In Module 2, we talk about the computing reorder point by taking into account of safety stock. We can mitigate the risk of a stock-out due to demand variability. There we alluded to the concept of customer service level using that to calculate the z value, and to help us figure out how much safety stock we need. Therefore, also figuring out what the new reorder point should be. In this module, Module 3, we're going to dive a bit further into the relationship between safety stock and customer service level. Such as a review that this is a normal distribution curve, and typically the middle of 50 percent halfway is our expected demand. This is what the mean, we calculate the mean of demand over the time. Then whatever we add to it, is the safety stock. The z value that we used really it is to tell us how far to the right of the curve we need to go to define how much inventory we need to carry. This is associated to the probability. The further out you go, for example, if it's 95 percent, I said example that we used in module 2. This would be a 95 percent point. This is how much to the right of the expected demand I need to go. This is the amount of service I need to carry. Or if you are taking into account the whole entire graph, then this is the total amount of inventory I need to have. The order point it is when you hit this point, I need to reorder XML inventory. Then service level, basically, another word is that is the in-stock probability. Ninety-five percent of the time I will have this item in stock. I say the example that I have handled orders, 95 of them will be shipped on time because I have 95 items in stock. We saw how to compute the z-score using the norms inverse function in Excel. But to look at it in a more non-electronic or tool-based, this is a standard table. We were looking for 95 percent, so just give you a little background on how this is computed. That for example, if we define the 95 percent service level. What we typically do is we'll look for the value that's closest to the 95 percent. But we don't round up. You can see that here I have two values that are very close. The closest is to 95 percent. One is 0.9495, and the other one is 0.9505. What we typically do, and also what the computer would do is they will pick the highest of the two that's closest to the value that we are looking for without rounding. In this case we'll go with 9505. Then what we do is, we go to the left, we get this value of 1.6. That is to the left of my 0.9505 on the same row. Then on a column, or go up in this column, and this is the 0.05 here. What we do is we take 1.6 plus 0.05, then we get 1.65. That's how the z-score is computed, is based on the probability that we defined and it is a corresponding value to tell us how far away from the mean that we need to go under the standard normal distribution curve. Now we come back to the Excel example. Again, following the same example that we've been using in Module 1 and 2. We computed all these values, basing in Module 2. We came down, and we also calculated the z value using the norms inverse function. In module 2, we only calculated this for 95 percent service level. But now you may be asked to do 96, 97, 98 even 99, and maybe up to 100 percent. You do the same thing. In this case, I can just drag this value here, over. Then I get the values up here. Same thing we CB stock. I cannot do the same thing with CB stock because I have, if I fixed C32. If I fix C28, then I can do the same thing. Because my sigma (L) does not change, and then I drag it here. You will see the incremental value that's needed. Here I just wanted to just point out that the relationship is not very linear in terms of the incremental values and that we saw the curve as the further up you go, the higher the [inaudible] level you go even from 95-97, is not a linear increase. If you take this as the base, we can see that the change right from this one to this. Then we taking 95 as my base, that has about six percent increase. This is a 7,10, and 16. I almost doubled. Oh, I did double. I would have almost doubled when I go to 98 in terms of the incremental changes. Then you can also do the same, buy safety stock and convert it to a dollar value based on the cost of the goods. Now was almost double in terms of investment I need to make to have this amount of inventory. Safety stock and here, inventory, so service level is very closely related to how much inventory you carry. If you have people asking you, why can't I have 100 percent? I can fulfill my order 100 percent of the time, and or maybe 99. Or, maybe I'll stay even 98. You can do similar analysis. Once you figure out, you don't even probably need to figure out this, savvy stop but it's good, maybe to translate this into the dollar value, and then you can quantify this as a fact to the stakeholders and let them know, this is the incremental investment that you need to make, and are they ready to do that in order to move even from 95-98? Would they be comfortable to putting almost double the money, and put them into inventory, as a inventory value. This is the relationship and this is often by the analysis that you had to go through. Business need to define the amount of inventory they will either carry by defining their service level, they wish to achieve. Then be mindful that there's costs associated to that, and it's not linear.