Safety stock

Introduction• Safety stock (also called buffer stock) is a term used

by logisticians to describe a level of extra stock that is maintained to mitigate risk of stockouts due to uncertainties in supply and demand

• Safety stock is an additional quantity of an item held in the inventory in order to reduce the risk that the item will be out of stock, safety stock act as a buffer stock in case the sales are greater than planned and or the supplier is unable to deliver the additional units at the expected time.

•  The less accurate the forecast, the more safety stock is required to ensure a given level of service.

• A common strategy is to try and reduce the level of safety stock to help keep inventory costs low once the product demand becomes more predictable.

• This can be extremely important for companies with a smaller financial cushion or those trying to run on lean manufacturing, which is aimed towards eliminating waste throughout the production process.

Reasons for keeping safety stock

• Safety stocks are mainly used in a “Make To Stock” manufacturing strategy.

• This strategy is employed when the lead time of manufacturing is too long to satisfy the customer demand at the right cost/quality/waiting time.

• The main goal of safety stocks is to absorb the variability of the customer demand.

• Creating a safety stock will also prevent stock-outs from other variations, like an upward trend in customer demand.

• Safety stock is used as a buffer to protect organization from stockouts caused by inaccurate planning or poor schedule adherence by suppliers

• Various methods exist to reduce safety stock, these include better use of technology, increased collaboration with suppliers, and more accurate forecasting

• An Enterprise Resource Planning system (ERP system) can also help an organization reduce its level of safety stock. Most ERP systems provide a type of Production Planning module

Inventory policy

• The size of the safety stock depends on the type of inventory policy that is in effect.

• An inventory node is supplied from a "source" which fulfills orders for the considered product after a certain replenishment lead time.

• In a periodic inventory policy the inventory level is checked periodically (such as once a month) and an order is placed at that time as to meet the expected demand until next order.

• In this case, the safety stock is calculated considering the demand and supply variability risks during this period plus the replenishment lead time.

• If the inventory policy is continuous policy (such as an Order point-Order Quantity policy or an Order Point-Order Up To policy) the inventory level is continuously monitored and orders are placed with freedom of time.

• In this case, safety stock is calculated considering the risk of only the replenishment lead time.

• If applied correctly, continuous inventory policies can lead to smaller safety stock whilst ensuring higher service levels, in line with lean processes and more efficient overall business management.

Example

• A commonly used approach calculates the safety stock based on the following factors:• Demand: the amount of items consumed by customers, usually a

random variable.• Lead time: the delay between the time the reorder point (inventory

level which initiates an order) is reached and renewed availability.• Service level: the desired probability of meeting demand during lead

time without a stock out. Naturally, when the desired service level is increased, the required safety stock increases as well.

• Forecast error: an estimate of how far actual demand may be from forecast demand.

• Assuming that demand during each unit time period are independent and identically distributed random variables drawn from a normal distribution. The safety stock can be calculated as:

Issues with this approach

• The inclusion of service level by means of NORMSINV assumes a normal distribution of lead time demand. First of all, real demand cannot be negative. This skews normality leading to consistent overestimation of safety stock by this formula. Secondly, supply is not a random event but a conscious decision, often triggered by batch sizes, economic order quantities or ROP formulas on the receiving side. With a very large amount of that may not be an issue but otherwise it is (for example, for a manufacturer that supplies these retail warehouses)

• The use of average and standard demand assumes it is statically constant. For seasonal demand (for example high in summer, low in winter) the formula will consistently produce stock outs in summer and waste in winter. Similar errors apply for demand that grows or declines

• Lead time is extremely hard to quantify in complex manufacturing and/or purchase environment, which has become the norm in global supply chains that span many independent partners. In practice, lead time is estimated by a rule of thumb that hardly improves on estimating safety stock with a rule of thumb. Even when lead time is correctly quantified, the formula assumes supply (production and purchase) is statistically constant, which is not always the case.

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