Inventory Modeling
The process of inventory modeling entails analysis of mathematical techniques and models to set inventory levels and reorder points with the goal of matching inventory purchase order costs with demand. These techniques include some of the different inventory management models we’ve covered here on SOS Inventory including:
Economic Order Quantity (EOQ) – uses a formula to determine the number of items to order to reduce costs.
ABC Analysis – sorts products by categories, i.e. best sellers to determine which items to have the most of on hand.
Inventory Production Quantity – lets you know how many items to order with each batch. This is the most appropriate for parts.
If your business orders full inventory items, EOQ is a more suitable inventory model.
FIFO – first in, first out, assumes the first product received will be sold first.
Just-in-time – this approach minimizes inventory on hand and allows the business to order as orders come in.
Safety Stock – This is the amount of stock to keep on hand to cover what would be needed during the time it takes for a new shipment to arrive from the supplier.
Overall, the goal is to find the equilibrium between the timing and quantity of reorders to keep pace with the current demand levels. This is a simplification of many different moving parts which consider all the various scenarios that could cause shortages, delays, price fluctuations, etc. One could get as sophisticated as calculating variables associated with limits on certain facilities, depending on laws, regulations, etc. of the geographical location.
Example of Inventory Modeling
Scenario: The Banana Boutique
Scenario: The Banana BoutiqueThe Banana Boutique is a rather unusual store that sells—you guessed it—bananas! They offer various types of bananas, from the classic Cavendish to exotic varieties like Red Dacca and Burro. Their goal is to strike the right balance between stocking enough bananas to meet customer demand while minimizing costs associated with holding excess inventory.
- Economic Order Quantity (EOQ)
The Banana Boutique decides to use the EOQ model. Here’s how it works:
- Demand: On average, they sell 500 bananas per week.
- Ordering Cost: Each time they place an order, there’s a fixed cost of $50 (for paperwork, transportation, etc.).
- Holding Cost: Storing bananas incurs a weekly cost of $0.10 per banana (for refrigeration, space, etc.).
The EOQ formula is:
EOQ = \sqrt{\frac{{2DS}}{{H}}}
Where:
- (D) represents the annual demand (500 bananas/week × 52 weeks/year = 26,000 bananas/year).
- (S) is the ordering cost per order ($50).
- (H) is the holding cost per banana per year ($0.10).
Calculating EOQ:
EOQ = \sqrt{\frac{{2 \cdot 26,000 \cdot 50}}{{0.10}}} = 1,000
The Banana Boutique should order 1,000 bananas at a time to minimize total costs.
- Safety Stock
To account for unexpected fluctuations in demand (e.g., sudden banana bread trends), the boutique maintains a safety stock. They decide to keep an additional 200 bananas as a buffer.
- Reorder Point
The reorder point (ROP) is the ideal inventory level for placing a new order. It’s calculated as:
ROP = \text{{Lead Time Demand}} + \text{{Safety Stock}}
- Lead Time Demand: The time it takes for a new order to arrive (say, 2 weeks).
- Safety Stock: 200 bananas.
So:
ROP = (500 \text{{ bananas/week}} \cdot 2 \text{{ weeks}}) + 200 = 1,200 \text{{ bananas}}
When their inventory reaches 1,200 bananas, it’s time to reorder.
- ABC Analysis
The Banana Boutique classifies their bananas based on value and importance:
- Class A: High-value bananas (e.g., Red Dacca) that contribute significantly to revenue. They monitor these closely.
- Class B: Medium-value bananas (e.g., Cavendish). Moderate monitoring.
- Class C: Low-value bananas (e.g., Burro). Less frequent monitoring.
If they were to allocate resources based on ABC analysis, they would optimize their inventory management.
In this whimsical example, the Banana Boutique ensures they have just the right number of bananas to keep customers happy without overstocking.
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