Case Study: Martin Pullin Bicycle Corporation

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Case Study Martin-Pullin Bicycle Corporation Martin-Pullin Bicycle Corporation (MPBC), located in Dallas, is a wholesale distributor of bicycles and bicycle parts. Formed in 1981 by cousins Ray Martin and Jim Pullin, the firm’s primary retail outlets are located within a 400-mile radius of the distribution center. These retail outlets receive the order from Martin-Pullin within two days after notifying the distribution center, provided that the stock is available. However, if an order is not fulfilled by the company, no backorder is placed; the retailers arrange to get their shipment from other distributors, and MPBC loses that amount of business. The company distributes a wide variety of bicycles.

The most popular model, and the major source of revenue to the company, is the AirWing. MPBC receives all the models from a single manufacturer overseas, and shipment takes as long as four weeks from the time an order is placed. With the cost of communication, paperwork, and customs clearance included, MPBC estimates that each time an order is placed, it incurs a cost of $65. The purchase price paid by MPBC, per bicycle, is roughly 60% of the suggested retail price for all the styles available, and the inventory carrying cost is 1% per month (12% per year) of the purchase price paid by MPBC. The retail price (paid by the customers) for the AirWing is $170 per bicycle.

MPBC is interested in making the inventory plan for 2012. The firm wants to maintain a 95% service level with its customers to minimize the losses on the lost orders. The data collected for the past two years are summarized in the following table: A forecast for AirWing model sales in the upcoming year 2012 has been developed and will be used to make an inventory plan for MPBC. Discussion Questions 1. Develop an inventory plan to help MPBC. 2. Discuss ROPs and total costs. 3. How can you address demand that is not at the level of the planning horizon?

Paper For Above instruction

The objective of this paper is to formulate an effective inventory management strategy for Martin-Pullin Bicycle Corporation (MPBC), focusing on the AirWing model. Given the company's supply chain constraints, demand variability, and service level goals, the plan aims to balance supply with anticipated demand while minimizing costs associated with ordering, holding, and stockouts. The analysis incorporates demand forecasts, lead times, safety stock calculations, and review policies to establish optimal reorder points and order quantities that align with the company's target service level of 95%.

Forecasting Demand for 2012

To develop an inventory plan, accurate forecast data is essential. Past sales data over 2010 and 2011, along with projections for 2012, are critical inputs. Assuming the sales are seasonal with deviations observable, statistical methods such as moving averages or exponential smoothing would refine forecast accuracy. For this case, suppose the forecasted monthly demand for 2012 is derived by averaging past data, adjusted for seasonality, resulting in an annual demand estimate. For illustration, let's assume the forecasted total annual units required for 2012 is 6,000 units, averaging approximately 500 units monthly.

Reorder Point Calculation and Safety Stock

The lead time for sourcing the AirWing model from overseas suppliers is four weeks (approximately one month). To prevent stockouts at a 95% service level, safety stock must be incorporated into the reorder point (ROP). The safety stock calculation considers demand variability during the lead time and the desired service level's z-score (approximately 1.65 for 95%).

Average demand during lead time (DLT) = Monthly demand = 500 units

Standard deviation of demand during lead time (σLT):

If historical demand standard deviation per month is known, say σ = 50 units, then:

σLT = σ × √Lead time in months = 50 × √1 ≈ 50 units

Safety stock (SS) = z × σLT = 1.65 × 50 ≈ 83 units

Reorder Point (ROP) = DLT + SS = 500 + 83 ≈ 583 units

This means that once inventory drops to approximately 583 units, a new order should be placed to replenish stock, considering the four-week lead time and safety buffer.

Economic Order Quantity (EOQ) and Total Cost Analysis

To minimize total costs—ordering, holding, and stockout costs—EOQ models are employed. The cost parameters are:

- Ordering cost (S): $65 per order

- Cost per bicycle (C): 60% of retail price, i.e., 0.6 × $170 = $102

- Annual holding cost per unit (H): 12% × $102 = $12.24

Using the EOQ formula:

EOQ = √(2DS / H)

where D = annual demand = 6,000 units,

EOQ = √(2 × 6000 × 65 / 12.24) ≈ √(780,000 / 12.24) ≈ √63,725 ≈ 252 units

Thus, the optimal order quantity per replenishment cycle is approximately 252 units, balancing ordering and holding costs.

The total annual inventory cost comprises:

- Ordering costs: (D / EOQ) × S = (6000 / 252) × 65 ≈ 23.8 × 65 ≈ $1,547

- Holding costs: (EOQ / 2) × H ≈ (252/2) × 12.24 ≈ 126 × 12.24 ≈ $1,542

- Stockout costs are minimized at this optimal EOQ, and assumptions of negligible backorders align with the 95% service goal.

Addressing Demand Uncertainty Beyond Planning Horizon

Demand variability over time presents challenges, especially for unforeseen fluctuations outside the forecast horizon. Strategies include:

1. Implementing a flexible safety stock policy: Adjust safety stock levels dynamically based on real-time demand data.

2. Using rolling forecasts: Update demand forecasts regularly to reflect recent trends.

3. Developing partnerships with multiple suppliers: Reduce lead time variability and increase supply chain resilience.

4. Employing responsive replenishment strategies: Incorporate quick-turnaround suppliers or local sourcing for short-term demand spikes.

5. Applying demand shaping techniques: Promotions or pricing adjustments to influence demand patterns.

Effective management of demand variability ensures MPBC can maintain high service levels without incurring excessive holding costs or stockouts, even beyond initial planning periods.

Conclusion

The inventory plan for MPBC involves calculating the optimal reorder point, safety stock, and order quantity to meet the 95% service level aim while minimizing costs. By implementing an EOQ-based ordering system with safety stocks aligned to demand variability, MPBC can efficiently manage its inventory. Continuous demand monitoring and flexible adjustment to safety stock levels will further enhance responsiveness to demand fluctuations, ensuring sustained customer satisfaction and profit maximization.

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