How bad are local efficiency measures?

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One of the predominant paradigms of managing shop floors is maximizing work center efficiencies. Many managers tend to believe that it is the best way to reduce the product costs and get the best out of the plant. The origin of the paradigm can be traced to the allocation rules of cost accounting. The rule of allocating overheads of a cost center on to the products by using machine or labor hours tends to create scenario where-in, increased output leads to overheads distributed over more output units and hence consequently lesser cost per unit. Hence the need to maximize work center efficiencies particularly for high investment resources is almost ingrained in every plant manager and guides his daily decisions.

This article tries to raise and answer the following questions:
1- Is maximizing local work center efficiencies good for the plant as a whole?
2- Does the paradigm of maximizing local efficiencies, at least, help the specific work center?
3- If we establish that maximizing work center efficiencies is not good for anyone, then should they be abolished?

To understand more, let us analyze the environment of custom manufacturing plants. Typically most custom manufacturing plants have two types of resources or operations – some operations ( let us call them type A) where people have a choice to not focus on orders like machine shop producing parts for servicing many orders and some work centers ( call them type B) where there is no choice but to focus on order completions. Typically they are assembly operations, site installation, packing or dispatch. In most plants the type B resources are usually towards the last stage of operations and type A are in the earlier stage. In such environments, the need to focus on utilizing work centers, forces managers to batch components across orders and when many type A work centers do that, the level of de-synchronization goes up as the order progresses in the shop. However when the order reaches close to type B resources like the assembly or dispatch or site installation, the de-synchronization is no longer tolerated. The type B resources trigger the expediting signals (or flow backs) to complete the remaining parts of an order. These flow backs usually come in as urgencies of specific single orders and as a result all supplying work type A work centers go to the other extreme – leave everything and attend to supplying the remaining parts of a specific order – they break their queues and take unplanned extra setups to service a single order. So from batching across many orders to minimizing the setup, they go to the other extreme of taking set up to service the remaining parts of one order. Typically this happens close to month end for plants which have to dispatch complete assembled units when the output of type A resources or the feeding lines to assembly drops to complete orders. This period of correction is payment for the sin of excess batching done in the initial part of the month. For organizations which supply independent parts to site installations, the capacity killer flow back requirement comes after few months depending on site installation lead time. It is not surprising for such companies to have an output which fluctuates widely across months. If in some month, the output goes up by selective cherry picking for dispatches, then after some time, the output drops when the plant tries to complete the mess of many open sites.

This painful experience is so ingrained in the minds of the plant people that they tend to believe that the focus on order completion causes plant output to go down.

But what we just analyzed is that the pressure point to focus on one order (and corresponding loss of capacity) is triggered because of delays. The delays are primarily due to increased de-synchronization. The increased de-synchronization is due to actions to maximize local efficiencies. So by trying to maximize efficiencies we end up eventually reducing it!

We know for sure that trying to expedite one order leads to waste of capacity but at the same time cherry picking across orders to fully utilize the non-bottlenecks is also the other extreme. If we operate any one extreme we will soon be forced to the other extreme. So the solution is very simple – do not operate at any extreme and you will be better off in capacity utilization as well as order completion. So we can operate at the middle of these two extreme which should be the stable zone. What is the middle zone?

De-synchronization was because of “cherry picking” of components across orders. “Cherry picking” was because orders were there to be cherry picked. So if we can reduce visibility of orders, we can find the middle zone. TOC’s Operations solution suggests that we cut the current buffer size (production lead time) to half and not allow material before the material release date as determined by the reduced buffer. Cutting the current buffer size by half means there will be fewer orders (than before) in the shop floor (WIP reduces by half). There is much less orders to cherry pick from but it is not one order – There is enough orders (though lesser than before) which allows for batching and the plant doesn’t have to process order by order. This coupled with the elapsed time based color priority system allows the work centers to play within a zone and still focus on moving many orders out from their department.


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