Theory of Constraints Handbook - James Cox Iii [192]
In most cases, when the term “seasonality” is used, the meaning is peak demand within a certain period of time. Such a peak of demand could take several months or just one or two days. There is a clear difference between these extremes; a very short peak means no replenishment could take place during the peak. This case will be dealt with as an MTS later in this chapter.
The capacity problem with seasonality16 is that within the peak the total demand might require more capacity than the CCR has. Such a situation would definitely reduce the on-hand stocks and all one could do is try to prioritize. For a short while, it could be good enough, but for a longer period of time, it would be disastrous.
Increasing the target levels before the start of the season is only a partial solution to the capacity problem. If there would be a real lack of capacity during the peak, and if the peak is not very short, then shortages will certainly occur.
Solving the capacity issue requires investment in capacity and materials before the start of the peak. The direction of the solution is to create enough inventories of several fast runners to cover the demand for those items throughout most of the whole peak. A valid way to do it is to forecast the minimum quantity to be sold through the whole peak of several fast runners and produce this amount prior to the peak. Not having to replenish those fast runners every time there is a sale would save precious capacity that will be used to replenish the other items. The reason we suggest doing this only for several of the top fast runners lies in the characteristics of fast runners to have less spread of the future sales. Even if some of the inventory is left after the peak, it will still be sold.
Problematic Environments for MTA
The replenishment solution for manufacturing is dependent on the priority mechanism in the execution phase. Not just on the priority itself, but even more on the capability to expedite. Environments with longer replenishment time and where expediting is either impossible or very difficult have to compensate for the lack of flexibility by maintaining more stock and by frequent replenishments. Even when the latter is possible, there is a real problem in achieving good availability.
Consider the case of sequence-dependent setups or even just very long setups coupled with a long list of items to be produced. For example, a production line of paint produces 12 different colors. Each of them has three to five different variations of the paint. In producing paint, the length of the setup (mainly cleaning the line from any residuals of the former paint) depends not only on the next color, but also on the previous one. When you keep the sequence that goes from light colors to the dark colors, the total setup time is much less than trying to produce according to the sequence of the real needs of the market. Hence, the production line has to stick to the preferred sequence and thus produce the whole cycle (certain slow items might be skipped from time to time). Suppose that the whole cycle takes 21 days (3 weeks). This means that the replenishment time is 21 days.17 What should the target level be? The “maximum” consumption is within 21 days, so the average sales within 32 days seems appropriate enough.
However, note that it means every item is replenished only once in 21 days. So, if the sales are higher than expected, toward the 20th day the on-hand stock might be penetrating deep into the red and there is nothing we can do about it. Deviating from the sequence might have too much impact on the capacity, maybe even turning the production line into a bottleneck.
The only remedy to this state is to hold much more stock. If the target level is twice the average of sales within the cycle time, then most of the time the on-hand stock will be in the green and toward the end of the cycle, it