Write an article based on this "Look to historic demand and demand variability to determine how to avoid stockouts. Determine average demand. Consider future demand for particular stock items. Calculate demand variability. Determine your service factors, aka Z-scores. Decide on the Z-score you are looking for."
The following calculations will predict the stock necessary to achieve a certain cycle service level - i.e. the percentage of supply cycles that will result in a stockout. Average demand is the total quantity of a material or good required each day over a fixed period. A common approach is to check the total usage of that item for a specified period, such as one calendar month or the interval between ordering and delivery of stock, and then divide by the days in that month to find usage per day. For many items — such as long-established brands in a grocery store — historical demand will provide the best guide to calculating demand. Sometimes it makes more sense to consider future demand. For instance, if you manufacture car transmissions and have received a large order, you will want to factor that order into demand. In this case, you might consider calculating average demand and then adding in the demand created by the large order. Average demand can only tell you so much. If demand fluctuates dramatically from month to month or day to day, you will need to include that in your calculations so that you will have enough stock to cover surges in demand. Start by using a spreadsheet to calculate the standard deviation in demand (in Excel, enter all demand figures in their own cells, then the formula is = STDEV(the cells in question)). Or use the following formula:  Start with the average demand over a period of time (i.e. a week, month or year). For our example, let's say it is 20 units per month. Determine the absolute difference between each data point and the average. For example, if monthly demand was 8, 28, 13, 7, 15, 25, 17, 33, 40, 9, 11, and 34 units, the differences from 20 would be: 12, 8, 7, 13, 5, 5, 3, 13, 20, 11, 9, and 14. Square each difference. In our example, this would yield: 144, 64, 49, 169, 25, 25, 9, 169, 400, 121, 81, and 196. Calculate the average of the squares. E.g. 121 Take the square root of the average. This is your standard deviation of demand. E.g. 11 The service factor, or Z-score, is based on the standard deviation of demand. A Z-score of 1 will protect you from 1 standard deviation of demand. So in our example, since the standard deviation of demand was 11, it would take 11 units of safety stock in addition to normal stock to protect against one standard deviation, yielding a Z-score of 1. 22 units of safety stock would yield a Z-score of 2. The higher your Z-score, the less likely you are to have a stock-out. In choosing a Z-score, you will want to balance customer service and inventory cost. You will want a higher Z-score for stocked units with greater value to your business. A Z-score of 1.65, satisfying demand with a 95% confidence level, is generally regarded as acceptable even for important stock. In this case, that would mean stocking approximately 18 units (the standard deviation of 11 x 1.65) of safety stock, or 38 units total (average demand + safety stock). Here are how Z-scores relate to the probability you can fulfill demand:  Z-Score of 1 = 84% Z-Score of 1.28 = 90% Z-Score of 1.65 = 95% Z-Score of 2.33 = 99%