The main points made are the following:

It is common that risk or technical experts and the public strongly disagree in their analysis of environmental risks, including industry-sponsored risk assessments. In fact, “experts judge risks to be minor or even non-existent while the public is quite concerned about the risks and perceive them to be high” (Sjoberg, 1999). Sjoberg analyzes several factors, including the fact that risk assessment requires factual judgment where values enter the process, different risk definitions such as probability vs. consequences, or that experts perceive themselves as control over the same risks that are of great worry to the public.

This post addresses potential sources of the schism between industry research and public acceptability of risk assessment, specifically public perception that industry-developed environmental risk assessments lack credibility and industry’s perception that the public are highly emotional and lack sufficient scientific literacy to comprehend and evaluate risk information. Following this analysis, we review required elements to understand how to optimize public participation in the environmental risk assessment process.

Academic and popular literature suggests agreement that the public’s distrust of industry has developed over the past half century as a result of repeated failures to provide adequate and/or accurate risk information to the public. One needs only look at the tobacco industry’s “research” on smoking risks to understand public skepticism. In 1994, the heads of major US tobacco companies testified before U.S. Congress that evidence showing smoking caused cancer was inconclusive. One month later, a box containing confidential documents was delivered to the University of California at San Francisco that showed industry-sponsored research acknowledging the risks were hidden for decades, potentially back to the 1920s (Cummings, Brown, O’Connor, 2007 pp1070-1). The consequential public opinion is that research conducted or funded by industry is unlikely to result in credible risk assessments, and even more unlikely to be presented to the public with accuracy and transparency should the findings be unfavourable to a proposed project or product.

Scientists were historically a tocsin for environmental and health risks, thus earning a level of credibility with the public. In the first half of the 20th century, scientists “may well have been viewed as trustworthy experts, but it mattered little to most people as they seldom came in close contact with science” (Jensen, 2000, 2). The last half of the century saw phenomenal growth in science and research, with an accompanying shift in the perception as to the reliability of information. Survey data indicate that ratings of confidence in government and industry have severely eroded during the past thirty years.” (Peters, Covello, McCallum p3). In fact, “the scientific majority sometimes finds itself pitted against a public opinion which simply does not accept its conclusions” (Sjoberg, 1999, p1).

A key reason for this shift is the increasingly competitive search for funding and the potential conflicts of interest resulting from those relationships. “An overall trend is that institutions dedicated to basic research are increasingly looking for partnerships with industry” with “an increasing influence of industry on research agendas” that “call for more economic relevance of research activities” (OECD, 2003). While economic relevance is acceptable, with nearly two-thirds of university research coming from industry sources, the bias becomes questionable. Financial ties that “intertwine industry, investigators, and academic institutions can influence the research process” (Bekelman, Li, Gross, 2003), but of greater concern is that “strong and consistent evidence shows that industry-sponsored research tends to draw pro-industry conclusions”. A review of research studies show statistically significant correlation between industry sponsorship and pro-industry conclusions (Bhandari et al, 2004).

Without industry funding, the existing government or charitable funding may be inadequate. In fact, in the absence of industry funding, it is unlikely that sufficient funding for important research “will be forthcoming from sources other than sponsors with a vested interest in the results” (DeAngelis, 2000). “The tendency to participate – and thus to invest time and other resources – is primarily a function of the degree to which an actor perceives a problem to touch his own interests, combined with the perceived chances to influence the output of the decision process and to expect a clear benefit from it” (Morgan, Henrion, 1990).

While industry has both the obligation and available funds to develop risk assessments, the public or impacted citizens typically lack the funds to conduct independent research or develop data that can be utilized to analyze, challenge, or contradict industry-produced risk assessments. Although government or taxpayer-funded risk assessments are not an efficient or desired alternative, the setting of minimum standards for risk assessments and information disclosure, and the establishment of a process for public feedback, is necessary. Potentially affected citizens rightfully demand transparency and accuracy in the communication of risk.

“Il successo è la capacità di passare da un fallimento all’altro senza perdere l’entusiasmo.” (Success is the ability to go from one failure to another with no loss of enthusiasm)

 Winston Churchill

 Con queste parole si potrebbe cominciare il ragionamento di oggi su un argomento che è spesso fonte di angoscia e di vergogna nel panorama italiano: la possibilità di sbagliare e l’importanza dell’errore.

 Spesso vi è infatti una credenza diffusa e generata dalla paura di affrontare i dati reali che spinge a trattare gli errori come se si potessero combattere con un incantesimo, capace di tenerli alla larga dall’azienda o dal settore di riferimento.

Un altro problema è che spesso gli errori sono estrinseci e radicati, al punto da essere diventati prassi di cui nessuno ricorda l’origine, ma che vengono portati avanti perché “si è sempre fatto così”.

Cìò può essere comprensibile in un panorama fatto di frammentazione e di aziende dimensione medie o piccole, spesso in competizione tra loro e quindi ben lontane da un’analisi di mercato globale che consenta di capire le logiche e di inserirsi in modo innovativo.

Tuttavia questo non è vero per tutte le aziende e negli ultimi anni si è vista la capacità di alcune start-up, libere dai vincoli del passato e concentrate unicamente sul far bene nel proprio settore concentrandosi sulle proprie capacità, che hanno saputo conquistarsi anche importanti parti di mercato.

Come spesso accade però basta guardare ai cugini anglosassoni per vedere che questo modo di vedere era già in atto anni fa e probabilmente anche in molte aziende italiane, che però spesso hanno col tempo dimenticato la propria vision.

Ad esempio nel 1966 un ingegnere britannico, di nome Pugsley, ha dichiarato che “una professione che non fa errori è una professione che non progredisce”.

Spesso infatti quello che a prima vista appare come un errore potrebbe diventare un modo alternativo di vedere i processi aziendali o di affrontare la situazione in un contesto mutato, che può aver trasformato i vecchi “errori” in soluzioni vincenti.

Questo è ovviamente un paradosso ma può essere utile per mostrare la necessità di cambiare alcuni degli elementi con cui siamo soliti valutare l’economia e lo stato di salute delle aziende.

Gli elementi dell’economia classica consentono infatti un’analisi “perfetta” basata su modelli statici, ma gli eventi degli ultimi anni ci hanno mostrato come cambiamenti (talvolta globali) possano avere effetti devastanti e provenienti da campi che si tendeva a sottovalutare.

Passando ai giorni nostri si può notare come Tata Motors avesse inventato il programma “Dare to Try”, segnalato anche su Sunday Times, per stimolare i dipendenti ad essere innovativi e premiare anche gli errori, perché magari da lì si sarebbero potute trovare soluzioni innovative e magari risolvere poi problemi strutturali.

Ratan Tata, l’ex presidente del gruppo era solito dire che i fallimenti sono come una miniera d’oro per una società.

Oggi molte grandi aziende, anche sul territorio italiano, hanno capito l’importanza di ascoltare il personale, nella segnalazione di proposte di miglioramento, che è un modo elegante per descrivere gli errori di organizzazione per poter porre in atto strategie mirate.

L’unica cosa da tener presente è di saper inserire una corretta analisi del rischio, che permetta di capire quanto l’errore possa incidere realmente sull’andamento dell’azienda o sul lancio di un prodotto nuovo.

Perciò non abbiate paura di sbagliare, perché solo così si può recuperare la capacità di osare che è un elemento necessario per competere, progredire ed eccellere.

E per chiudere può venirci in aiuto una citazione da un altro presidente americano:

È molto meglio osare cose straordinarie, vincere gloriosi trionfi, anche se screziati dall’insuccesso, piuttosto che schierarsi tra quei poveri di spirito che non provano grandi gioie né grandi dolori, perché vivono nel grigio e indistinto crepuscolo che non conosce né vittorie né sconfitte.

Franklin Delano Roosevelt

Almost half a century later later, large companies (Tata Group for example, India’s largest conglomerate) reportedly hand out an annual “Dare to Try” Prize for “the best failed idea”.

Ratan Tata, the former chairman of the group used to say that failures are like a gold mine for a company. We would add absolutely, yes, and it has been so since Humans started to wander around and feed on unknown plants and fruits, tried to build a fire.

Tata is not alone. Since the ’90s Eli Lilly, a large drug maker, similarly organizes “failure parties”.

Both these companies and other that follow similar paths have understood Pugsley’s message and that innovation cannot occur without failures.

No failures, no progress.

Success and failure are equally important learning experiences, provided they do not “kill” you or your organization, hence the necessity to “properly measure” the risks before jumping in.

That’s where risk management fits in the context of innovation.

It’s a bit technical, but it shows that maths make things simpler, rather than more complicated, bring clarity!

Talking about clarity, let’s remember that the context of most of our work at Riskope is in downside risk, in various industries. When we refer below to “Consequences”, we are referring to the “sum” of many components including, for example: replacement cost, Business interruption, loss of market share, reputation, legal costs, crisis cost (boycotts, protests…), etc.

As many pointed out in the LinkedIN discussion, both probability and consequences are actually stochastic (random) within a population of scenarios (careful not to “sample” different populations with the excuse of simplifying the problem). Both vary between a Min and a Max, with a certain expected value Ave, and a standard deviation St.

Oh, by the way, some may even point out that p,C are not necessarily independent variables, but let’s not go there this time around for the sake of space.

Thus R= p * C holds, with p, C and, as a result, R being stochastic (random) variables. Thus R will have a Min and a Max, Ave and a standard deviation St and it will be possible to evaluate the probability that R is larger than a given value, or what is the value that has a x% probability of exceedance.
More importantly, as we do on a daily basis in ORE applications (Optimum Risk Estimates), we can compare probabilistically the risk to the client’s tolerability threshold (another chapter we will leave aside for obvious space limitations).

To do that all of the above we need to calculate R.
Now, let’s make sure we do not use a bazooka to shoot a mosquito here, with all its unpleasant side effects!

Monte Carlo simulation would work provided we know with good approximation Min, Max, Ave, St of p and C. We believe that in most cases we could all convince ourselves we have a grasp of Min, Max and Ave, but frankly St is a difficult one.
Furthermore, Monte Carlo will require that you define the distribution (type) of p,C…and there we are in uncharted territory.

Information theory says that if we do not know (very well) what type a distribution belongs to, we minimize the errors on the estimates by keeping it simple! Some authors, even go so far as to say that you are better off selecting a UNIFORM (yes, you read well) distribution if you are not sure of the type.

Now, using Monte Carlo to calculate R as a product of two uniform distribution is really using a space ship to go buy your candies at the shop next door.

Below we are showing the super simple, analytic solution for the case where p and C are symmetric distributions (of any type) developing respectively between pMin =CMin =nil and a maximum value pMax, CMax.
Of course the case where pMin = a, CMin= b would also be very easy to derive.

Because both distributions are symmetric their averages are respectively

E(p)= pMax /2;
E(C)= CMax /2.

Risk R= p*C, so Ave (R), is immediately found as follows:

Ave(R) = Ave(p) * Ave(C)= (pMax * CMax)/4;

It can be seen that the average risk is four times smaller than the maximum risk, for any shape of symmetric distributions going from nil to Max.

A slightly more complicated direct formula leads to St(R).
Job done!

Now we can calculate any probability of exceedence you’d like by creating an empirical distribution of R with Min(R), Max(R), Ave(R), St(R).

Why would one use Monte Carlo and make the collateral damage of increasing the errors?

If this type of maths intimidates you, there is another approach we often use at Riskope: we consider several sub-cases of a scenario with point estimates of p-C and we “lump them up” in a “risk bubble”. We have a number of slideshows you can access from our blog that display such “risk-bubbles”.

Furthermore, if you really believe you have a grasp on the dissimetry of the p,C distribution, then you could use other direct approximations as well, still leaving the Monte Carlo bazooka to rest.

Worldwide, the aviation industry is one of risk management, health and safety. This global industry operates in an environment of extreme caution. Notwithstanding this, there have been approximately 150 cases of intoxicated pilots which have come to light over a period of 12 years.

As recently as last month, an American Airlines pilot was arrested as he was conducting pre-flight checks, preparing to fly 53 passengers from Minneapolis St Paul International Airport to New York City La Guardia Airport. Officers had been alerted by allegations that a strong smell of alcohol was emanating from him. They required him to take a breathalyzer test, which he failed. In Minneapolis, the limit is 0.04 of breath alcohol concentration which is much stricter than the limit for road users.

Not just alcohol.

There have also been cases of drug taking by aircraft crew. In 2011, the pilots and flight attendants on Russian airline Yakutia were accused of smoking marijuana immediately prior to boarding a plane for flight. This was investigated and the flight of 192 passengers was delayed for half a day before a new crew could be found to take control.

It is not only alcohol and illegal drugs which create risks. Addiction to prescription drugs can also raise issues of risk for airline personnel. These, though, are much harder to detect.

Most airline companies will have their own policies on substance abuse in addition to the requirements of international regulation. These policies tend to concern the use of alcohol and other substances within a given time relative to the flight. They are known as ‘bottle to throttle’ policies. Canadian Aviation Regulations are strict.

Aviation accidents which occur as a result of drink or drugs abuse are, however, rare. In spite of the media coverage which arises when a pilot fails a breathalyzer test, professionals within the industry are very aware of the cost – both financial and human – of a disaster happening. This is down to training and rigorous policies.

Aviation drug and alcohol policy is determined at three levels:

Numerous Man-made and natural hazards impinge on the buses path

The operation had run a shuttle bus service for its personnel from and to the capital city for a decade with no major bus accidents when there was a single fatality accident with a company’s vehicle (not a bus). The driver lost direction and went over the side of the slope, ending up approximately 200m below.  Then, in short sequence, another fatal accident occurred, this time with a bus.

Repeated traffic accidents, all over a country, have the potential to trigger crises and violent reactions against a specific company.

The operation immediately invested more than 1MUS$ in (national) road improvements encompassing 15km of heavy-duty guard rails, in follow-up to a list of almost 20 actions defined by a preliminary road safety risk assessment.

Mitigation along a highway may include a variety of techniques, the implementation of which should be a risk based decision process.

The operation publicly declared having the goal to reduce to the lowest possible, but sustainable and reasonable level, the chances of fatal accidents during the shuttling of its personnel. To attain that goal the operation requested that three alternatives would be compared in terms of risks, efficacy, efficiency and sustainability.

A) Status Quo, i.e. a bus service on the road “as is” up to date (base-case).
B) Investing (capital expenditure and increased ongoing maintenance) in mitigation of the existing road.
C) Building a private airport and shuttling personnel from the airport to the operation with buses.

For the study of quantitative relative risks of the three alternatives, it was decided to exclude from the analyzes business interruption and concentrate on accidental harm to people. The study also assumed that the impact of climate changes would be comparable for the three alternatives, reducing the need to develop complicated and very disputable scenarios.

The main aim of the risk assessment was to determine the probability of an event causing single or multiple fatalities for each alternative and from there define a preliminary evaluation of relative risks.
The “differential” relative risks between alternatives can then be used as a preliminary discriminant in the selection of the alternative to be implemented, unless other factors come into play and a long-term comparison shows that the risk profile/uncertainties inherent to each alternative could lead to significant differences in the long term cost and sustainability.

In order to cope with discrepancies and lack of data, like in many other cases, Riskope had to derive ranges of probabilities from incomplete data developed in other countries, other environments, in such a way to cover, to the best of Riskope’s knowledge and understanding, what is expected to be a valid range in the considered cases. Riskope had already successfully used such approaches in ERM efforts for with complex multi-modal transportation system including air, road, rail, barges and ocean going vessels to full client’s satisfaction.

International reputable sources were consulted to allow the definition of expected consequences of accidents, which remain, of course, subject to great uncertainties and can only be defined with broad ranges. Given the lack of data and great uncertainties surrounding this study Riskope adopted a prudent approach and considered large ranges of fatality rates per accident unless data were clearly indicating that smaller values were pertinent and possible.

Pertinent readily available data on road accidents were studied and summarized from the site specific data. The values finally used in the study constitute a blending of all these incomplete information and to remain on the safe side, Riskope adopted rather wide ranges, strutted, however, by factual data gathered to date of consequences and probabilities.

Under various assumptions (see table below) the quantitative total risk ( from ORE) was found to be lower for Alternative C (37% to 65% of Alternative A), with Alternative B having a total risk 73% to 98% of the highest risk Alternative A).

Aircraft shuttling (Alternative C) would reduce risks to the lowest relative level among the two considered alternatives  despite the necessary residual bus shuttling from the airport to the operation.

Total Risk for the three alternatives. Vertical axis is Total Risk (units are casualties per year).
The various colors correspond to the contribution to total risk by various hazards as coded in the legend (sorry, but we have to preserve client’s confidentiality!).

As mentioned in the study’s report, there are scenarios that could make this aircraft alternative less attractive than it seems (for example if pulmonary edema, dental problems, raising to significant levels because of repeated flying from sea level to the operation).

In summary, this ISO 31000 compliant study concluded that quantitative relative risks could be reduced half by building an airport and completing the shuttling service by bus, under the large set of assumptions that had to be made to cover knowledge and informational gaps.

If properly understood and managed, even an unexploded bomb can become an instrument for social gathering and community safety.

Back in 1999, in a course we were giving on a regular basis at UBC (Continuing Education, University of British Columbia), entitled “Design of Risk Management Systems”, then in the book entitled Improving Sustainability through Reasonable Risk and Crisis Management ( A guide to Making Better Decisions ISBN 978-0-9784462-0-8) we were promoting a strong linkage between Risk Management and Crisis Management as well as the need for robust, science based, risk ranking methodologies.

We spoused the principles that constitute ISO 31000 before it was written, like many serious Risk Management professionals, I am quite sure, and started reading IEC/ISO 31010 with lots of expectations.

IEC/ISO 31010 covers lots of ground indeed, including lists of available tools to identify hazards (in various contexts), determine probabilities (and their approximate distributions, if need be) and consequences of hazards. For each tool (like Monte Carlo simulation or Bayesian estimates, etc…) IEC/ISO 31010 defines applicability. Many welcomed this thorough international “house-keeping” effort, although some criticisms have been formulated, sometimes arising from very specific fields, that will most likely be covered in future editions.

From our perspective IEC/ISO 31010 has however some “shadow areas” that should be discussed:

1) Risk “tolerability/acceptability” is used, but not defined (not even a method is discussed, although historic published examples exist from various countries). This leaves the door open to major confusion and misrepresentations, inefficiencies and mitigative funds misallocation as pointed out by various authors in the last decade.
2) Risk “Ranking” is mentioned but a proper procedure is not defined. An example? In a top-ten risk list developed using common practice approaches, one will usually find high likelihood/ low consequence and low likelihood/high consequence risks mixed-up.
3) Crisis and Reputational impacts are not even referred to…despite the strong exposures these types of impact can have on the balance sheet of a corporations.
4) Complex consequences metrics needed to cover environmental, long term, etc… risks are not neither developed nor supported.

At Riskope we believe that until a code will stress these points and define proper methodologies (although it may remain a non prescriptive code like ISO 31000) we will be in a situation where a ISO compliant Risk Management approach could lead to confusion and misrepresentations with potential nefarious consequences.

What is your opinion?

The Titanic Photo: Sipa Press/Rex Features

This post is less a history of the disaster of the Titanic and more an insight into the legacy that the incident left to future risk analysis professionals. All data and information has been collected from public sources and will be identified where relevant.
The events of April 14th 1912 are infamous; the Titanic hit an iceberg on her maiden voyage and 2 hours and 40 minutes later she sank, leaving 1,503 passengers and crew dead. The unthinkable had happened to the unsinkable (it should be noted that the White Star Line company never used the ‘unsinkable’ phrase and this was later attributed to post sinking press coverage).
There are various facts that contributed to the tragic loss of life that night that could have been avoided:

• Too few lifeboats available; only enough to accommodate 1200 passengers on a ship transporting 2200.
• Despite warnings of potential ice flow the captain was instructed to increase speed
• The lookout had not been provided with binoculars
• The crew were not confident in the use of the brand new on-board wireless system

Lack of risk analysis

All of these factors are the result of money management being placed above risk analysis in the hierarchy of ship building. This was common practice in the early 1900s as competition became tight and shipping companies fought for passengers. However, the Titanic disaster led to an investigation of procedures and decision making that transformed the ship building industry and almost created the risk analysis industry overnight.
In his essay “The Titanic Disaster; An Enduring example of Money Management v Risk Management” Roy Brander (P. Eng) states that “most of the problems all came from a larger systemic problem. The owners and operators of steamships had…taken larger and larger risks to save money”. It seems barely credible today that such common sense decisions were being overridden by such purely financial reasoning.
The case of the lifeboats (or lack thereof) is the perfect of example of how the owners designed the Titanic with profit, not safety in mind. It was decided that the lifeboats took up too much deck space which – on a travelling monolith like the Titanic – was of a premium. The decision to allow passengers more space to enjoy a daily promenade or to play deck games was backed up by the fact that the regulation of lifeboats was undertaken by a committee “dominated by shipbuilders”. Lack of independent guidance with regards to such vitally important risk management decisions meant that mistakes – or even just plain bad decisions – were validated. In the aftermath of the tragedy the rules regarding lifeboat provision changed overnight. The money management based formula was immediately disposed of and a more simple idea – a seat for everyone – was introduced. This legacy of the Titanic disaster remains “never…questioned” to this day.

Concerns ignored

Other risk management concerns were swept aside by the ship’s owners. One claim was that the captain was instructed to speed through an area known for icebergs in an attempt to break existing Atlantic crossing records. The kudos of having such a record to the Titanic’s name would be worth thousands in extra bookings and so the risks of navigating through ice flow at speed were ignored.
In a bid to seem future proof the owners ensured a new wireless system was installed in time for the maiden voyage. However, due to poor training and untested procedure “not all warnings reached the bridge” and later SOS  calls from the Titanic were missed. With the vast technological advances this and last century have witnessed it seems unlikely this would happen again. What were applications only available to the military are now available to the average person, with technology and communications choices being wide and affordable. Training is also now a big part of risk analysis implementation with procedures put in place at every step to ensure mistakes are picked up immediately and resolved without delay, as well as more stringent procedures when it comes to checking new equipment and staff training.

There are a myriad of examples of how risk management was ignored in the building and execution of the Titanic in order to make a profit but the legacy of independent checks, regulation and lessons learned are still in place to this day. As Ray Brander states, the disaster “ripped away blindfolds and changed dozens of attitudes, practices and standards almost literally overnight”.
Riskope are proud to continue this code of independent risk analysis, working with businesses to make the correct decision in difficult circumstances whilst steering your projects across an ocean of uncertainties. Contact Us to discover how we can help your business navigate towards reasonable, sustainable, rational solutions compliant with your tolerability and acceptability criteria.

We will start this post by summarizing the tragic tale of L’Aquila, a city featuring many historic public buildings and centuries old residential structures located in Italy, a country where retrofitting of old (privately owned) structures to meet new seismic safety criteria is reportedly not enforced (OPCM 3274/03, art. 2, comma 6).

The area is seismic as witnessed by major earthquakes recorded since the year 1349, then 1452, 1461, 1501, 1646, 1703, 1706, 1958 and 2009. This last quake led to 309 casualties, 1600 wounded (200 very severely), 65,000 evacuated in the city and damages for over 10B€. Numerous studies had been conducted on the seismicity of the area, including long-term predictions made in 1995. It is well known, that predictions in this field are always surrounded by large uncertainties. Other studies had shown that local conditions may have amplified the effects of a quake in the area. A 1999 study on the vulnerability of public, strategic and “special” buildings showed critical vulnerabilities, which were never addressed in many buildings (including, reportedly, all those that ended up collapsing during the last earthquake).

Prior to the tragic event a “swarm” of foreshock earthquakes with almost 100 times the average rate was recorded in and around L’Aquila. The swarm triggered a crisis status due to public’s panic, further fuelled by independent scientists opinions. The swarm had started in December 2008 (M=1.8), then in January with M=3 gradually and continuously evolving with increasing intensity and frequency to the date of the major event.

An official government body called the National Commission for the Forecast and Prevention of Major Risks had six top officers participating in a meeting with the public on 31st March 2009, six days before the nefarious earthquake (Mw=6.3/Richter 5.9), and a day after the latest, and strongest event in the swarm.
Reportedly six commission members and one civil protection officer worked together as a collective unit during the meeting at the request of the head of the Civil Protection Department, G. Bertolaso, to carry out what Bertolaso had called a “media operation,” which meant that the experts spoke directly with the public rather than via the civil protection department. Still the public’s concerns were entirely dismissed and people were told to relax instead of being on guard. As a result some of the town’s residents changed their behaviour of seeking shelter outside, as they were used to doing when tremors happened, staying indoors instead.
The seven were brought to trial for manslaughter in September 2011 for the advice they gave in that meeting.

Our Analysis

L’Aquila was a very vulnerable “portfolio”, exposed to a natural hazard which had occurred in the past, and had a chance of occurring again in the future.
Both the hazard and the vulnerability were well documented. The only unknown was the timing. The discussion whether the 2008-2009 swarm was a beneficial energy release or, as it actually happened, a series of foreshocks leading to a stronger main event is, in the long run, quite irrelevant.

From a prior post on Negligence (see prior post for more detail on Negligence) we know that in some countries tort law uses the somewhat vague standard test of the “reasonable man” to judge liability of negligence. Following the test, an entity may be deemed negligent only if Mitigative moneys spent (per annum) are less than the annualized risks. Clearly transparency and rationality constitute a strong a priori defence in case something would go wrong.

In that post, using two real-life examples, we showed that the legal negligence test is not a critical factor for safety, health and risk and crisis management, but constitutes a bare minimum. The negligence test is not an end, but only the start of a continuous process.

How would the test score for L’Aquila case?

Even if one decided to be madly optimistic and not consider human victims, the wounded etc., but consider only the replacement cost of the public infrastructure (excluding private residences), loss in tax revenues, the cost of rescue and emergency management, the overall cost of the catastrophe could have been very optimistically estimated ahead of the quake at 5B€. Below are the replies of the test (at L’Aquila) for various probabilities of occurrence:
p= 1/100 C (B€)=5 Minimum Mitigative Moneys=50M€/yr
p=1/1000 C (B€)=5 Minimum Mitigative Moneys=5M€/yr

The reason for selecting a probability of 1/100 derives from the nine major recorded events in approximately 700 years. However, even if one would consider, again in an overly optimistic way, a probability ten times lower, thus 1/1000, the Minimum Mitigative Moneys would still be 5M€/yr.

Apparently nothing was done in l’Aquila to mitigate or prepare for the “next big one”. As far as we can read, no one ever performed a negligence test, a proper risk assessment, where not only the hazard, but also the consequences are considered.

Furthermore there was no transparency in the information to the public, to say the least.

What the Judge has ruled

The judge stated that the seven members of the Commissione had analyzed the risk of a major quake in a “superficial, approximate and generic” way and that they were willing participants in a “media operation” to reassure the public. He ruled that this failure led to the deaths of 29 of the 309 people killed in the quake and to the injuries of four others (showing a detailed approach to the causes of death). “The deficient risk analysis was not limited to the omission of a single factor,” he writes, “but to the underestimation of many risk indicators and the correlations between those indicators.” Here we would add that unfortunately the convicted seem to have performed hazard analyses, but not risk analyses, i.e. they did not consider the potential effects of the hazard and what the mitigative options could have been (not only retrofitting, but preparedness, drills, etc.).

The statement above summarizes very well Riskope’s understanding and analysis of the facts available to us.
All the discussions and commotion about the sentence (saying that “science has been killed”, that “the last time a scientist was judged in this way was Galileo”, etc.) are misplaced comments that show the ignorance of their authors of the basic rules of risk analysis. As a matter of fact, Scientific American (David Ropeik, The L’Aquila Verdict: A Judgment Not against Science, but against a Failure of Science Communication) rightly wrote that “this was not a case against science, the Judge recognized the non predictability of such an event already in the indictment, but a judgement against the failure of scientific communication (of risks).”
It is time that geoscientists, seismologists and engineers, who are very capable and respectable hazard specialists, recognize that risk assessments are an area which requires specific knowledge, in which they are not cognisant.
Risk assessments should be prepared by risk specialists and hazard knowledge constitutes at most half of the equation.
Judges have grasped the difference.