In this article we cover exactly what buffer inventory is and its pros and cons. We examine the methods for calculating it and share our simple 6 step process for effective buffer inventory management.
Buffer inventory, or safety stock, is a reserve of goods held by a company to guard against demand fluctuations and supply chain disruptions to ensure uninterrupted operations. It balances risk mitigation and inventory costs.
Example: A smartphone manufacturer maintains a buffer inventory of 5000 microchips. This ensures that they can meet customer demand even during unexpected supply chain delays or sudden spikes in order.
Buffer inventory can offer a number of advantages, but it also comes with certain disadvantages. We will explore these below:
Here are the advantages of buffer inventory:
1. Risk Mitigation: Buffer inventory reduces the risk of stockouts, ensuring that customer demand can be met, even in the face of demand variability or supply chain disruptions.
2. Improved Customer Service: It leads to better customer satisfaction as the company can fulfill orders reliably and on time.
3. Production Stability: Buffer inventory helps maintain stable production by compensating for variations in production rates, equipment breakdowns, or unexpected quality issues.
4. Supplier Reliability: It provides a cushion against supplier delays, giving suppliers more flexibility and reducing the risk of supply chain interruptions.
5. Demand Forecasting Flexibility: Buffer inventory allows for more flexibility in demand forecasting, as it can absorb forecasting errors and unexpected shifts in market demand.
While buffer inventory has advantages for inventory management, it also has disadvantages.
1. Higher Holding Costs: Maintaining buffer inventory incurs costs for storage, insurance, and the opportunity cost of capital tied up in inventory.
2. Reduced Cash Flow: Excessive buffer inventory ties up capital that could be invested elsewhere which potentially reduces cash flow and financial flexibility.
3. Risk of Obsolescence: Over time, buffer inventory may become obsolete if not used which leads to inventory write-offs and wasted resources.
4. Storage Constraints: Buffer inventory requires storage space and excessive inventory levels may strain available storage capacity.
5. Reduced Efficiency: Over-reliance on buffer inventory can lead to complacency in improving supply chain and production processes and potentially reduces overall efficiency and competitiveness.
The specific formula to calculate buffer stock may vary depending on the context and assumptions, but here are two common methods:
The reorder point method calculates buffer stock based on the average demand and lead time (the time it takes to replenish stock). The formula is:
ROP = (Average Demand * Lead Time) + Safety Stock
Average Demand: The average daily or weekly demand for the item.
Lead Time: The average time it takes to replenish the item from the supplier.
Safety Stock: The extra stock (buffer stock) held to account for variability in demand or lead time.
The Safety Stock is typically determined by considering factors like desired service level, demand variability, and lead time variability. Common approaches include using z-scores from a normal distribution or historical data.
This method focuses on achieving a specific service level, which is the probability of not running out of stock during the lead time. The formula for calculating buffer stock to achieve a desired service level is:
Safety Stock = (Z-score * Standard Deviation of Demand) * Square Root of Lead Time**
Z-score: The number of standard deviations from the mean that corresponds to the desired service level. It is based on a statistical distribution, often the normal distribution.
Standard Deviation of Demand: The measure of demand variability.
Lead Time: The time it takes to replenish the item from the supplier.
This method allows you to set a specific service level and calculate the buffer stock needed to achieve it.
To maintain a balance between ensuring product availability and minimizing inventory holding costs, you can follow our simple 6 step process below:
Define the target service level that represents the probability of not running out of stock. For example, you may aim for a 95% service level. This indicates that you want to fulfill 95% of customer orders without stockouts.
Example: A hardware store aims for a 95% service level for its popular power tool. This means they want to have enough buffer inventory to meet demand 95% of the time without stockouts.
Examine historical sales data and demand patterns to calculate the standard deviation of demand during the lead time. This statistic quantifies demand variability.
Example: A car dealership analyzes the past year's sales records to determine that the standard deviation of monthly demand for a specific car model during the lead time is 20 units.
Determine the Z-score corresponding to the chosen service level using a statistical table. The Z-score represents the number of standard deviations from the mean (average) demand you want to cover with safety stock.
Example: To achieve a 95% service level, the car dealership looks up the Z-score of 1.645 in a statistical table.
Apply the Z-score, standard deviation, and lead time to calculate the required safety stock using the formula: Safety Stock = (Z * σ * √(Lead Time)).
Example: Safety Stock = (1.645 * 20 * √(7)) = 98.48 units of the car model.
Combine safety stock with average lead time demand to determine the reorder point. The reorder point is the inventory level at which you should place a new order.
Example: Reorder Point = (Average Demand during Lead Time + Safety Stock) = (50 + 98.48) = 148.48 units of the car model.
Continuously monitor actual inventory levels and compare them to the reorder point. Reevaluate and adjust buffer inventory levels based on changes in demand patterns, lead times, or desired service levels.
Example: If the car dealership experiences a surge in demand for the model due to a promotional event, they may need to increase the safety stock and reorder points accordingly to avoid stockouts.
GlobalTech is an electronics company that seeks to meet customer demand consistently and reduce stockouts. Let’s explore how they implemented our buffer inventory management process below.
GlobalTech sets a target service level of 95%, meaning they aim to fulfill 95% of customer orders for their popular tablet model (Tablet A) without stockouts.
The company analyzes historical sales data for Tablet A and calculates that the standard deviation of monthly demand during the lead time (which is 28 days) is 120 units.
To achieve a 95% service level, GlobalTech looks up the Z-score of 1.645 in a statistical table.
Using the formula: Safety Stock = (Z * σ * √(Lead Time))
Safety Stock = (1.645 * 120 * √(28)) ≈ 434.65 units of Tablet A.
The company combines the safety stock with the average monthly demand during the lead time, which is 600 units.
Reorder Point = (Average Demand during Lead Time + Safety Stock) = (600 + 434.65) ≈ 1034.65 units of Tablet A.
GlobalTech continually monitors the inventory levels of Tablet A. If they observe a surge in demand, such as due to a seasonal promotion, they may need to adjust the safety stock and reorder point to avoid stockouts and ensure they meet their 95% service level target.
We hope that you now have a better understanding of what buffer inventory is, its pros and cons, and how to effectively manage it to optimize your business operations.
