Problem Solving
Uncertainty challenges the process of decision-making. Organizations and individuals should apply the benefit-cost analysis to determine the risks associated with uncertainty. In the individual problem 17-2, the player is uncertain about whether to play the TV show game or not. Using the probability distribution, it is possible to evaluate the probable risks of playing the game. The current price of the contestants is $1 million. If their guess is wrong, the prices decrease to $500000 but if they are right the price goes up to $2million. Therefore, the possible outcome will be $500000 or $2 million. Since the opponent believes that his guess will be 50% right of the time, the probability of loosing automatically becomes 50%. Hence, the expected value of probable occurrence will be (1/2) (500000) + (1/2) (2M) which equates to an average of $1,250,000. This exceeds the price of the contenders and so the contestant should play the game (Froeb & McCann, 2007). The game is in its final round, thus the competitor will have to play only once. If the game is fair, the lowest probability of winning will be (50%) (1M) which will equate to 500000. Therefore, if the competitor wins, he will have a profit of $500000 on top of his price.
Problem 17-6 creates uncertainty for the HR manager during the hiring of recruits. The applicants have different levels of expertise. The manager has to verify the information given on the resumes. He is challenged on deciding the best candidate who will fit the vacant position. This creates uncertainty on whether to hire or not. This creates the problem of moral hazard since the manager is unable to distinguish the best candidates (Froeb & McCann, 2007). Therefore, he might end up hiring a recruit who is not fit and rejecting the one who has the capability of performing. The type 1 and II decision error costs associated with this problem are behavior monitoring cost and incentives compensation costs respectively.
In this situation, the CEO of the company will more likely notice the decision error of behavior monitoring. Since the manager was unable to distinguish the fit and unfit applicants, the probability of hiring both of them was equal. Therefore, the unfit employee, who will otherwise be underperforming, will always tend to hide the weaknesses and bad side. The HR manager will start observing the employee’s behaviors so that he can detect the underlying issue (Froeb & McCann, 2007). This will further lead to punishment for the worker. This will affect the hiring decisions of the HR manager in the future. He will always be under pressure to make the right decision because the CEO noticed the previous errors. He might become stricter and introduce Assessment strategies to analyze recruits before beginning full employment. Consequently, he will make better hiring decisions.
At the start of 2019, the company established a new product to the market and the target audience comprised of youths between the ages of 20-35. The product was set to sell at $250. According to research, 78% of the customers were willing to purchase the product but at a lower price of $225. Only a few people were willing to pay $250. There was uncertainty about the best price that would make both the high and low-income earners purchase the product (Froeb & McCann, 2007). Considering that the product had reached customer satisfaction, the company decided to settle on a price of $220 so as to benefit from the majority in the market. However, several risks would be anticipated like change in customer preference and sale of a similar product by a competitor at a ridiculously low price.
By reducing the price of the product, the company will earn more sales revenue since many people will do the purchase. On the other hand, it will incur production costs which will take time to recuperate. Therefore, the benefits of the decision can be computed as follows: selling at $220 will incur loss of $30 per product, ($250-$220), from the initial selling price of the product. However, this will be compensated since everybody will but at this product. Therefore, the benefits will be (0.78) ($30) $23.4. The company should adopt this decision since it guarantees a return on sales (Froeb & McCann, 2007). Since the customers who were willing to pay $250 constituted 12%, the profit will increase by the same value, (0.12) (23.4) $2.808. Therefore, total profit will be $23.4 +$2.808 =26.208. This will increase the revenue of the company with time.
References
Froeb, L., & McCann, B. (2007). Managerial Economics: A Problem Solving Approach. Boston, MA: Cengage Learning.
