Program Risk Analysis (Essay Sample)

Title: Program risk analysis
Learner’s name
Institutional affiliation
The promotion of goods is a marketing strategy, through which companies create loyalty in their customers. The selling of goods at promotional prices encourages customers to purchase from the enterprise in the future. Toro introduced a promotion in the sale of their snow blowers in the early eighties. The promotion involved a refund to the customers, for their purchase, in the case of modest snowfall in the subsequent winter after purchase. This paper presents an analysis that seeks to explore the possible implications of the promotion, from three different views. The analysis of promotion risks bases on the views of the customer, company as well as the insurers.
Risk analysis from Toro’s point of view
While the general view of the program shows some likelihood of risk, the risk level of the program, from Toro’s point of view is low. From the case study, looking at their payout for the year of 1983, the company pays 680 thousand dollars ($680K), leaving sums amounting to $106K as profit. The risk level of the project could easily be misinterpreted if the happenings over the period are not put into consideration. During the period of the promotion, the insurance company made an error in the quotation of 2.1% of the snow blowers retail price covered. During the same month, the level of snowfall significantly increased in comparison to the previous year. As a result of the premium cap, the insurers accepted liability. The case further reveals that the company did not have to pay the normal 10% discount to the dealers, as it did in the fall. As a result, the company benefited by registering a 8% profit increase, as well as keeping their retailers and customers happy.
Insurance company’s point of view
From the assessment, the highest risk befell the insurance company. In compliance with their agreement with the enterprise (client), they covered 2.1% of the snow blowers’ retail value (Bell, 2004). As recorded in the case study, the cumulative number of rebates over the period of promotion was 19%. The coverage of the costs was shared between Toro and the American Home Assurance company, with the latter covering 17% of the rebate costs. Despite the challenge that the company faced with the promotion program over the period, there were still chances of continuing with it, after a few adjustments. One of the necessary adjustments would be increasing the premium to about 8% of the total sales. The increase would be equivalent to the average payouts the company had made over the four last four years. The consequence of the increase would be; an increase in rates by the insurer, to recover the loss. Nevertheless, the continued implementation of the promotion exposes Toro to significant risks, whose costs must be partly covered by the company. The presence of the risk lies in the nature of snowfall that can hardly be predicted nor controlled.
Customer’s point of view of the risk analysis
The consumer is the only party with no risk involved in the promotion program. The desire of any customer is to have security for expenditures made. The occurrence of snow can hardly be predicted, and hence the purchase of snow blowers would at some point look like a gamble. Due to the uncertainty in the occurrence of the snow, some customers would opt not to purchase, until it the snow occurred. The purpose of the promotion program was to give the customers an assurance of their expenditures, in that; if the snow failed to occur, they get a refund. For this reason, it was a win-win for the customers, since regardless of what happened, they would either use their product or get a refund. The running of the promotion highly benefits the customers, and motivate them to buy the snow blowers, without worrying about the chances of the snow occurrence in the subsequent winter. For this reason, the stoppage of the promotion would likely demotivate the customers, who would begin to worry about the associated risks of buying the product, in the case the snow did not occur. In this regard, the likelihood would be a decline in the average sales registered by the company, since many of the customers would prefer waiting for the occurrence of the snow, before making purchases.
What caused an increase in insurance rates?
The rise in the insurance rates was triggered by the payout costs incurred in 1982. Due to the unpredictability of the occurrence of snow, the insurance company required analysis of the past data, in the determination of the appropriate payout rates. Based on the business activities that occurred between 1982/83, the insurance company determined that there was need to increase the rates, hence distributing the risks across the stakeholders. Since the insurer had previously registered an increase in the payout by 19%, it was logical to determine a new premium rate, which was quoted at 8%. This determination of the rates was based on two years, and therefore, if it was based on the previous three years, the company would use the rate of 4.2%, instead of the quoted 2.1%. Due to the unpredictability attached to the scenario, the determination of the actual risk in the promotion was difficult. If I were the insurer, I would have resolved to use the same formula, in the determination of rate to be applied to the Toro customers’ payouts.
Examination of the customer’s view of the payback structure
The customers enjoyed the payback structure since it was a win-win for them. The payback structure guaranteed the clients of the benefit of their purchases. The provisions of the promotion were that the customer would either get enjoy the services of the machine during the snow period or in the case the snow never occurred, a full or partial refund was offered. The first win aspect of the payback structure was that; any customer purchasing the snow blower machine needed not to worry about if the snow would occur, and in case it occurred, the machine serves its purpose. The determination of the snow occurrence was based on the weather station, which reported the levels of snow over the covered period. If the reported snow level were less than 20% of the average snow level, the company would give 100% money back. In the event the snow level was less than 50%, Toro would refund 10% of the purchase price, with the best part of the deal being that; the customer kept the machine for future use. Looking at the payout structure, it was a win for the customers, regardless of the level of snow that occurred. If Toro needed to continue the implementation of the promotion, keeping the risk level at a lower side, they needed to consider adjusting the provisions of the premium. The improvement would involve adjusting the full refund snow level from 20% to 10% or below. The percentage required for partial refund should also be adjusted 40% or below, hence lowering the occurrences of refund.
As a customer for the snow throwers, the ability to make a sound decision lies in the capacity to eliminate uncertainty (Peters, 2005). In this case, the uncertainty in the occurrence of the snow, as well as the snow level affects the consumer decision-making process. The consumers tend to focus on the current seasons, at the expense of the subsequent ones. The decision of the consumer not to buy the snow blowers proves costly in the event of the snow occurrence.
The conjoint decision traps
The decision-making traps cannot be overlooked in this analysis. All the parties involved are likely to be faced with common decision traps of varied intensity. The consumers are the party most likely to be faced with the common decision traps. The statistics of the snow occurrence may influence the consumer’s decision to purchase the snow blower machine. For instance, if the previous year experienced hid snow downpour, the pseudo-certainty effect may take the course, leading to the consumer’s decision to buy (Roebuck, 2012). The payout structure does favor the consumer, and hence the decision to purchase the machine may be easier since the customer has nothing to lose.
The insurance company applies the focalism (anchoring) theory in its decision on the appropriate premium rates. Assuming that Toro continued with the promotion, the insurer would make a decision on the premium rates, based on the data of the previous period. Toro would also apply the same theory to decide on the appropriate rates, in the efforts to avoid the repeat of losses encountered in the prior period.
The decision matrix
Consumer
* General: the insurer gives weight to the information initially received.
* Specific: by overestimating or underestimating the possible snow in the subsequent year, the insurer is subjected to negative or risk-acceptant.
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