Risk Analysis in Theory and Practice, Essay Example

In the case of someone breaking in to the office vending machine at least twice a month, getting no more than $15 to $20, it can be concluded that the workplace has lost at least $180 given that the act was ongoing for the span of six months. The problem is not so much catching the perpetrator in the act, but being able to stop him/her. Setting up the camera where the vending machine is placed would only catch the person in the act, and this would take time also.

It is not denied, however, that the person committing the act should not be caught. Although, this would entail that the security in the office would need to watch out for the act, and wait for the person to commit the crime once again.

Setting a camera security system up would cost a lot more than the money being stolen from the vending machines. However, if the time span on the said stealing were to lengthen, and the amount of money being taken were to rise, then getting a camera would be a good idea.

Other discoveries also may be found if ever the workplace does install a security camera system to watch out for the person taking money from the vending machine. We can find out not just who it is, but we can see if anyone else performs acts which are not socially acceptable in the same room. This would make the installation of the cameras more of a long-term investment if the purpose of the installation were not only for this one specific incident. It can also stop other similar incidents from occurring, and the right perpetrators will be caught (Viscusi, 2000).

I would present my idea and security program to management, in a way which makes the installation of the cameras more of a company investment. Right now, the first thing the company wants is to catch the person taking the money, however other problems may arise in the future. Installing a camera system in the workplace would lower the risks of such acts to occur, and it will provide more security for the working environment. Stealing is not the only case a camera system would be able to stop, and this is how the plan shall be presented to the company.

Probabilities are statistical problems concerning outcomes and are written as numbers. In a coin toss, there are two probabilities which can happen, either the it will be heads or tails, you cannot get both at the same time (Mellor, 2005). Anything can happen, and it is not something which is definite and certain. Coin tossing uses percentages of chance and probability.

Probability does not directly tell one what is going to happen, it is just something which gives you an idea of the most likely outcome. For example, it is least likely in a coin toss that if someone tosses ten coins at once, that all of the coins will be heads; however, if the person tossing the coins tries for long enough, the chances of this happening will be higher. Also, if you toss a coin fifty times, and all times it turns out to be heads, it is not most likely that the fifty-first time you toss the coin it will be tails (Mellor, 2005). The odds still will stay the same, which is 50% for each side.

These coin tosses are “independent events” which means that the coin cannot decide for itself what will happen next (Mellor, 2005). It is unlikely that a coin can be tossed six times in a row and all the times it landed, it showed to be heads. Therefore the least likely has already occurred and has manifested in the results of the coin tossing. However, this does not mean that the seventh time the coin is tossed, the outcome will be the same, nor does it mean that it will be different. The same odds of the seventh time a coin is being tossed is much similar to the first time the coin is tossed, the odds remain at 50%. Therefore, the probability of me winning in the next coin toss, and the probability of the coin coming up to be tails still stays the same, and it’s likeliness of being tails does not depend on past events. My chances, as well as my friends’ chances both stay the same at 50%.

Over the years, people have tried to figure out as much as they could regarding safety risks (Jensen, 2002). This is through figures and probabilities for people to have a bit of an idea of the outcomes when an action is done, sometimes no action is done and it is something that just happens. There are basic methods of analysis for risks, and these methods include the classic fault-tree analysis and software reliability on topics such as expert opinions and risk management and regulations (Dickson, 2005).

Problems which occur in real life that include decision making, in particular those which are related to high-risk events which rarely occur can be a very complex area of study. This is because data on such events are very limited, and this makes statistical methods unusable (Dickson, 2005). The reason for this is because risk analysis depends on statistics and probability. Risks are based on what occurred previously, in contrary to the coin-tossing probability experiment.

The basic philosophy of risk analysis asks the question of “what is uncertainty”. This question discusses risk analysis in itself; there is no certainty in risk analysis. It is logical connections made with information, data and statistics gathered from previous events. It is the conclusion which is made based on what past events predict to be most likely. There are of course adverse outcomes, and these are weighed out by the probability of them least likely to happen. However, it does not mean that these events are never going to happen.

References

Dickson, D.C.M. (2005). Risk Analysis in Theory and Practice. Economic Record, 81(254).

Jensen, U. (2002). Probabilistic Risk Analysis: Foundations and Methods. Journal of the American Statistical Association 97(459); 925

Mellor, D.H. (2005). Probability: A Philosophical Introduction, London: Routledge.

Viscusi, W.K. (2000). Corporate Risk Analysis: A Reckless Act?. Stanford Law Review, 52(3).