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    Economic downturn crisis forecast November 2008

    Contact us to know details on economic downturn crisis forecast

    graphic results of economic downturn crisis forecast November 2008

    Economic Downturn Magnitude and Duration Quantitative Study by Riskope (http://www.riskope.com), November 2008

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Our clients beat the trends. We are proud to contribute to their leadership.

We have been reading with a lot of interest Deloitte’s report entitled: Tracking the trends 2011, The top 10 issues mining companies will face in the coming year.
The issues highlighted in Deloitte’s report are summarized below:

1 Financing
2 Volatility
3 Stakeholders engagement
4 Taxes, regulations and governments
5 How to invest more strategically
6 Hiring and retaining talented workers
7 Prospection (in hazardous areas from a geo-climatic-geographic and political point of view)
8 Climate change and other hazards (including regulatory hazards)
9 Infrastructure gap in the countries of operation
10 Exploring new revenues opportunities

As we were reading the report, it became quickly rather obvious that many of the points in the list above had already been covered by recent Riskope’s jobs for international clients.

This proves that our clients are clairvoyant and were “on the trends” way ahead of the pack.
That demonstrates leadership, and we are proud to contribute to our clients’ success.

To be able to brings concrete answers to our clients’ questions we had to develop unconventional and sometimes very innovative approaches, sometimes entire new methodologies.

Here is a summary of some selected jobs summaries, performed in the last few years, covering a number of the issues highlighted by Deloittes’ report.

We have been and still are performing studies related to Cyber War and Cyber Defense for military and Civilian Clients.

Financial Comparison of long term alternatives, including upside and downside risks have been performed for large environmental remediations (asbestos dump, arsenic stocks, etc.).

Alternative ways to work/process in hazardous climate and very diverse geographic areas have been studied in the field of transportation, unexploded ordnance (UXO), landmines etc.

Large multimodal transportation systems have been analyzed  with respect to climate change impacts, special hazards, including terrorism.

B2B, Corporate to Country solutions to reduce impact of seismic events, ingress/egress problems have been analyzed, prioritized, using Risk Based Decision Making (RBDM).

Cleantech solutions (disposal of waste oils, reduction of carbon footprint, alternative transportation modes, etc.) have been weighted and compared to standard solutions.

Crisis Forecast, One Year and 3 months Later (reality check)

In the “Economic Downturn Magnitude and Duration Quantitative Study” we published in November 2008 we established a few classes of “Measurements of Magnitude” for the crisis to come.

Now let’s analyze more in detail the case of Greece (not a G20 country, but a Euro country). What can be read in the news is that a “new round of painful austerity measures, including salary cuts for civil servants, pension freezes and tax hikes” is going to be undertaken.

Therefore we can conclude that Greece went from the class “Blues” to “Generalized Poverty” (see http://www.slideshare.net/Foboni/crisis-forecast-one-year-later). Generalized Poverty is characterized by high rate of unemployment (up to 10% -12%), poor to nonexistent maintenance of civil systems, reduced health programs, reduction of salaries of public officers, protests, some criminality increase, and some violence.

In our paper we defined the probability to see the next level, i.e. “Severe Impoverishment”, characterized by extreme rate of unemployment (over 12%), severe reductions of public transportation offer, gradual replacement of police forces with armed forces patrolling, reduction of state-managed retirement plans, with generalized protests and criminality increase, high violence etc…

Crisis Forecast, One Year Later

On 14-15 Sept 2008 Lehman Brother went down in flames.

In the aftermath of Lehman Brother crash we published on internet a forecast of the crisis “duration and magnitude”. Interestingly, only a handful of contacts asked us clarifications and to give details on the scale of consequence we had used (is it linked to stock markets? To financial indicators?)…
May be, no one believed that reasonable predictions can be made?

As we were publishing our prediction, we were indeed already seeing in the media statements reporting that “quantitative models were wrong” and other inflammatory statements. As usual, in panic/emergency situations, our society tends to react with little finesse (that’s by the way one reason why Crisis Management Plans are so important to implement BEFORE a crisis).

“Models” as a whole were discredited in the eyes of many readers and “forecasters”, now seen as pariah, became persona non grata.

Apparently no one bothered to say that “some models” are plainly wrong or were very poorly used, but others may work just fine!
No one bothered either to say that may be some ruthless people had used the models in order to get the replies they wanted (we have seen the same happen in fields as different from financial forecasts as humanitarian demining, and we have even published papers on this subject, all along with others).

In the full paper we summarize the prediction as it was made one year ago, and we analyze how it stands in front of one more year of history.

Enhancing Efficiency and Efficacy in Humanitarian Programs

We often confuse efficiency and efficacy.

Efficiency corresponds to an operation with a high result-versus-costs ratio, for example results vs. energy, time, and money.

Efficacy characterizes an action with the power to produce an effect.

Efficiency means doing as good a good a job as possible. Effectiveness means getting a result by doing the right job.

Reportedly neither efficiency nor efficacy rank very high in the Humanitarian Programs industry, one that lives, for the most part, on the good will of international donors with actors harshly competing just like commercial corporations to get the largest share of the donations.

For example, over recent years, the community working towards the aims of the Anti-Personnel Mine Ban Convention (Geneva International Centre for Humanitarian Demining, 2005; The Convention on the Prohibition of the Use, Stockpiling, Production and Transfer of Anti-Personnel Mines and on their Destruction, 1997) begun to struggle with fundamental questions related to the efficiency of clearance efforts and the need to release land in countries facing strong demographic and social pressures (Jordan Times, 2004). Indeed, much of the land being cleared, using expensive and resource-intensive assets, is generally not found to be contaminated by land mines, unexploded ordnance or by explosive remnants of war (L. Geddes, 2005). Similar examples could be set up for other fields in the Humanitarian Programs arena.

From a decision making point of view it has always been a challenge to distinguish between sometimes conflicting needs in poor countries, possibly devastated by wars and diseases.

Innovative methodologies allow enhancing the performances and deploying assets where they are most needed.

It has been recently and eloquently demonstrated that risk based decision models could significantly improve the situation on both the efficiency and the efficacy front.
As an example, interested parties can see the Gichd website (Manual Demining Study, Risk Section and Appendix), as well as a Presentation.

Proper decision making techniques in fields as diverse as Humanitarian Demining or Heavy Industry infrastructure allow to select the right job first and to do a better job in enhancing the sustainability of corporations, communities and even individuals.

Rational Methodologies for Land Mines/Unexploded Ordnance Contaminated Land Release or Clearing Decision Making

RECENT UXO/MINE CLEARANCE FINDINGS

Over recent years, the community working towards the aims of the Anti-Personnel Mine Ban Convention1 (APMBC) has begun to struggle with fundamental questions related to the efficiency of clearance efforts and the need to release land in countries facing strong demographic and social pressures (Jordan Times, 2004).

In a series of studies on Lao PDR it was found that physically cleared ground more than 292 km2 was less than 2% contaminated with Explosive Remnants of War (ERW), denoting a rampant and chronic waste of resources and life-saving efficiency in an industry that lives on the good will of international donors. Very costly mistakes are by and large made at tactical (local/community) decision making level, i.e. when deciding whether to clear, sample or release a Suspected Hazardous Area.

This appears to be indicative of operators clearing ground where, in all likelihood there may be no ERW, instead of undertaking a reasonable, transparent and sustainable analysis of available information and then allocating resources that would maximize the result.

VARIOUS ENTITIES WORLDWIDE ARE INTERESTED IN ENHANCING PERFORMANCES OF HUMANITARIAN ACTIONS

Various entities worldwide are of course interested in releasing land and allowing clearance resources to be deployed to areas where mines and UXO presence is most likely.

However, unless the consequences of an ERW initiation are included in the information analysis (impact on population, development etc.), i.e. unless “Risk Based Decision Making (RBDM) for Land Clearing and Releasing” is performed, then rational, transparent and sustainable portfolio prioritization at local, regional or national scale cannot be achieved.

A preliminary version of the RBDM developed by Riskope (C.+F. Oboni) when consulting for GICHD and calibrated by them at programming using examples from Europe and using Whitman’s acceptability criteria reported 30% less mistakes made in selecting properties to clear than usual procedures ( Riskope Presentation at GICHD )

MODELS CAN BE MORE OBJECTIVE THAN HUMANS

The results confirmed the nowadays generally accepted concept that Humans seem to be overly confident in their decision-making skills and human misjudgment is a source of wide-spread budget and resource wastes. Those who resist this type of model’s findings, generally a majority at first, are typically quite willing to admit that models will be right more often than human experts “on average”, but love to point out special cases (Financial Times, How computers killed the experts, FT, London, Saturday September 1, 2007; P. E. Meehl, Clinical versus statistical prediction: A theoretical analysis and a review of the evidence. Northvale, NJ: Jason Aronson. (Original work published 1954), 1996.) and the inevitable exceptions. To the authors’ dismay the models were tampered with shortly after their release, most likely as a result of this train of thoughts.

WHAT CAN BE DONE TO ENHANCE RBDMs PRELIMINARY MODELS

The preliminary models were based on a priori probabilities to overcome the lack of data and the siloed data syndrome. Despite their limitations, such probabilistic models are perfectly acceptable, and are the only possible way to proceed in many industries. Possible enhancements would come from pertinent use of the available data and development of proper statistics.

The 2006 GICHD models showed it was possible to significantly reduce inefficiencies due to poor judgment in a UXO contaminated area with a probabilistic model using limited information. The authors believe a statistical model based on extant data, once the data silos syndrome is overcome and factual available data are pertinently processed, would certainly outperform the former and bring great advantage to the world of humanitarian demining. Moreover such an approach, pertinently modified could work for the landmine contamination case as well.

Over the last few months the meager set of results derived from the field trial of the preliminary RBDM method enabled the authors to pursue under their own financing and free of any contractual obligation the development of such an enhanced model for the evaluation of the probability of existence of an ERW on a considered property.

Interestingly the analysis of the limited field trial data lead to preliminary conclusions which either “confirm” the general experts’ beliefs on UXO presence or go in a counter intuitive direction, as exemplified below.

For example, Riskope found that:

• The probability to find a generic UXO (pGU) while clearing a piece of land where someone has declared seeing a UXO is 76%.

• The pGU while clearing a piece of land where no one saw a UXO is 53%.

These two statements “confirm” the general experts’ belief that an eye witness is important to guide decisions, but interestingly the probabilities are not so dramatically different.

Riskope also found that:

• The pGU on a parcel of land where an accident has been reported is 38%.

• The pGU where an accident has not been reported is 75%.

This second set says that one has better chances to find UXO on a piece of land where an accident was not reported than where an accident was reported. So, if these findings are confirmed, the “feeling” that if a site has a “history” of accidents, then it is a high priority will be proven wrong.

These examples show that measurable relationships exist between extant data. Models using these relationships, that may sometimes be counter-intuitive, would certainly outperform what has been produced to date and be self-adapting to any ERW, any environment, in any country, leading to a “universal model”.

Under the Riskope’s R&D program analyses of the data relationships allowed to derive two pioneering models of the second generation.

By obtaining more data, further data analyses can be performed and relationship can be studied, proving or disproving good old “experience based” flair and methodologies based on non-scientific agglomeration of data under the form of tables, flowcharts etc.

Riskope pledges time for the development of a predictive method for UXO/ Landmine contamination based on the data that the public/NGOs/other entities will return to them for treatment (contact us via Riskope web site to receive instruction on formats and data requirements). The results of this endeavor will remain available to all the contributors and will not be the object of any commercial activity by Riskope.

If we all work together we will be able to deliver a tool that will save lives by allowing optimum deployment of demining/clearing efforts in entire countries.

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