A General Manager Of Harley Davidson Has To Decide On The Si
A General Manger Of Harley Davidson Has To Decide On the Size Of a New
The management of Harley Davidson faces a strategic decision regarding the expansion of its manufacturing capacity by choosing between constructing a large or a small facility. This decision involves analyzing potential demands, associated payoffs, and the probability of various demand scenarios. The goal is to select the option that maximizes expected monetary value (EMV), thereby optimizing the company's financial outcome based on probabilistic assessment.
To facilitate this decision, a detailed probability analysis and decision tree model are employed, incorporating the estimated payoffs and their associated probabilities. By systematically calculating the expected payoffs for each alternative—building a small or large facility—the management can make an informed choice grounded in quantitative data. The decision-making process involves evaluating the likelihood of low and high demand scenarios, their respective payoffs, and deriving the expected values, which guide the optimal strategic choice.
Paper For Above instruction
Introduction
The manufacturing industry, especially in the motorcycle sector, is highly sensitive to market demand fluctuations. Harley Davidson’s decision on facility size impacts production capacity, operational costs, and potential revenue. Selecting the optimal facility size requires careful analysis of demand probability, payoffs under different demand conditions, and the expected monetary value of each option. This paper evaluates these factors, constructs a decision tree, and determines the best strategic alternative for Harley Davidson’s expansion plan.
Analysis of Demand and Payoffs
The company considers two options: constructing a small or large facility. Each option encompasses different demand scenarios—low and high—and corresponding payoffs. For the small facility, the payoffs vary depending on demand, with the associated probabilities. Similarly, the large facility has its own set of payoffs for low and high demand scenarios.
The payoff calculations are grounded in the potential revenues and costs associated with each demand scenario. For the small facility, the payoffs are $40 (low demand) and $55 (high demand). The probabilities of these demand levels occurring are 0.4 and 0.6, respectively. For the large facility, the payoffs are $50 (low demand) and $70 (high demand), with the same demand probabilities.
Step-by-Step Calculation of Chances and Payoffs
To determine the overall expected payoff for each facility size, the individual payoffs are weighted by the probability of each demand scenario. The calculations are as follows:
- Small Facility with Low Demand: 0.4 x $40 = $16
- Small Facility with High Demand: 0.6 x $55 = $33
- Large Facility with Low Demand: 0.4 x $50 = $20
- Large Facility with High Demand: 0.6 x $70 = $42
Expected Value of Each Alternative
Summing these weighted payoffs provides the expected monetary value for each facility size:
- Small Facility: $16 + $33 = $49
- Large Facility: $20 + $42 = $62
Based on these calculations, the large facility has a higher expected monetary value ($62) compared to the small facility ($49). This analysis suggests that, under the current probabilities and payoffs, constructing a large facility is financially the more advantageous strategy.
Decision and Strategic Implications
The decision to proceed with the large facility is supported by the above calculations, reflecting a higher expected payoff. However, additional considerations such as capital investment costs, risk tolerance, and long-term strategic goals should also be integrated into the final decision-making process. Accounting for these factors ensures a holistic approach that aligns with Harley Davidson’s broader corporate strategy.
Conclusion
By utilizing probability analysis and expected monetary value calculations, Harley Davidson’s management can confidently select the large facility option. The quantitative approach demonstrates that, given the current estimates, the large facility maximizes expected returns and aligns with the company's growth objectives. Future decisions should incorporate sensitivity analysis and scenario planning to refine the risk assessment and support robust strategic planning.
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