BUS606: Operations and Supply Chain Management

In our calculation, there are some reasons behind inclusion of all the formulas in Safety stock determination. We got the Demand from regression analysis as the demand was unknown for desired period. Besides Lead time and Demand are mutually dependent. Using the demand we calculate EOQ to get the specific amount to order each time by optimizing the inventory related costs. After that EOQ is divided by the review interval to get per day demand from EOQ, indicate optimum demand each day we need. Now, this amount is added with mean absolute error. As the error indicates missing amount in demand, could be positive or negative, it is added with in our calculation. Then the derived data is multiplied by mean lead time to get the demand of the lead time period. As lead time could vary, as we see it varied before in our case, we need to multiply the derived data with the standard deviation of lead time to reduce the error of lead time took so far before.

In our case, the result is 2476, which almost 2 times of our mean demand (1185). By looking at data, it supposed to acceptable safety stock as it indicates safe inventory amount for 2 periods considering the lead time. If unfortunately one time delivery fails, the safety stock is enough to support the interim period (1 failed delivery period+1 New order receive lead time period=2 period of inventory). Besides, Considering the Review period on 10 days (1 period) and average lead time of 10 days adds 20 days that is equals to 2 period of demand. Our Safety stock indicates this 2 period demand (20 days). Besides, as the demand data was derived from extensive analysis of Linier regression, Error calculation and EOQ analysis, we can expect the demand data contains less error in derived safety stock data.

Other calculations in the 'Calculation 1' chart. For example, Sample variance, Correlation, Square of correlation coefficient etc. was to calculate the validity of the data used in our model