Biopure Corporation: A Quantitative Way for Deciding the Pricing and the Distribution Strategy for Oxyglobin

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Biopure Corporation: A Quantitative way for deciding the pricing and the distribution strategy for Oxyglobin

Note: such quantitative analysis is not required for your mid term exam. However, this note will be of interest to any student who is interested in knowing how to employ a rigorous way of computing the price and the subsequent distribution strategy.

Step 1: Calculating the total potential demand for Oxyglobin:

Critical cases: We can calculate the total potential demand for dogs for the critical cases in terms of units of blood as follows:

Itâ€™s given that the total no. of vet practices are 15,000. Out of these 5% (or 750) are emergency care practices and rest 14,250 are primary care practices. It is also given that a primary care practice on an average uses 17 units of donated blood and the emergency care practice uses 150 units per year. Therefore, the total demand for emergency care practices for the critical cases would be 150*750 units and that for primary care practices for the critical cases would be 17*14250 units. The total demand for critical cases would be 354750 units of blood.

Semi/Non Critical cases: Given the total units of blood for the critical cases, we can calculate the total units of blood for the semi critical cases. Itâ€™s given that the critical cases were 2.5% of the total cases and semi critical were 27.5%. Therefore the total demand for semi critical cases would be 354,750*27.5/2.5 =3,902,250 units.

Step 2: Estimating the demand curve

Refer to tables A and B of the case. Note itâ€™s given that the vets use a doubling rule, that is, they charge a price to the customers that is twice the price they pay to the company. Next, it is important to note what the decision tree would be for the consumers. First, Biopure sells Oxyglobin to the vets. If the vets decide to try the product, then they suggest Oxyglobin as an option to the pet owners. Finally the pet owners decide whether to use Oxyglobin or not. It is assumed that the vets double the price when they give Oxyglobin to the pet owner. The implication is that when we calculate the demand for Oxyglobin as a function of price to the vets using tables A and B, we need to multiply the probabilities given in tables A and B to get the total probability of the consumer using Oxyglobin at a given price to the vet. For instance, consider the critical cases. If Biopure charges 150 dollars to the vet, the probability that a vet would try it in the first place would be 80% (table A). Then given that the vet is willing to try Oxyglobin, he would charge 300 dollars to the pet owner. The probability that the consumer would try it at 300 dollars conditional on the vet trying Oxyglobin is given as 75% (table B). Therefore, the overall probability that the consumer will try Oxyglobin at a 150-dollar price to the vets will be 0.75*0.80. We can use this procedure to calculate the probability of the consumer choosing to use Oxyglobin at any given price to the vet (there are only 4 price points: 50, 100, 150 and 200) for both the critical and non-critical cases. This is shown as follows

Price to the vet

Non Critical Cases

Critical cases

Trial Probability for the vet

Trial probability for the customer given that the vet has tried

Overall trial probability for the customer

Trial Probability for the vet

Trial probability for the customer given that the vet has tried

Overall trial probability for the customer

0.315

0.75

0.015

0.39

Thus, we get the overall trial probability for both critical and semi critical cases for the 4 price points. Next, the total potential demand for the critical cases is given as 345750 units and for the semi critical cases is given as 3902250. Thus, if Biopure were to charge $50 per unit as the price to the vet, it implies that the demand from non critical cases would be 0.57*3902250 = 2224283 units and from the critical cases would be 354750*0.9=319275 units. Thus, we can calculate the total demand for Oxyglobin for each of the price points. This is shown in the following table:

Price