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Commonality

Commonality is often present in most businesses. 3C identifies, classifies and uses commonality under two different categories:

Commonality at the subassembly level, and commonality at the purchasable-item level. We will address, in this paper, only the later category and leave the discussion of the important issue of commonality at the subassembly level for a later publication. Let us just emphasize that the same GAGE tool is used to measure, understand and make decisions related to the MM issues of subassemblies.

Capitalizing on the presence of commonality gives the business a competitive advantage. A general measure of commonality, however, had not been devised until 3C literature became available during 1993.

3C contains a general measure of commonality called CIND (Commonality INDex). The CIND is derived from the mathematical formula of a straight line.
A separate document (pending publication) deals with the details of the "commonality index" CIND. This future paper is focused on the commonality aspects from the 3C point of view.

Simulation Results

GAGE reports data that is used to build several types of graphs that characterize the business and its performance when the MRP or 3C MM methods are used to service the business.

In this section we present a summary of the comparisons obtained through intensive simulation studies of busi­nesses containing various degrees of "forecast inaccuracy" or as we call it "System Flexibility."

Delivery Performance

Customer satisfaction is without a doubt the most impor­tant ingredient for success and its importance is expected to increase as global competition intensifies and local markets become more aggressive. Henceforth, GAGE keeps track of all the customer orders received and prepares the data used for the profile shown in figure 4.

MRP-NSS represents the results of an MRP model running with No Safety Stock(or protection for MPS variations). Observe that even at variations as low as 10% (from the quantities and products planned), this type of system already reports stock-outs of up to 30%.

MRP-YSS represents the results of an MRP running with different percentage levels of over-planning in all items of the MPS. It can be observed that the delivery performance improves to the same levels as 3C. The cost of this protec­tion for MRP is increasingly higher as more flexibility is demanded. For 3C, the situation is entirely different. The cost of this protection and increased flexibility in customer service could be expensive, relatively cheap and in some cases even free, depending on the CIND value of the business.

Rotations of Inventories (TOR)

Figure 1 presents the conclusions that we have reached from results obtained through the simulation models. The inventory turns (also know as TOR for Turn Over Ratio) are calculated as the annual sales (shipments) divided by the average inventory carried throughout the year. Both nomi­nator and denominator are evaluated at material cost only.

When a simulation request to simulate less than a year, GAGE performs the simulation as requested and estimates the annual results with the values obtained during the time requested. We emphasize that these TOR values represent rotations of purchased items (raw materials) only. The real TOR of the business, we all know, should include abso­lutely all inventories held by the business, regardless of its place of storage or the age of it.

The horizontal coordinate on this graph represents what in some businesses is known as "Forecast inaccuracy." While some of these businesses keep pouring money into fruitless projects aimed at reducing these "inaccuracies," 3C recog­nizes that these "inaccuracies" actually represent the "flex­ibility" that is being demanded and expected from our business in these competitive times. If only this simple fact were accepted, we would really be on our way cementing the foundations of the systems of the time to come.

The simulation studies performed clearly indicate that 3C can double the rotations of inventories for businesses facing markets requiring flexibility of more than 30% (30% forecast inaccuracy).

From an operational point of view, we have recorded a great number of differences when using 3C comparing it to MRP II (the system used before by professionals who carried out the introduction of the new system).

Figure 2 shows two outlines with the functionality and the environment of the computer system developed to operate applying the new theory. This system is called HERMES (5) and is capable of managing a logistic chain in the 3C environment. This system includes all functionality neces­sary to obtain the required flexibility from 3C.

Once the 3C parameters have been calculated and the correct function of the hole system has been secured, there is a drastic contrast between the 3C environment and the MRP II environment. In future publications we will explain in more detail each of these differences. Basically, the CYCLIC and COMPLEX activities in MRP II are substi­tuted by others SIMPLE and CONTINUOUS which cause a double effect: less resources (since it is simpler) and better used (since it is continuous).

From a flexibility point of view, excellent results are obtained based on the elimination of the "time fence con­cept" which is so decisive in MRP II.
Inventory and Service levels reached at our test-factory are far better than those of the factories to which they are compared.

This paper has discussed briefly the new MM method called 3C and have provided comparisons of the perfor­mance of MRP and 3C, the first serious MRP challenger. An important attribute of 3C, in contrast with other methods, is that it provides advantages in terms of Customer Ser­vice, while producing economic improvements in inventory investments and revenues with a direct positive impact on the Company's Botton-Line.

Hopefully our article will also trigger scepticism and inter­est among researchers and especially MM professionals. More research will be needed to test, try and evaluate the new alternatives that undoubtedly will be lining up as proposed substitutes for MRP.