Case Analysis: Ski-Right
The case begins with Bob Guthrie, a retired physician and an avid skier, who realized that there was a need for a special ski helmet following the recent incidents that lead to serious head injuries for skiers. There were existing ski helmets in the market, but Bob believed that he had a chance to make helmets more appealing to the people, by adding new features. Bob took this idea as something that could not only be an outlet for his creativity, but as a way for him to make some money. He set out with the goal of making helmets that were attractive, safe and fun to wear. With this in mind, Bob came up with several ideas for his new helmet, which he named ‘Ski Right’.
Bob wanted his helmets to be attractive, so …show more content…
TR – LB – PP | $50,000-$13,000 | $20,000-$7,000 | -$2,000 (-$10,000) | -$5,000 (-$15,000) | | 4. CC – PP | $50,000-$30,000 | $20,000-$10,000 | -$2,000 (-$20,000) | -$5,000 (-$30,000) | | 5. CC – TR – LB | $50,000-$50,000 | $20,000-$20,000 | -$2,000 (-$35,000) | -$5,000 (-$60,000) | | Probabilities | 20% | 40% | 30% | 10% | |
OPTIONS | States of Market | | Excellent Market | Good Market | Average Market | Poor Market | EOL | 1. PP | $45,000 | $18,000 | $0 | $0 | $16,200 | 2. LB – PP | $38,000 | $14,000 | $2,000 | $5,000 | $14,300 | 3. TR – LB – PP | $37,000 | $13,000 | $8,000 | $10,000 | $16,000 | 4. CC – PP | $20,000 | $10,000 | $18,000 | $25,000 | $15,900 | 5. CC – TR – LB | $0 | $0 | $33,000 | $55,000 | $15,400 | Probabilities | 20% | 40% | 30% | 10% | |
Minimum EOL= $14,300
*Therefore, the least amount of loss will be incurred if Option 2 is chosen.
Expected Value of Perfect Information OPTIONS | States of Market | | Excellent Market | Good Market | Average Market | Poor Market | EMV | 1. PP | $5,000 | $2,000 | -$2,000 | -$5,000 | $700 | 2. LB – PP | $12,000 | $6,000 | -$4,000 | -$10,000 | $2,600 | 3. TR – LB – PP | $13,000 | $7,000 | -$10,000 | -$15,000 | $900 | 4. CC – PP | $30,000 | $10,000 | -$20,000 | -$30,000 | $1,000 | 5. CC – TR – LB | $50,000 | $20,000 | -$35,000 | -$60,000 | $1,500 | Probabilities | 20% | 40% | 30% | 10% | |
EVPI =EVwPI - max(EMV)
EVwPI =