Council Of Supply Chain Management Professionals 333 East BU

Council Of Supply Chain Management Professionals 333 East Butterfield

Cleaned assignment instructions: Analyze a case involving Silo Manufacturing Corporation (SMC) regarding their inventory management strategies, specifically focusing on economic order quantity (EOQ), ordering costs, inventory holding costs, and the impact of managerial goals on supply chain decision-making. Address several specific questions assessing the cost implications of different ordering policies, applying EOQ principles, and proposing actionable solutions to reduce overall ordering costs.

Sample Paper For Above instruction

Supply chain management is a complex discipline that involves balancing various costs, including ordering costs and inventory holding costs, to optimize overall operational efficiency. The case of Silo Manufacturing Corporation (SMC) offers a rich context to explore these concepts, especially through the lens of economic order quantity (EOQ), which serves as a mathematical tool to determine the optimal order size that minimizes total inventory costs.

In the case, SMC faces internal conflicts between its financial and purchasing departments, each advocating for different ordering policies driven by their respective performance goals. The financial comptroller, Fred Ferguson, emphasizes minimizing inventory carrying costs, advocating for small, frequent orders, while the purchasing director, Peter Patrachalski, aims to reduce ordering costs by purchasing larger quantities less frequently. The company's leadership seeks a balanced approach using the EOQ model, but several variables influence the optimal order quantity, including demand rate, ordering costs, inventory holding costs, and constraints such as ordering in whole cases.

Fundamental to understanding the decision-making process is the original Harris-Wilson EOQ formula, developed in 1913 and later refined through different models that incorporate discounts, backordering, transportation costs, and multiple warehouses (Harris, 1913; Wilson, 1934). The classical formula assumes constant demand, instantaneous delivery, and no interaction among items, which, although idealized, provides a valuable starting point for practical application (Coyle et al., 2009).

Applying EOQ calculations to SMC involves considering the specific data provided: annual demand of 10,752 units, unit cost of $112, ordering cost of $48 per order, and inventory carrying cost rate of 32%. Using the basic EOQ formula:

Q = sqrt[(2 D * S) / H],

where D is annual demand, S is ordering cost, and H is the annual holding cost per unit (H = unit cost × carrying rate), leads to a calculated EOQ of approximately 2,785 units. Since orders can only be made in whole cases (units per case = units per case), adjustments are necessary to align with practical constraints, affecting total costs and managerial decisions.

The first key question involves comparing the total annual costs for proposals—ordering 4 cases (approximate to 448 units) versus 32 cases (approximate to 2,560 units)—highlighting how smaller, frequent orders result in higher ordering costs but lower inventory costs, and vice versa. Calculations show that ordering 4 cases annually leads to higher total costs compared to ordering 32 cases, emphasizing the importance of identifying the true EOQ to minimize total cost (Hax & Candea, 1984).

Moreover, analyzing the sensitivity of total cost to rounding the EOQ to the nearest whole case reveals the concept of cost robustness. Minor deviations from the optimal EOQ lead to slight increases in total costs, which underscores the importance of accurate demand forecasting and flexible policies for real-world applications.

As the organization aims to reduce overall inventory levels by 8.9%, adjustments in ordering policies are necessary. For example, to meet this goal, the order quantity may need to decrease, which would also entail increasing order frequency—potentially raising total ordering costs unless the ordering cost per order is reduced. In scenarios where demand increases due to sales growth, and carrying costs decrease owing to efficiency initiatives, the EOQ must be recalculated to ensure optimality (Coyle et al., 2009).

Implementing just-in-time (JIT) principles involves further altering the optimal order quantity, ideally down to a single unit, to minimize holding costs. However, the economic feasibility depends on the ability to reduce ordering costs significantly and maintain reliable supply chain operations. Recommendations for lowering ordering costs include negotiating bulk discounts with suppliers, streamlining procurement processes through automation, and contracting with third-party logistics providers to reduce logistical expenses (Heizer & Render, 2017).

In conclusion, the case of SMC exemplifies the need for a nuanced application of EOQ, considering organizational goals, practical constraints, and dynamic variables. Strategies to optimize inventory management should incorporate continuous review and adjustment, leveraging technological advancements and supply chain partnerships to achieve cost reduction and inventory efficiency.

References

• Coyle, J. J., Langley, C. J., Novack, R. A., & Gibson, B. J. (2009). Supply Chain Management: A Logistics Perspective (8th ed.). Mason, OH: Southwestern Cengage Learning.
• Harris, F. W. (1913). How Many Parts To Make At Once. Factory, The Magazine of Management.
• Hax, A. C., & Candea, D. (1984). Production and Operations Management. Englewood Cliffs, NJ: Prentice-Hall.
• Heizer, J., & Render, B. (2017). Operations Management (12th ed.). Pearson Education.
• Wilson, R. H. (1934). A Scientific Routine for Stock Control. Harvard Business Review.