Chapter 13 Inventory Management For The Month

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Given the monthly usages in the following table, classify the items in A, B, and C categories according to dollar usage. Determine the percentage of items in each category and the annual dollar value for each category.

The following table contains figures on the monthly volume and unit costs for a random sample of 16 items from a list of 2,000 inventory items at a health care facility:

• K34: $10, 200 units
• D4B: $12, 90 units

Develop an A-B-C classification for these items. How could the manager use this information? After reviewing your classification scheme, suppose that the manager decides to place item P05 into the A category. What are some possible explanations for this decision?

A large bakery purchases flour in 25-pound bags, using an average of 1,215 bags annually. Preparing an order and receiving shipment costs $10 per order, with annual carrying costs of $75 per bag.

• Determine the economic order quantity (EOQ).
• Calculate the average number of bags on hand.
• Find the number of orders per year.
• Compute the total cost of ordering and holding flour.
• In case holding costs increase by $9 annually, assess how this impacts the EOQ and total costs.

The firm uses approximately 40 boxes of copier paper daily over 260 working days annually. Storage and handling costs are $30 per year per box, with order and receipt costs of about $60 per shipment.

• What order size minimizes annual ordering and carrying costs?
• Calculate the total annual cost using this optimal order size.
• Are the annual ordering and carrying costs always equal at EOQ?
• Should the office switch from an order size of 200 boxes to the EOQ? Justify your recommendation.

Garden Variety Flower Shop uses 750 clay pots monthly, purchased at $2 each. With annual carrying costs estimated at 30% of the cost and $20 per order, the current order size is 1,500 pots.

• What is the additional annual cost incurred by sticking with the current order size?
• Besides cost savings, what benefits does the optimal order quantity provide?

A produce distributor uses 800 packing crates each month, bought at $10 each, with an annual carrying cost of 35% of purchase price.

Sample Paper For Above instruction

In inventory management, categorizing items efficiently is crucial for optimizing costs and improving operational effectiveness. The fundamental principle involves classifying inventory items into categories A, B, and C based on their dollar usage, which accounts for their significance in the total inventory value. This method, known as ABC analysis, assists managers in focusing their attention and resources on the most critical items, thereby enhancing inventory control and reducing unnecessary costs.

Applying ABC analysis begins with the collection of usage data and unit costs, as exemplified in the given tables. For instance, high-cost items with substantial usage figures tend to fall into category A due to their significant contribution to overall inventory value. Conversely, lower-cost, less-used items are classified as B or C. Calculating the percentage of total dollar value contributed by each item allows managers to allocate resources proportionally, ensuring that critical items receive the appropriate focus. Typically, approximately 70-80% of the total value is attributable to roughly 10-20% of the items, which defines category A, while the remaining items are spread across categories B and C based on their contribution percentages (Harris, 2006).

In practical application, the manager can use this classification to determine optimal inventory levels, reorder points, and safety stock quantities. For example, critical and high-cost items in category A warrant closer monitoring and more frequent orders, minimizing stockouts and excess inventory. Conversely, items in category C, which contribute minimally to overall value, can be ordered less frequently and in larger quantities to reduce ordering costs (Nahmias, 2013).

Suppose the manager decides to move an item like P05 into the A category after initial classification. Several reasons could explain this decision. Firstly, P05 might have experienced an increase in usage or unit cost, elevating its dollar value contribution. Alternatively, strategic supply considerations, such as criticality to operations or supply risk, might justify its reclassification. It is also possible that recent supplier changes or stockout incidents have highlighted the importance of closely managing this item, prompting a shift into category A to ensure priority focus (Chopra & Meindl, 2016). Such reclassification helps allocate managerial attention effectively and optimize inventory performance.

In the case of the bakery buying flour, the Economic Order Quantity (EOQ) model offers a systematic way to determine the ideal order size that minimizes total inventory costs, including ordering and holding costs. The EOQ formula is expressed as EOQ = sqrt(2DS / H), where D is annual demand, S is ordering cost, and H is holding cost per unit (Heizer, Render, & Munson, 2016). Substituting the given values (D=1,215 bags, S=$10, H=$75) yields EOQ = sqrt(21,21510/75) ≈ 20 bags. This calculation suggests that ordering approximately 20 bags each time balances ordering and holding costs efficiently.

Annual quantities directly influence average inventory levels, which are typically half of the EOQ, thus about 10 bags. The number of orders per year is calculated as D/EOQ, resulting in roughly 61 orders annually. Total costs include ordering costs (number of orders multiplied by per-order cost) and holding costs (average inventory multiplied by holding cost per unit). If holding costs increase by $9 to $84, the EOQ increases slightly according to the square root relationship, indicating a marginal rise in total costs, emphasizing the sensitivity of EOQ to holding cost fluctuations (Silver, Pyke, & Peterson, 1998).

Similarly, for office paper, the EOQ helps determine the most cost-effective order size by balancing ordering and holding costs. Using the EOQ formula with D=40 boxes/day 260 days =10,400 boxes annually, S=$60, H=$30, the EOQ is estimated at sqrt(210,400*60/30) ≈ 200 boxes. This aligns with the current order size, but small adjustments could lead to cost savings. If the current order size differs from the EOQ, it indicates potential for efficiency improvements. Transitioning to the EOQ minimizes combined ordering and holding costs, leading to cost savings over time.

In the context of the flower shop's use of clay pots, maintaining an order size different from EOQ incurs additional costs due to overstocking or frequent replenishments. For instance, maintaining a larger batch size than EOQ increases holding costs without proportional decrease in ordering costs. As a result, staying with the current size of 1,500 pots entails higher annual costs compared to an optimal order quantity. Conversely, optimal ordering benefits include reduced inventory holding, improved cash flow, and optimal stock levels that meet demand without excessive surplus (Waller, 2004).

The produce distributor’s use of packing crates similarly benefits from an EOQ approach. With monthly usage equivalent to D=800 crates, annual demand D=9,600 crates. Using S=$10 and H=35% of $10 = $3.50, the EOQ calculation results in approximately 96 crates per order. By adhering to this order quantity, the distributor minimizes total inventory costs, balancing frequent smaller orders with higher ordering costs against larger, less frequent orders with higher holding costs. Re-evaluating with updated costs or demands ensures continuous optimization (Bowersox, Closs, & Cooper, 2013).

In conclusion, ABC classification and EOQ models are vital tools in inventory management, allowing organizations to optimize costs, improve stock control, and enhance operational responsiveness. Strategic use of these techniques leads to cost-efficient inventory policies, better resource allocation, and increased competitiveness in dynamic markets.

References

• Bowersox, D. J., Closs, D. J., & Cooper, M. B. (2013). Supply Chain Logistics Management (4th ed.). McGraw-Hill Education.
• Chopra, S., & Meindl, P. (2016). Supply Chain Management: Strategy, Planning, and Operation (6th ed.). Pearson.
• Harris, F. (2006). Modern Inventory Management. John Wiley & Sons.
• Heizer, J., Render, B., & Munson, C. (2016). Operations Management (12th ed.). Pearson.
• Nahmias, S. (2013). Production and Operations Management (7th ed.). McGraw-Hill Education.
• Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory Management and Production Planning and Scheduling (3rd ed.). Wiley.
• Waller, M. A. (2004). Inventory Management: Principles and Practices. Journal of Business Logistics, 25(1), 93-118.