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It is never a good business practice to run out of inventory, since the consequences can be dire. For example, if an item is in high demand and selling rapidly, running out of it almost certainly means business lost to competitors – sometimes to the tune of thousands of dollars. In addition, reordering an item that is hot on the market can add cost in terms of both increased prices and quick shipping to make up for lost time. And, if the market drops out of that particular product before the reorder arrives, a distributor can be left with some very expensive inventory that isn’t likely to move any time soon. Thus, most companies involved in supply chain distribution are always trying to optimize their safety stock.
It may seem that terms like ‘safety stock’ are bandied about relentlessly without anyone having a really firm fix on precisely what they mean. Ask ten different companies what safety stock is and how to ensure that it exists, and ten different answers are likely to be given. There are also numerous models in existence for calculating the basis for safety stock – some based on bestguess scenarios and others based on very specific mathematical calculations. However, it is generally considered that safety stock is the amount of product necessary to meet varying customer demand, while keeping stocks on hand to a minimum. That way, costs are kept in check, useless inventory does not pile up in the warehouse, and orders are met in a timely fashion.
The most accurate means of predicting safety stock are, of necessity, the most complex because they are based on mathematical probability. One of the most widely utilized means of calculating how much safety stock is to determine probability through the statistical model called Standard Deviations of a Normal Distribution of numbers. In this method, historical data is used to predict demand variability, through a fairly complicated set of calculations relating service factors, leadtime factors, order cycle factors, forecasttomeandemand factors, and standard deviations. At the same time, experts acknowledge that there is no final agreement on a solid formula for determining each factor, but several variations that are used. Therefore, it is sound advice for each business to modify the formulas to best meet its own needs.
By the same token, there are several factors that are common to most methods of calculating the margin necessary for safety stock. A leadtime factor, or the difference between lead time and forecast period, must be determined. An order cycle factor, to account for the relationship between order cycles and service levels, is also a common component. A forecasttomeandemand factor should be based on the types of variances that exist within a specific business. A minimum reorder point should be calculated and factored into the equation; the reorder point should be the same time period as one average sale. Leadtime variances are difficult to predict, but also need to figure in to the prediction model.
There is a variety of software on the market that is helpful with calculating the amount of safety stock necessary for a business, but in reality a good spreadsheet may suffice just as well. Again, the need for a particular method of safety stock calculation and the means of executing it are particular to the business in question and no method is likely to suffice for any and all companies.


