Events Plus is a professional company that conducts seminars for businesses and government organizations. They conduct seminars on a wide variety of subjects, some of which are very popular and some that are not so popular. Naturally, they want to make a profit on all of their courses. There are expenses involved in every course and if they do not get enough participants in each course, they will lose money. The challenge for Events Plus is to figure out how to manage their risks so that they make as much profit as possible and can continue to do business. This report is a risk analysis of the Events Plus business.
Events Plus has documented the results of their seminar offerings for the past eighteen months, which give us enough data for some risk analysis. They offer a discount for attendees who pay for the offered courses at least six weeks prior to the course. They want to be able to determine the likelihood of a seminar being conducted, and turning a profit, at the six-week mark.
Data from the past eighteen month’s shows that out of one hundred-ten offerings, seventy-six of the seminars were conducted. A total of thirty-four seminars were cancelled, either due to illness or lack of enrollment. In order to determine viability of a seminar, Events Plus uses enrollment at the six-week mark as an indicator of profitability. They break the seminars down into three categories: break even at the six-week mark, almost break even at the six-week mark, and not near the break-even mark at six weeks. Table 1 shows the breakdown of seminars for the past eighteen months.
The last column in the table shows the overall probability of the seminar being held based on the past eighteen months. This figure is derived by multiplying the probability number in the first column with the probability number in the second column. This represents the conditional probability of holding an event.
One tool that will help Events Plus management determine whether to continue with a seminar is a decision tree. The decision tree associated with Table 1 is below:
The break-even point is determined based on whether or not there is at least seventy percent enrollment six weeks prior to the seminar date. Almost means that there is at least ninety percent enrollment six weeks prior to the seminar date. With the decision tree, management can determine the probability of a seminar actually happening and make informed decisions about cancelling seminars that might lose money.
Using the information provided in table one and the decision tree allows us to determine the probability of seminars happening, based on past performance. The probability that Events Plus will reach the break-even point at six weeks and ultimately hold the seminar is eighteen percent. This number is derived by taking the percentage of seminars that were at the break-even point at the six-week marker and multiplying that number by the percentage of these seminars that were actually held . In this case, twenty percent of the total number of seminars offered broke even at six weeks prior to the seminar. Of this twenty percent, a total of ninety-one percent of the seminars were conducted. The twenty percent multiplied by the ninety-one percent yields that probability of eighteen percent.
The same calculation will tell us the probability that Events Plus will nearly reach the break-even point at the six-week marker and still hold the seminar. Table 1 shows that they nearly hit the break-even point at the six week point thirty percent of the time and these seminars were conducted seventy percent of the time for all probability of twenty-one percent.
When asked about the probability that Events Plus will not reach the break-even point six weeks prior to the seminar but still hold the seminar anyhow we just have to look at table 1 again. This table shows that fifty percent of the seminars had not reached the break-even point or even nearly reached the break-even point at the six-week marker. In spite of this, they still held the seminar sixty percent of the time. This means that they have a thirty percent probability of holding a seminar that did not get near the break-even point at the six-week marker and are at risk of holding the seminar at a loss.
Another way for Events Plus to determine risk is to consider the expected value of the seminars. In order to do this, we need to consider the costs associated with conducting seminars as well as the potential revenue produced by the seminars. In the case of Events Plus, the average cost of conducting a seminar is $32,000. This amount is lost completely if the seminar is not conducted. The average revenue for a seminar, after preparation costs are deducted is $20,000. In order to figure the expected value of a seminar we first compute the expected revenue of the seminar, based on the probability of it being conducted and then subtract the expected cost of the seminar based on the probability of it being cancelled (Frame, 2003). The result should give an expected value for the seminar based on its probability of occurring.
Using this formula, we can determine the expected value of a seminar given that they have reached the break-even point at the six-week marker. Given that Events Plus expects to net $20,000 from a successfully completed seminar, we can multiply that amount by the probability of the seminar being conducted (91%) and come up with an amount of $18,200. We then figure the expected loss if the seminar is cancelled by multiplying the total cost of the seminar ($32,000) by the probability of a breaking even seminar being cancelled (9%). This gives us a figure of $2,880. By subtracting the potential loss figure from the potential gain figure, we come up with an expected value for a seminar that has reached the break-even point at the six-week marker as $15,320. This shows that it makes good business sense to hold the seminar if it is at the break-even point at the six-week marker.
Next, we can figure the expected value of a seminar given that it is near to reaching the break-even point at the six-week marker. These are the seminars that had reached seventy to ninety-five percent of the break-even point at the six-week marker. Based on data from the past eighteen months, Events Plus held seventy percent of the seminars that were near the break-even point at six weeks. If we multiply the $20,000 expected profit by seventy percent, we get a value of $14,000. When we multiply the total cost of the seminar ($32.000) by the percent that the near break-even seminars were cancelled (30%), we get a value of $9,600. Subtracting the $9,600 from the $14,000 we come up with an expected value of $4,400 for seminars that almost reach the break-even point at the six-week marker. Although this is not a great amount, it shows that it still makes good business sense to hold the seminar.
Finally, if we consider seminars that have not reached the break-even point at the six-week marker, we come up with an entirely different result. When figuring the possible profit from seminars that do not reach the break-even point we multiply the $20,000 expected profit by the sixty percent completion rate for a figure of $12,000. By multiplying the $32,000 cost to conduct the seminar by the forty percent cancellation rate, we acquire the figure of $12,800. Using these figures shows that the expected value of conducting a seminar that does not reach the break-even point at the six-week marker is a negative eight hundred dollars, which means that it does not make good business sense to hold the seminar.
It is easy to determine the probability of Events Plus actually holding a seminar once it begins preparing it. To do that we just need to look at the seminars that it actually completed in the past eighteen months. We can take the total number of seminars completed (76) and divide it by the total number of seminars offered (110) for a probability of sixty-nine percent, or we can simply add the overall probability percentages from the right hand column of Table 1 for the yes lines to achieve the same number.
When it comes to risk analysis, there are no clear answers. The purpose of risk analysis is to help management make informed decisions to minimize risk and increase profits. Probability analysis using historical data is one way to try to project likelihoods for the future. Managers may not use all of the information provided by risk analysis. They may choose to continue with a project, or seminar in the case of Events Plus, even if it runs the risk of losing money based on other factors like good will, training, experience, and needs. By tying additional information, such as seminar topics and intended audiences to the seminars that do not break even, managers can help limit loses by changing the nature of the seminars offered and not expending resources on seminars that run a high probability of being cancelled. The important thing to remember with risk analysis is that it is just one tool available to management to assist them in making informed decisions.
References
Frame, J. D. (2003). Managing Risk in Organizations: A Guide for Managers. San Francisco: Jossey Bass.
