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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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How to get the most out of (Vegetable) Waste Oil for your Small or Medium Business: CDA-ESM can help you to select the best option

Reportedly, some fast food chains started (2007) to use their waste cooking oil to make biodiesel. In one example encompassing 1200 restaurants, the entire corporate truck fleet of 155 vehicles was converted to biodiesel, which means 6.1 million liters of waste oil put to use on the roads. Other sources reveal that McDonald’s trucks in Austria have been using biodiesel “for a few years.”

In order to show how Comparative Decision Analysis-Economic Safety Margin (CDA-ESM) can help in the selection of the best Vegetable Waste Oil management alternative, we consider as an example a restaurant, i.e. a commercial kitchen (for example an ”average sized” fast food restaurant, of roughly 150m2, or less than 500m3 construction volume) or any equivalent Medium Sized Business (MSB).

The MSB’s Management wants to find a better way to deal with their waste frying oils, but also wants to avoid the implementation of the filtering station necessary for an automotive use of its waste oils. Furthermore, the MSB does not have enough vehicles to make the fleet conversion economically feasible/reasonable.

Management is also fully aware that, reportedly, some large chains like Burger King and McDonald’s would like to use frying oil to heat water, but has heard they don’t have the space for a redundant system and fast-food restaurant personnel may not have the time nor the ability to operate a more complex burner system. However, Management has recently learned that there are off-the-shelf solution with burners capable of burning waste oils that are simple to use, can even accommodate several fuels, and, with some restrictions, can be inserted in existing furnaces, thus avoiding expensive replacements.

Management has therefore to decide whether they want to maintain the status quo, i.e. the presently active waste frying-oil management/disposal or to switch to a new installation which would include a burner capable of using those waste oils to generate useful heat. The new installation should not be redundant (no need for extra room) with the present one, and should either use the existing furnace with a new burner, or replace the old system with a brand new one.

This Paper shows how to set up the data necessary for the alternative selection using an innovative alternative evaluation methodology called CDA/ESM (Comparative Decision Analysis/Economic Safety Margin) (C.+F. Oboni, 2009). CDA/ESM brings to MSBs the opportunity to apply Risk Based Decision Making to the alternative selection process and to explore how two code compliant and perfectly legitimate alternatives may differ on the long term, not only in their costs, but also in their risk profile (upside and downside risks, i.e. opportunities and failures).

CDA/ESM eliminates the pitfalls of NPV (see below) and has been used at preliminary design level (Oboni and Oboni 2007, 2008; Oboni 1999-2000, 2005) to support decisions in many industries/situations by comparing alternatives in financial terms, including:
a) life’s cycle economic balance encompassing internal and external risks and
b) project implementation and demobilization costs and risks.

CDA/ESM has been successfully applied to date to industrial alternatives such as: rope v.s. road transportation, surface v.s. underground solutions, environmental rehabilitation projects, water treatments alternatives, transportation networks and go/no-go decisions.

CDA/ESM is particularly useful when comparing long term projects, as its “risks included” cumulative cost evaluation eliminates the “zeroing effect” and the “rosy scenario syndrome” linked to NPV.

Can we quantify reputational risk? Basel Committee is getting close to asking this.

The Basel Committee is getting closer to asking firms to try to quantify reputational risk and at Riskope we consider it absolutely feasible.
Indeed, in the probability-cost of consequence plot (i.e. the “risk space”) reputational risks can be easily added (they come as costs multipliers).
These two presentations: Pres1 and Pres2 contain information from our courses and book related to adding reputational components to standard risk assessments and risk based decision making.

This type of analyses can show that a small “physical” risk can lead to a huge “total” risk, once the reputational part is added. And the total risk may well slide over corporate’s tolerability. At Riskope we believe that any risk management effort should encompass the definition of the corporate’s tolerability threshold, and we have developed the methodologies to derive that threshold.
Some specialists seem to believe that reputation risks should be treated as “absolute hazards”, meaning that they either exist, and may lead to the corporate destruction, or they do not. Other suggest using a “proxy variable” like counting the number of clients the bank will lose in case of a “hit”.
We disagree with the idea of using a “binary” destruction/not destruction method because it sets us back almost a century in management history, as it means doing hazard management rather than risk management, like European Railroads used to do, for example, in the early ’900s.
We also disagree about using a proxy variable. Indeed, counting how many clients the bank will lose, is just a small step removed from evaluating how much business (money) the bank will lose, so why shall we not do things transparently?

Inserting reputational risks in a global transparent and easy to understand perspective for the organization will allow proper prioritization and a sensible risk management plan.
Corporations do need to “do business in a better way”, and in my mind that has to be coupled with sensible, transparent holistic and “homogeneous” understanding and prioritization of risks.
So, let’s try to summarize: reputational risks come as an additional component to other risks.
Example 1: a wrong communication from a bank can generate a damage of 50,000$ to a couple clients, with the annual probability of 1/25, but it is estimated that the reputational component would “multiply” that damage by 100 (so, now we have 5.05M$) when scores of clients run away from that bank.
This way of thinking allows proper prioritization of risks.
Example 2: the bank has another operational risk that could generate a damage of 3M$ with the same annual probability of 1/25. It looks that this second risk is higher than the one of Example 1: WRONG conclusion, because the first risk has a strong reputational component (5.05M$ is larger than 3M$, at same probability).
We have several real life examples of this: a) a small rock falls from a cliff, damages a vehicle inspecting a railroad, and the whole worker’s union goes to strike because the railroad is unsafe, b) a high-tech company runs a fire drill which goes very bad and the whole city starts a blockade because they panic over the “corporate unpreparedness”.

It is only once tolerability thresholds are added in the p-C plot that proper prioritization of complex risk portfolios can be rationally achieved, by comparing the “intolerable part” of each risk scenario.
Now, if you want to read about a “small risk” that ended up costing an arm and a leg to a famous US airline, please look at
Post1 and Post2

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