A Gathering Evil (Fiddleback 01 - Dark Conspiracy)

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All too often, event risk managers get off base, simply because the politics of the situation make it impossible for them to work. Politics is the art of the possible; know what is possible and go there.

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Time your proposals and reports carefully. To illustrate these principles better, assume that you are plan- ning a major celebration in your community. Now, as- sume that a famous movie star from this community is returning to appear at the celebration. Even before accepting the position, it is critical that you decide how comfortable you are working in this situation. Do famous people intimidate you?

Can you stand up to the media scrutiny? How well do you deal with people who may be reluctant or even adverse to giving you the data that you re- quest? Then ask yourself who are the major stakeholders. Review the description of conflict theory found in Chapter 1 and ask your- self what does each group want before, during, and after the event.

For example, our movie star may be seeking publicity, showing her in a wholesome light for a new movie she is making.

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How do these different agendas shape your understanding of event risk? Is your role to be a security guard or an event manager? Does every- one in town know why you are there or did someone else hire you without seeking local approval? Once you have determined if you are comfortable with the job and with your bosses, you can begin to list assumptions about the event.

How close to re- ality are you or are you creating problems that barely exist while overlooking problems that may be ubiquitous? Now, you need to review the material found in Chapter 1. Be careful to constantly check yourself. As you prepare for the town celebration, are you reverting to old patterns? Have you practiced good listening skills and are you willing to redo the plan if new data become available?

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At the end of this chapter are guidelines for improving your lis- tening skills. Listening may be the single most important skill that a risk manager needs to develop. Principles of Gemba Kaizen Much of this chapter examines decision-making theory. Despite what many people believe, few event risk managers have all or even most of the data needed to make informed decisions. Indeed, in a classical hierarchical system, those on top of the pyramid, that is to say, those who have the most power, often have the least knowledge.

Executives often are not on site and they often must use highly filtered information. Even if event managers could spend large amounts of their time at the point of contact, there is no way that they could be at all points of contact. Where one goes to look for information may be as important as what information one gathers.

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In the case of a wedding, should the risk manager only confer with the bride and groom or would he or she want to interview people such as the caterer, florist, and parking lot attendant? The Japanese have tried to circumvent this system by use of what they call Gemba Kaizen. For example, it would be hard to assess and con- trol the risks of a celebrity wedding if the event risk manager did not attend the event. Select a project. Understand the current situation and objectives.

Analyze data to identify root causes. Establish countermeasures.

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Implement the countermeasures. Confirm the effect. Even in this system, which the Japanese developed for manu- facturing purposes, choices must be made as to observation points. In event risk management, the situation is further complicated as event managers must be concerned about selling the product the event , producing the product the trade show, convention, festi- val , and being certain that the product staging the event is de- livered to the consumer in a safe and timely manner.

The first set of questions that a risk manager must ask is: How does he or she receive information? Is the information conveyed from direct observation, from empirical or factual sources, or from intuitive sources? Following is a brief summary of the types of event risk information that can be gathered and examples of how it is used in event risk management.

Routine inspections of an event site location, for example, may re- veal potential risk.

Thus, the event risk manager cannot actually observe risk. The best that he or she can do is to assume that a particular situation can result in the po- tential for harm. Thus, even in the most empirical of event cases, the event risk manager must rely on his or her own professional intuition from past events. For example, let us suppose that floors have been waxed just prior to an event. As long as the risk is in the future, it is only a mere hypothesis.

We might argue that waxing makes floors slippery. However, the fact that the floors are slippery might make people extra cau- tious.

Thus, the waxed floors might also cut down on slippage. The risk might take place on the floor; however, the person may be so busy watching his or her step that he or she does not see the low ceiling and bumps into it. One might imagine that older peo- ple have a higher potential for slipping, but it may be children who slip due to the shiny floors inviting them to try and see if they can slide.

Summary in 20 words or less:

Event risk managers should keep careful records. For example, who slipped and where, what was the age breakdown, and did men and women exhibit different patterns? There can be no future data, but rather we use data from past events to assume that, under similar circumstances, fu- ture events of a similar nature may occur. Of course, as the popu- lar television advertisement reminds people: Past performance is no guarantee of future action.

Where might the event risk occur? Under what circumstances would this event risk occur? Who might be at the event? What is the risk of conducting this event? In the example of the waxed floor, there is no guarantee that people will slip on a newly waxed floor, but past history tells us that slippery floors are more dangerous than nonslippery floors.

The assumption that the past can be a helpful predictor of the fu- ture is the basis of science. Thus, we assume that a person who is inebriated and whose faculties are impaired has a greater chance of being in an accident while driving than one who has not been drinking alcohol. Of course, there is no guarantee that the inebri- ated driver will be in an accident or that the sober driver will not be in an accident.

The most we can do is create a working hy- pothesis: Under similar circumstances, there is a higher probabil- ity that a drunk driver will crash his or her car than a sober driver. Data are only as good as the way that they are formulated. For example, if no records are kept on where people come from, then even the most careful data analysis will not reveal a distinction between local and foreign visitors. Without the correct variables, the risk manager is at a loss. Event risk managers, then, must not only analyze the variables correctly, but also know which vari- ables to analyze.

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