The So Risk Program

Reads: 1014  | Likes: 0  | Shelves: 0  | Comments: 0

More Details
Status: Finished  |  Genre: Other  |  House: Booksie Classic
In the mid-eighties, snow-thrower manufacturing firm Toro, launched a promotion where purchasers of snow blower could refund a part of their purchase in the event that the next winter was characterized by modest snowfalls. The amount of money that was refunded was related to the amounts of snowfall thus putting the program at certain risks as well as uncertainties. This paper explores the choices made by the company and the risks linked to the S’No Risk program.

Submitted: February 05, 2015

A A A | A A A

Submitted: February 05, 2015

A A A

A A A



 

 

 

 

The S’No Risk Program

Student’s Name:

Institutional Affiliation:

 

 

 

 

 

 

 

 

Table of Contents

1.0 Introduction. 3

2.0 Risk Analysis. 3

2.1 Toro’s Perspective. 3

2.2 American Home Assurance Perspective. 3

2.3 Consumer Perspective. 4

3.0 Insurance Rates. 4

3.1 Consumer Perspective on Payback Structure. 5

4.0 Decision Making Process. 5

4.1 Influence of program on purchase. 5

4.2 Decision Traps. 6

4.3 Decision Matrix. 6

4.4 Consumer Regret 8

5.0 Success of the S’No Risk Program.. 8

5.1 S’No Risk Program Prospects. 9

6.0 Conclusion. 10

References. 11

 

 

 

 

 

 

The S’No Risk Program: An Analysis

1.0 Introduction

In the mid-eighties, snow-thrower manufacturing firm Toro, launched a promotion where purchasers of snow blower could refund a part of their purchase in the event that the next winter was characterized by modest snowfalls. The amount of money that was refunded was related to the amounts of snowfall thus putting the program at certain risks as well as uncertainties. This paper explores the choices made by the company and the risks linked to the S’No Risk program.

2.0 Risk Analysis

2.1 Toro’s Perspective

In the year that the program ran, Toro carried a risk that was relative to the highest amount they would pay out to American Home Assurance would be approximately USD 680,000 in 1983 and at the same time gain a profit of USD 160,000 (Bell, 2004). In the same year that the S’No Risk promotion, several elements were involved: the American Home Assurance company made an error in quoting the 2.1% figure as cover of the snowthrower retail value; the snowfall that was experienced was significantly higher when compared to the previous year, however, the presence of the premium cap by American Home Assurance, Toro did not lose out on its liabilities shorts. In addition to this, the company did not pay the usual 10% discount to its 26 distributors in the fall. This translated to an 8% profit for the company.

2.2 American Home Assurance Perspective

The American Home Assurance company bore the highest risk with the running of the S’No Risk program. The insurance company had agreed to meet all customers’ claims at 2.1% of the covered snowthrowers retail value (Bell, 2004). The total rebates in the promotion year stood 19%. Toro was able to hedge its losses while the insurance company absorbed 17% of the rebates costs. In the event that Toro would continue with the S’No Risk program the premium rates would increase to 8% of the sales total. This amount was from an average of the previous four years of Toro’s actual payouts. The insurance company would attempt to recoup losses as Toro was forced to bear part of the risk in the year that experienced heavy snowfall. The snowfall could not be controlled either predicted which in essence created the uncertainty factor of the insurance cover.

2.3 Consumer Perspective

The consumer perception of the promotion is that of no-risk and to that end, they were able to utilize the offer by purchasing and/or upgrading larger models of the equipment (Bell, 2004). With the absence of the S’No Risk program would leave a dissatisfied consumer in the event they purchased a snowthrower and there were no snow; and if the consumer opted not to purchase and there was record high snow falling. The program offered a win situation for the consumer as it eliminated the aspect of uncertainty in the purchasing decision-making process.

3.0 Insurance Rates

American Assurance Insurance had to increase the premium rates for Toro so as to spread their risk over a group or individuals so as to remain in operation. The insurance firm used previous snowfall recordings and past claims to formulate the average number of purchases of snowthrowers. In addition, the fact that there was a 19% payout in the period running in 1982-1983 the insurance firm had to factor this when presenting the new premium at 8% of sales (Bell, 1994). Using hindsight, if the S’No Risk program had been available the previous three years, then the insurance firm would have quoted a rate that was based on the 1979-1982 average payouts. Thus, the figure would be 4.3 % as opposed to the quoted 2.1%. The unpredictability of the weather complicates the analysis of risk by any actuarial scientist and hence, I would be no exception; I would utilize a similar formula as that of the insurance firm in determining an insurance premium rate that was fair to the customers

3.1 Consumer Perspective on Payback Structure

The S’No Risk payback structure presented a win-win situation for the snowthrowers customers. The basis of the payback structure rested solely on the snow weather patterns reported in the different regions where the average snowfall was the determinant factor. The sliding scale was inclusive of a complete refund of a 100% in areas where the weather stations recorded an average snow fall of below 20% and a 50% refund for average snowfalls that were below 50%. In order for the promotion to be improved, it would mean that Toro would have to lower the average snowfall to below 10% for a customer to get a 100% refund and a refund of 50% refund for snow fall averages that were below 40%. In the improved scenario, the premium rates on insurance would be static for lack of a precedent set up prior to expected snow fall payouts and also for the simple reason that the new and higher incentives would lead to high sales of units.

4.0 Decision Making Process

4.1 Influence of program on the purchase

Compromise and uncertainty are the key decision-making aspects that would impact my decision as a customer to purchase a snowthrower. As mentioned, weather is uncertain and not knowing the amount of snowfall that would fall within a given season would play a role in my purchase decision-making. As a consumer, my focus will be, as stated by Kahneman (1984), on mental accounting of the purchase of a unit within the snow season without analyzing its use in the following years. I would anchor my decision on the previous years’ snow fall amounts and either under or overestimate the current year amounts. (Simonson, 1992).

4.2 Decision Traps

Decision traps affecting all players in the program are inevitable. The consumer faces the decision trap on anchoring where he gives preference to the most prevalent information at hand. If he chooses to overestimate the lack of snowfall amounts based on the previous year’s recorded amounts, he may opt to buy a snowthrower based on the sliding parameters of the S’,No Risk program. According to Kahneman (1979), the consumer could face the pseudo certainty effect of the prospect theory where he is either risk-averse or risk-acceptant based on the snowfall patterns. The customer, under the S’No Risk program, faces no real risk because program or no program, he still needs a snowthrower with the prospect of reduced cost being higher. However, if the customer is risk averse, he may overestimate the amounts of snowfall and opt out of purchasing a snowthrower

4.3 Decision Matrix

The premium rates that were to be used were determined by the insurance company using anchoring had Toro opted to extend the promotion to the following year. The fact that the insurance company had lost money with the 2.1% rate, it used this as an anchor to set a disproportionate weight at 8%. The S’No Risk program was based on Toro’s anchor in predicting the snowfall amounts for preceding years which in their estimate would not be a repeat of previous years had the promotion been extended.

 

 

 

 

 

Anchoring Prospect Theory






C:\\Users\\Graffix\\AppData\\Local\\Temp
C:\\Users\\Graffix\\AppData\\Local\\Temp

Toro Company

 

 

C:\\Users\\Graffix\\AppData\\Local\\TempC:\\Users\\Graffix\\AppData\\Local\\Temp

Broad: Risk averse or risk acceptant.

 

Specific: risk averse as program was discontinued. High premium rates retained.

Specific: Successful program not repeated in 1983

 

Broad: Weight given to the small number of consumers that were refunded the previous year

 

 

 

 

 

 







C:\\Users\\Graffix\\AppData\\Local\\Temp
C:\\Users\\Graffix\\AppData\\Local\\Temp
 

 

 

 

 

 

 

 

 

 

 

 

 

4.4 Consumer Regret

The S’No Risk program presents no buyer remorse and offers the consumer the opportunity to purchase a snowthrower with no regret and at their individual terms. In the event that the consumer purchases a unit and there is no snowfall then he will be dissatisfied. On the other hand, if there is snowfall then the purchase of the unit will be worth it. Under the S’No Risk program the consumer will be satisfied either way; whether it snows or not, a purchase of the snowthrower will be worth the while. If the consumer does not purchase the snowthrower even after being offered the S’No Risk rates and it happens to snow then he will regret his decision of, not purchasing a unit; and if the snow fails to fall he will still be dissatisfied because had he purchased it then he would have gotten a full refund hence gotten the snowthrower for free.

5.0 Success of the S’No Risk Program

The program S’No Risk program was a big success for all stakeholders: Toro, the customers, and the snowthrower dealers. Toro experienced an increase in sales and even went ahead and had an extra 2500 units assembled offseason. This translated to an increase in the company’s profits. The overall net sales in 1983 grew by an average of 8% as compared to the previous year. The capped premium of 2.1 % offered by American Home Assurance was quite low and played in favor of Toro. The rebate sliding scale offered a great opportunity for the consumers to own snowthrowers at minimal risk with customers from high snow fall amount areas experiencing the lowest overall risk- if there was snowfall they would utilize their purchase and if the snow failed then they would own snowthrowers at no cost after a full refund from Toro. The success of the program was however not experienced by American Home Assurance mainly because the capped premium rate of 2.1% was too low given the favorable weather patterns experienced in 1983. The payout amount totaled to USD $630,508 (Bell, 1994) and could have been USD 5.8M at a rate of 19%.

5.1 S’No Risk Program Prospects

Toro Company under my management would face a few changes. Thought the S’No Risk program was a success in 1983, it may have been purely due to fate from Mother Nature. As it is, fate can or cannot repeat itself. The company would have a number of varying options for its dealers and customers that would benefit the company in all possible case scenarios. The purchase dates for the snowthrowers would be more restricted to cover a smaller period so as to reduce the number of any potential refunds. Secondly, the S’No Risk would cover the two stage machines so as to drive their sales up as the one stage machines already enjoyed relatively high sales per annum. Thirdly, the distribution outlets would have two options; to offer their clients the 10 rebate or the complete S’No Risk package. The options would be given after the determination of the low-risk areas. This would also be utilized to boost sales in the low sales seasons.

However, as the manager of Toro Company, I would opt to discontinue the S’No Risk program based on the two factors of uncertainty and complexity. The fact that the weather is unpredictable increases uncertainty and this in turn increases the risk that ultimately outweighs any possible rewards the company could experience. Based on the actuarial calculations made by Carol, the premium rates would need to be increased fourfold from the previous year that would then put it close to the 10% discount already offered. In addition, the weather may be unfavorable to Toro in the event that there is indeed a period of low snowfall amounts which would result in high amounts being paid out which would then affect the company’s bottom line. Further, the complexity factor will be due to the additional administrative load linked to customer refund claims.

6.0 Conclusion

This paper has discussed the novel S’No Risk program ran by Toro and insured by the American Home Assurance. The program offered a sliding scale refund to its customers for purchases of snowthrowers and was based on the amount of snowfall experienced in mapped out regions. The program was a success for the company, its customers and dealers. However, despite this success, Toro opted to discontinue the program after determining that the risks outweighed the benefits mainly because of the uncertainty factor of the weather.

 

 

 

 

 

 

 

 

 

 

References

Bell, D. E. (1994). The Toro company s’no risk program. Harvard Business School. Case No. 9-185-017.

Kahneman, D., & Tversky, A. (1984). Choices, values, and frames. American Psychologist, 39(4), 341–350. doi: 10.1037/0003-066X.39.4.341

Simonson ,I., Tversky, A. (1992) Choice in Context: Tradeoff Contrast and Extremeness Aversion. Journal of Marketing Research, 29 (3). pp. 281-295

 



© Copyright 2017 Master Papers. All rights reserved.

Other fall school high nature novel american free choice lost theory home experienced experience hand key uncertainty bear winter mother simple snow fate continue leave lose past success thought inevitable money reason seasons perception determined presence perspective mental close making remorse weather choices predicting decision compromise journal paper lead faces four contrast role changes machines 984 cap without structure next rested regret ahead play fair created low error year elements real essence situation insurance under needs paid remain due group may stated according below amount within areas controlled offered involved linked information record three mentioned possible spread impact based result event forced research business related worth marketing face translated years sales line effect value fact stage management mean presents season opportunity pay running values analysis individual models individuals falling factor harvard operation gain full weight great hindsight failed trap satisfied own process risk meet period turn does affect following unpredictable snowfalls bore cost win 99 influence benefits already knowing company determination heavy uncertain potential sliding complete 9- higher discount matrix favor either launched lack bell retail customers complexity payback traps customer risks references profits program restricted scientist net similar significantly distribution played purchasing promotion order additional usual 34 figure cover assurance ran indeed gives 39 introduction repeat offer absence cannot table enjoyed grew putting previous case scale buy per carried covered carol dates given highest stood whether 3- focus able ultimately recorded despite larger lower anchor manager options certainty dissatisfied exception static attempt extended solely relative extra load package aspects aspect 37 further losses happens terms modest purchased shorts rewards however patterns determinant conclusion toro regions costs prospects psychologist unit experiencing addition bottom certain itself thus smaller total firm average increased rate increase basis equipment expected reported scenario purchase opposed consumer uncertainties 98 prior stations claims chooses analyzing affecting current rebate actual predicted offers players compared factors benefit frames reduce dealers agreed boost assembled accounting absorbed actuarial administrative affiliation amounts anchoring approximately averages averse aversion blower buyer calculations capped clients complicates manufacturing hedge pseudo 983 profit context purely rates premium formula snowfall improved hence 994 estimate discussed units 979 doi minimal win-win fails refund increases contents totaled gotten consumers reduced 68 overall unpredictability purchases lowest presented recordings preference 63 inclusive presenting payouts prospect prevalent secondly outlets payout scenarios quoted extend characterized stakeholders pp mainly favorable varying unfavorable recoup utilized decision-making relatively opted insured determining institutional incentives distributors liabilities usd mapped quoting mid-eighties snow-thrower purchasers refunded explores snowthrower snowthrowers rebates no-risk utilize upgrading eliminated formulate 979- precedent kahneman overestimate simonson opt parameters risk-averse risk-acceptant disproportionate preceding snows offseason risk- 8m refunds annum thirdly low-risk discontinue outweighs fourfold outweighed tversky 66x tradeoff extremeness

Booksie 2017-2018 Short Story Contest

Booksie Popular Content

Other Content by Master Papers

Popular Tags