.com/2011/05/18/cyber-war-is-%E2%80%9Congoing%E2%80%9D/ ), so here they are, for your information.
Please note, all percentages are approximate, rounded up to the nearest 5%.
While 60% of the respondents use a well defined risk glossary, only 25% use well-defined risk assessment procedures and 40% expresses probabilities in non numeric ways (qualitative, indexes etc.).
Almost everyone declares to formally evaluate consequences of their decisions, yet 50% do not formally evaluates cascading failures (dominoes effects, interdependent failures).
60% of the respondents define risk tolerability criteria to support their decisions, and almost everyone update their assessments by periodic reviews.
50% have a formal definition for Cyber Defence in their organization, and 75% of the respondent are concerned by possible Cyber impacts (attacks, warfare, etc.) to their organization. Accordingly, 75% believe their organization should strengthen their Cyber Defence scheme.
90% believe that information silos in their organization blur their vision, and almost everyone says that Cyber Defence programs should span across all their organization’s activities.
Now that you see the results spelled out in plain text, what are your reactions?
Posted by coboni on August 3, 2011
http://foboni.wordpress.com/2011/08/03/results-of-our-poll-on-cyber-warfare-and-risk-based-decision-making-procedures/
From the Black Swan list we can count 1 Political/social Black Swan (Unrest in the Middle East).
Now if we look at the last 200 years of Human history we can easily count at least 16 (http://en.wikipedia.org/wiki/List_of_revolutions_and_rebellions) political/social major large scale events. Even without considering two World Wars, but only “a few additional wars since then“, we get, for the sake of simplicity, to a total of around 20.
So, now, the question is: how can anyone try to argue that something that happens approximately 20 times in 200 years is a Black Swan?
Having worked many times as expert in courts (civil and criminal) we can tell you that no judge, no jury, would follow a theses claiming that some event happening world-wide 20/200=10% of any year is a “hard to predict, rare event”!
The Black Swan list also shows 1 Terror Attack Black Swan (Twin Towers & Pentagon).
Here we would be forced to enter into a more detailed discussion: as a matter of fact, the Twin Towers might well have been the largest terror attack event “ever”, even if we consider the towers as two separate attacks (which occurred very close in timer and space to each other), but many countries have and are subject to terror attacks or terror(istic) eras (Ireland, Israel, Italy, Argentina, Bolivia, Chile, USSR etc. just to quote a few), mass murder etc. with a total number of victims comparable, if not larger. The will to kill other human beings for political, religeous, ethnic reasons is certainly not unpredictable, and examples abound in human history!
All that to say that, again, considering September 11 as a Black Swan seems almost blind, or at least uninformed, especially since many critical structures all around the world, have been designed, from the 70s on, considering possible accidental impacts from a large aircraft (nuclear reactors domes, and if we are not mistaken, the Towers themselves), proving that “some people” were thinking ….
So, if on one hand it was difficult to believe that an entire group of terrorists would decide to participate in such a simultaneous suicidal attack, rational experts had foreseen such an “improbable” accidental event and taken measures against it (the fact that the measures might have been inefficient is out of the scope of this post). Terrorists just dramatically changed the probability of that accidental event, making it voluntary, but did not change its consequences! Thus, I would not try to argue with a judge that the Twin Towers were a Black Swan!
By the way, if you look here you will see how probabilities of events can be estimated for the sake of a risk assessment, even if data are scarce, and you will see that such an event would have been evaluated at a very low level, but certainly not discarded in a serious risk assessment. Please note however that of course much more detailed solutions exist!
WE WILL SOON CONTINUE THIS DISCUSSION WITH OTHER CASES.
Posted by coboni on June 21, 2011
http://foboni.wordpress.com/2011/06/21/black-swan-mania-part2/
It has been a viral epidemic culminating with the economic recession.
We are referring to the use of the term “Black Swan”.
Of course we are not talking about the Tchaikovsky ballet, or the recent related movie, but to the Black Swan Theory which refers “to unexpected events of large magnitude and consequence and their dominant role in history”.
The theory was developed by Nassim Nicholas Taleb to explain, for example:
Lists of what is considered by various authors as Black Swan have appeared all over the media in the aftermath of the 2008 economic recession.
We are showing one list, among many, below, as an example:
• 2001, attacks on the World Trade Center and Pentagon;
• 78% decline in the Nasdaq;
• 2003 European heat wave (40,000 deaths);
• 2004 Tsunami in Sumatra, Indonesia (230,000 deaths);
• 2005 Kashmir, Pakistan, earthquake (80,000 deaths)
• 2008 Myanmar cyclone (140,000 deaths);
• 2008 Sichuan, China, earthquake ( 68,000 deaths);
• Derivatives roil the world’s banking system and financial markets;
• 2008 Failure of Lehman Brothers and the sale/liquidation of Bear Stearns;
• 30% drop in U.S. home prices;
• 2010 Port-Au-Prince, Haiti, earthquake (315,000 deaths);
• 2010 Russian heat wave (56,000 deaths);
• 2010 BP’s Gulf of Mexico oil spill;
• 2010 market flash crash (a 1,000-point drop in the DJIA);
• 2011 Surge of unrest in the Middle East; and
• 2011 March earthquake and tsunami in Japan.In the next parts (there will be two more), we will discuss why this list is MISLEADING, WRONG, and using “Black Swan” as
A BUZZWORD CAN BE A VERY DANGEROUS HABIT.
Posted by coboni on June 14, 2011
http://foboni.wordpress.com/2011/06/14/black-swan-mania-using-buzzwords-can-be-a-dangerous-habit/
Many Risk Assessment use Annual Loss Expected (ALE) as a metric for consequences. The failures of the system or subsystems under consideration are evaluated with an array of methodologies. Among these the classic one are Failure Mode and Effects Analysis (FMEA) and the Failure Mode and Effects Criticality Analysis (FMECA).
The essence of FMEA/FMECA is the impact analysis of every potential defect on functionality of the whole system and order of potential defects according to the level of its severity.
This has lead in the past to some “aberrant” studies where hundreds, if not thousands of defect scenarios and resulting paths to failure were analyzed in huge “trees” …..disproportionate with the available data and their quality, leading to misleading perception of the accuracy of the answers.
Instead, the ultimate goal of any Risk exercise should be to define optimal proportion between threats and costs of system’s protections, based on available data and their uncertainties. The system can be anything, an IT system including hardware and software, a transportation system, a static infrastructure, an operation, such as a mine, a commercial wharf, a humanitarian program, a rescue or military operation, etc..
Once a proper approach is developed and appropriate preparedness actions foreseen, time needed for appropriate reactions in case of a hazard occurrence (the source of the risk) is decidedly shortened. The lack of appropriate preparation may lead the system (and its owner, whether it is a corporation, a governmental entity, an NGO) to collapse.
Appropriate reactions based on a clear plan pave the road towards long-term survivability and development of the system and its owner, as we have pointed out and discussed in detail in our book Improving Sustainability through Reasonable Risk and Crisis Management.
Specific literature very often skips the issue of quantitative methods of risk assessment, only concentrating on “mainstream” and often very poorly implemented qualitative methods or misleading ALE/ FMEA/ FMECA.
The root causes of this lack of attention to quantitative methods are nested in poor information, misunderstanding about the data required to perform a quantitative approach and “syndromes” on which we have already expanded in past postings on 16 common human traits.
Posted by coboni on March 17, 2011
http://foboni.wordpress.com/2011/03/17/ale-fmea-fmeca-qualitative-methods-is-it-really-what-we-need/
