premolecular
...ts In this report we are mainly concerned with premolecular’s inventory and therefore we will analyze its current inventory costs in order to be able to compare them after the optimization that we are looking for. As stated above, although Premolecular deals with a number of different products, we have concentrated our analysis on one single product: Cardiva. In order to analyze the costs of Cardiva inventory under the current inventory management system we have calculated the annual costs of ordering and the average annual inventory holding costs for the years of 2002, 2003 and 2004. These calculations are presented in table 4 of the Annex 2 to this report. The following table summarizes the results. 3.4.2 Dependability Since the process under analysis is not a productive process but rather a commercial one, the dependability in terms of capacity to meet anticipated demand in only a matter of inventory management. In this sense, the only measure that can be of relevance in order to characterize the process’s capacity to meet anticipated demand is its inventory level. Currently there is no safety stock (apart for a very small quantity) given the fact that, as mentioned above, the products are ordered to the suppliers when the order from the customers comes in. The average inventory results from differences in time between the delivery of the supplier and the shipment to the customer. During this time the products rest in the Premolecular’s warehouse. The average inventory level during 2002 was 377 units, during 2003 was 437 units and during 2004 was 515 units. The average inventory level over these three years was 448 units. 3.4.3 Speed Given that the process under analysis concerns mainly the inventory management, there is no sense in identifying the throughput rate of the process. In this context, there are three measures that are of vital importance: The suppliers lead time, the average inventory time and the lead time to customers. We have identified these three measures for each of the three years under analysis. The results are presented in the following table. One of the key issues under analysis in our project is the Service Level to the final customer. From the table above we can infer that the average lead time to deliver is around 4,6 days. Although this figure may seem quite acceptable, we have recorded deliveries with lead times as high as 43 days, which, for a medical product is not acceptable. 3.4.4 Quality In the context of a process like the one we are analyzing, the quality is measured by the Service Level to the final client, that is, the probability of non-existence of stock-outs. Given the fact that under the current inventory measurement system the company has neither safety stocks nor a defined Reorder point, in order to calculate the Service Level under the current inventory management system we’ve identified the level of inventory when the orders were placed to the suppliers and we’ve considered this as an “empirical” ROP. The Service levels calculated for each of the three years under analysis are the following: • 2002: 51,11% • 2003: 49,42% • 2004: 94,67% The Service Level in 2004 results mainly from one order that was placed while there were 2.120 units in stock. This stock has a huge impact in the measure that we’ve used as empirical ROP and therefore impacts the calculations of the Service Level. 4 Operational Problem Encountered The problem encountered has two different dimensions: • On one hand, the Service Level is very low (the service level of 2004 is not representative due to the explanation presented on the previous point). • The inventory costs are mainly due to the ordering costs and can be optimized by reducing the annual number of orders and increasing the quantity ordered. This is possible since the company’s warehouse has enough space to accommodate a higher level of inventory. 5 Solutions to the operational problem Since inventory is material obtained in advance of need, any inventory control policy must be based on some anticipation or belief about which materials will be needed in the future, how much will be needed, and when the need will arise. In other words, inventory control must involve some forecast of future demand, whether crude or sophisticated, explicit or implicit. In a very real sense, the ability to forecast demand and re-supply times accurately will set an upper limit on how successful or efficient the inventory control policy will be. In order to solve the above identified problems, we have drawn a new inventory management policy that allows Premolecular to have a 95% Service Level and also an optimization of its inventory costs. The 95% Service Level was chosen because we believe it to represent a good compromise...