Case Study Bell Computer Company

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Title ABC/123 Version X 1 Case Study – Bell Computer Company The Bell Computer Company is considering a plant expansion enabling the company to begin production of a new computer product. You have obtained your MBA from the University of Phoenix and, as a vice-president, you must determine whether to make the expansion a medium- or large-scale project. The demand for the new product involves an uncertainty, which for planning purposes may be low demand, medium demand, or high demand. The probability estimates for the demands are 0.20, 0.50, and 0.30, respectively.

Case Study – Kyle Bits and Bytes Kyle Bits and Bytes, a retailer of computing products sells a variety of computer-related products. One of Kyle’s most popular products is an HP laser printer. The average weekly demand is 200 units. Lead time (lead time is defined as the amount of time between when the order is placed and when it is delivered) for a new order from the manufacturer to arrive is one week. If the demand for printers were constant, the retailer would re-order when there were exactly 200 printers in inventory. However, Kyle learned demand is a random variable in his Operations Management class.

An analysis of previous weeks reveals the weekly demand standard deviation is 30. Kyle knows if a customer wants to buy an HP laser printer but he has none available, he will lose that sale, plus possibly additional sales. He wants the probability of running short (stock-out) in any week to be no more than 6%.

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The decision faced by the Bell Computer Company regarding its expansion project involves analyzing the uncertainty associated with demand levels for the new computer product. This analysis requires careful consideration of the relative probabilities of low, medium, and high demand scenarios and the subsequent impacts on project scale and profitability. Concurrently, Kyle Bits and Bytes’ challenge revolves around inventory management of HP laser printers, where demand fluctuation and service level requirements must be balanced through appropriate safety stock calculations.

Assessing the Expansion of Bell Computer Company

The core of the decision for Bell Computer Company is whether to undertake a medium-scale or large-scale expansion. This analysis hinges on evaluating the expected value of the project’s outcomes based on demand uncertainties. The probabilities assigned to low (0.20), medium (0.50), and high (0.30) demand levels suggest that a probabilistic approach such as expected monetary value (EMV) analysis can guide the decision-making process.

To compute the EMV for the expansion, estimates of the potential revenues, costs, and profits associated with each demand scenario are necessary. For example, assuming the revenue and profit margins stay consistent across the demand levels, the expected demand can be calculated as:

Expected demand = (0.20 × low demand) + (0.50 × medium demand) + (0.30 × high demand)

Such an expected value provides a basis for scaling the project appropriately. A larger-scale project might incur higher fixed costs and risks but could also lead to significantly greater profits if demand materializes at the higher end. Conversely, a more conservative, medium-scale project might limit exposure to risk but potentially restrict growth.

Furthermore, the company should incorporate risk analysis techniques such as decision trees or Monte Carlo simulation to quantify the uncertainty and evaluate the robustness of each expansion option. Sensitivity analysis can help determine how variations in the demand estimates influence the optimal decision, adding depth to the strategic planning process.

Inventory Management and Service Level Optimization for Kyle’s Laser Printer

Kyle Bits and Bytes must determine the appropriate order quantity and safety stock level to maintain a service level that limits stock-outs to no more than 6%. This scenario is a classic application of inventory management principles, especially the calculation of safety stock under stochastic demand and lead time conditions.

The key parameters include: average weekly demand (200 units), demand standard deviation (30 units), lead time (one week), and the target stock-out probability (6%). Using these parameters, Kyle can employ the reorder point formula:

Reorder point (ROP) = (Average demand during lead time) + Safety stock

Since demand is variable, the safety stock is calculated based on the desired service level, typically using z-scores from the standard normal distribution. The z-score corresponding to a stock-out probability of 6% is approximately 1.55.

The safety stock (SS) is computed as:

SS = z × standard deviation of demand during lead time

Given the demand variability is weekly, and lead time is one week:

SS = 1.55 × 30 = 46.5 units

Thus, the reorder point becomes:

ROP = 200 + 46.5 ≈ 247 units

To maintain the desired service level, Kyle should place a reorder when inventory drops to approximately 247 units, ensuring the probability of stock-out in any given week remains below 6%. This safety stock buffer accounts for demand fluctuations and variability, effectively balancing the costs of excess inventory against lost sales.

Moreover, Kyle should monitor demand patterns periodically to adjust safety stock levels, especially if demand variability or lead times change over time. Advanced techniques, such as probabilistic forecasting and continuous review policies, can further optimize inventory levels and improve customer satisfaction.

Conclusion

The strategic decisions for the Bell Computer Company and Kyle Bits and Bytes highlight critical aspects of operations management—risk analysis for large investment projects and inventory optimization under demand uncertainty. Employing probabilistic models and decision analysis tools enables organizations to make informed, data-driven choices that optimize outcomes and manage risks effectively. Both cases demonstrate the importance of integrating demand forecast uncertainties, safety stock calculations, and strategic planning to navigate complex operational challenges successfully.

References

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