# Clean & Brite Company's New Product: Probability Of Success Or Failure

Pages: 4 Words: 890

## Question :

Scenario

You are to undertake a study to find out whether the company Clean & Brite needs to market a new brand of toothpaste.

Case Study

A product manager at Clean & Brite (C&B) wants to determine whether her company should market a new brand of toothpaste. If this new product succeeds in the marketplace, C&B estimates that it could earn \$1,800,000 in future profits from the sale of the new toothpaste. If this new product fails, however, the company expects that it could lose apprcoximately \$750,000. If C&B chooses not to market this new brand, the product manager believes that there would be little, if any, impact on the profits earned through sales of C&B’s other products. The manager has estimated that the new toothpaste brand will succeed with probability p = 0.35. Before making her decision regarding this toothpaste product, the manager can spend \$130,000 on a market research study. Based on similar studies with past products, C&B believes that the study will predict a successful product, given that the product would actually be a success, with probability 0.8. It also believes that the study will predict a failure, given that the product would actually be a failure, with probability 0.7

a. To maximise expected profit, what strategy should the C&B product manager follow?

b. Calculate and interpret EVI for this decision problem with p = 0.35. Then use a data table to find EVI for p from 0.05 to 0.70 in increments of 0.05, and chart EVI versus p.

c. Using the analysis from part b, find the EVSI when p = 0.15. T

d.calculate and interpret the EVPI when p = 0.35.

• Construct a spreadsheet model with decision tree.
• Develop a solution for C&B, and write your recommendation in the form of a report.

ASSESSMENT ELEMENTS

• Report.

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Quantitative Management Practice

Clean & Brite Company Case Study

Introduction

The product Manager of Clean & Brite is under the dilemma if she should introduce a new brand of toothpaste in the market. The new product can be success or a failure. The report analyses the probabilities of success and failure of the new product and its effect on the profitability of Clean & Brite.

Background to the Problem

Clean & Brite determines that if the new product is a success than it will earn \$1,800,000 as profits to the company in future form the sale of new product. However if the new product fails, the company will incur the cost of \$750,000. On the other hand if C&B does not market the new brand, its profit from existing products will be same and there will be no impact on its profits.

C&B will introduce the new product if considering the probability of its success there is expected profit.  The manager estimates that the new toothpaste brand will be successful with the probability p = 0.35. However, the company can buy additional information on market research for \$130,000.  The market research will predict the success of the product, given that the product would actually be a success, with p = 0.8 and will predict a failure, given that the product would actually be a failure, with p =  0.7.

Strategy To maximize the Profit (QA)

C&B is looking for the strategy to maximize the expected profit to the company. The manager of C&B can take a decision on this only when the probability for success and failure of the new product are determined and evaluated for the expected profit.

Firstly, the expected profit is determined without the additional information. The manager of C&B predicts the success of the product p = 35%.

Secondly, the expected profit is determined with the additional marketing information.  Considering that the actual probability of success of the product is 0.35 and using the information provided by the marketing company, it is determined that the probability that they predict success of the new product is 47.50%. This means that their prediction for the failure of the new product is 52.50%. The probabilities are calculated as shown in Table 1 below:

Table 1: Probabilities of predictions

 Event Calculations Probability of correct prediction Prediction of Success of the product (0.35x0.80) + (0.65 x 0.30) 0.475 Prediction of failure of product (0.35 x 0.20) + (0.65 x 0.70) 0.525

The posterior probabilities are predicted for the decision tree from the above data. The posterior probabilities are shown in table 3 below.

Table 2: Posterior probabilities given predictions

 Actual/ Predicted Success Failure Success 0.5895 0.4105 Failure 0.1333 0.8667

Using the decision tree, all the possible outcomes for the success and failure of the product given the additional information are mapped. Diagram 1 outlines the various options available to Clean & Brite. The detailed analysis is under the tab labeled Q.A in the attached spreadsheet.

Diagram 1: Decision tree on expected profitability with or without additional information

It can be seen in diagram 1, that given the p= 0.35 for the success of the product, if the additional information is purchased the  expected profit of the company increases.  The expected profit without additional information is \$142,000. The expected profit with the additional information is \$227,750 after taking into account the additional cost of information.

Thus the Marketing manager of C&B should buy the additional information. It is also seen in the diagram that the Expected profit is maximum if the product is launched on the prediction of success in additional information and not launched on the prediction of failure in the additional information.

The following strategy is recommended to C&B :

 Decision: Choose to Buy Information If Information Says Product will be a success: Launch the product If Information Says Product will be a failure: Don’t launch the product

EVI for this decision problem with p = 0.35 (QB)

The additional information provided by the marketing company is useful to C&B but only for a certain range of probability of success. The information is worth buying only when the probability of success of product is more than 0.25. Below this probability the cost of gaining information is more than the benefits derived.

The expected value of Information at p = 0.35 is \$227,750. This EVI includes the cost of information of \$130,000.  The EVI for probabilities form 0.05 to 0.70 at intervals of 0.05 is presented in the table below.

Table 3: Expected Value of Information (EVI)

 Probability (p) EVI 5% \$         (130,000) 10% \$         (130,000) 15% \$         (105,250) 20% \$           (22,000) 25% \$              61,250 30% \$           144,500 35% \$           227,750 40% \$           311,000 45% \$           394,250 50% \$           477,500 55% \$           560,750 60% \$           650,000 65% \$           777,500 70% \$           905,000

The Chart of EVI vs P is as below:

It can be seen in the above table and chart that the buying of information is useful only when he actual probability of success of the product is more than 25%

EVSI when p = 0.15 (QC)

The EVSI given the p= 0.15 is -\$105,250. Since the probability is less than 25%, the expected value of information is negative. Thus the cost of information is more than the benefit derived from it. The EVSI includes the cost of information.  Table 4 below shows the EVSI for the given probability.

Table 4: Expected value of s ample information (EVSI)

 Probability (p) EVI EV Without information EVSI 5% \$         (130,000) \$                      - \$        (130,000) 10% \$         (130,000) \$                      - \$        (130,000) 15% \$         (105,250) \$                      - \$        (105,250) 20% \$           (22,000) \$                      - \$          (22,000) 25% \$              61,250 \$                      - \$            61,250 30% \$           144,500 \$             15,000 \$          129,500 35% \$           227,750 \$           142,500 \$            85,250 40% \$           311,000 \$           270,000 \$            41,000 45% \$           394,250 \$           397,500 \$            (3,250) 50% \$           477,500 \$           525,000 \$          (47,500) 55% \$           560,750 \$           652,500 \$          (91,750) 60% \$           650,000 \$           780,000 \$        (130,000) 65% \$           777,500 \$           907,500 \$        (130,000) 70% \$           905,000 \$       1,035,000 \$        (130,000)

The table shows that the EVSI is positive only the given range of probability from 0.25 to 0.40.

EVPI when p = 0.35 (QD)

The information provided by the marketing company is not perfect. The information is useful only for a given range of probability. However if the information provided by the marketing company was perfect, the information  would be more valuable to C&B. Considering that the information provided is perfect and that the success of the product is predicted to be a success and failure 100%  correctly for each event. The EVPI  at p = 0.35 is \$487,500 as follows:

 Note: The EVPI does not include the cost of information of \$130,000 Perfect Information Expected Profit: \$        500,000 Basic Information Expected Profit: \$        142,500 Comparison of Expected Values: \$        357,500 Expected Value of Perfect Information: \$        487,500

Conclusion

IT is concluded that Clean & Brite should purchase the additional information from the marketing company provided that the probability of the Success of the product is more than 25% and less than 45%. If the probability is outside this range the cost of information will not maximize the profits.

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