Probability Analysis For Harley Davidson's General Manager

Probability Analysis A General Manger of Harley Davidson

The task involves analyzing the decision of a General Manager at Harley-Davidson regarding the choice between building a large or small facility based on demand predictions and associated payoffs. The analysis employs probability theory, decision trees, and expected monetary value (EMV) calculations. Data provided include demand scenarios, probabilities, actions, and payoffs for each facility size, culminating in an objective comparison to inform the best strategic choice.

Paper For Above instruction

Deciding on the optimal facility size is a critical strategic decision for Harley-Davidson’s management. This decision hinges on predicting market demand, estimating associated payoffs, and evaluating the risk and return of each option through probability analysis and decision theory principles. The core challenge involves applying probability concepts, constructing decision trees, and calculating expected monetary values (EMV) to support a rational, data-driven decision.

Understanding the Context and Data

The company contemplates two primary options: constructing a large or small facility. The demand is uncertain, categorized as either low or high, with respective probabilities. For the small facility, the demand probabilities are 0.4 for low and 0.6 for high. Similarly, for the large facility, the same demand probabilities are assumed. Payoffs depend on the demand scenario and subsequent managerial actions, which include doing nothing, reducing prices, expanding, or taking overtime. The payoffs reflect the anticipated returns under different demand conditions and management decisions.

Calculating Probabilities and Payoffs for Each Option

To evaluate these options, the first step involves determining the expected payoffs associated with each demand scenario. For example, with a small facility under low demand, the payoff is $40, and the probability is 0.4. Under high demand, the payoff increases to $55, with a probability of 0.6. The expected payoff for the small facility is thus calculated by multiplying each payoff by the respective demand probability and summing the results: (0.4 × $40) + (0.6 × $55) = $16 + $33 = $49.

For the large facility, the payoffs under low and high demand are $50 and $70, respectively, with the same demand probabilities. Its expected payoff is (0.4 × $50) + (0.6 × $70) = $20 + $42 = $62.

Assessing the Expected Values

The calculations suggest that the large facility has an expected payoff of $62, surpassing the small facility's expected payoff of $49. This indicates that, on average, the large facility is more profitable considering the probability-weighted payoffs. The decision to proceed with a particular facility size can thus be informed by comparing these expected values, a core principle of expected monetary value analysis.

Constructing the Decision Tree

A decision tree visually depicts the sequence of events, uncertainty, and choices. The initial node splits into two branches for the two facility options. Each branch leads to demand scenarios with associated probabilities, which further branch out based on potential management actions (like do nothing, reduce prices, expand, overtime). Each terminal node contains the payoff. Computing the EMV involves multiplying each payoff by its pathway's probability and summing across the branches related to each decision. The calculations confirm the preferential choice: the large facility with an expected value of $62 versus $49 for the small facility.

Implications for Strategic Decision-Making

Based on the probabilistic analysis, the decision favors building the large facility, owing to its higher expected payoff. This quantitative approach allows Harley-Davidson to make a rational choice under uncertainty, emphasizing the importance of considering both the likelihood of demand scenarios and the associated payoffs. While the expected value favors the large facility, managers should also consider other factors like risk tolerance, capacity constraints, and strategic objectives beyond numerical analysis.

Conclusion

Applying probability analysis and expected monetary value calculations reveals that constructing a large facility offers a higher expected return ($62 versus $49 for the small) under the given demand scenarios and payoffs. This analytical approach aids Harley-Davidson’s management in making informed investment decisions, balancing potential gains against uncertainties. The decision aligns with maximizing expected value, although strategic considerations should still influence final choices to encompass risk preferences and corporate goals.

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