With implementation of Theory of Constraints solution, it is expected that all plant managers align their thinking and decision making to the paradigm of flow rather than local efficiencies . While it is intuitively easy to understand and appreciate the flow paradigm, it is very difficult to GIVE UP the efficiency paradigm. Not many production managers can give up the efficiency paradigm easily even though they understand the causality of how the efficiency measures come in the way of flow. Many of them would agree to implement an effective flow system which prevents workers from working on things, which should not be worked upon at a point of time. But at the same time they present a valid obstacle, “how do we ensure resources are working efficiently on things they are supposed to work?” They have a valid point.
It is important to ensure workers are working hard and are not slackening down, when they are working on the right things. We need people to be efficient. While the need is valid, but the mechanism of using efficiency measures to conclude on efficiency is not, particularly in environments with wide variety of SKUs, differing processing times and variability. In most of these environments, people have developed elaborate formulas to determine the productivity of each work centre. The complexity of the formula goes up when one tries to nullify the effects of production variables to arrive at a “fair” way of comparing work centres. But, it is almost impossible to put all possible production factors (particularly the variability) in the formula. So most of the time, the formula offers enough scope for people to “manage” it. These measures actually encourage “cherry picking” (selecting easier to manufacture at cost of others, batching, postponing setups). Every work centre worker and manger knows the way to manage these numbers by selecting some items over others. People can hide slackening of efforts on some SKUs by “cherry –picking” other SKUs to arrive at a better number for the period. Hence one can never know from these numbers, if there was any slackening of efforts in manufacturing. So one never knows if people were really efficient by just looking at the numbers. Not only managers have no clue about efficiency by just looking at these numbers, there is a further damage to flow which is caused by the “cherry picking” actions of the work center managers.
We all know what “cherry picking” does to flow of orders. The cherry picking of items at various local work centres lead to de-synchronization at the convergent points (not all items available together for assembly) or material stealing in the divergent points. It leads to some items being produced ahead time; WIP goes up in the shop floor and so does the lead time, while on time delivery drops down.
It is difficult to conclude if these measures really prevent slackening of efforts (we can never know if numbers were achieved because of hard work, genuine improvement or mere cherry picking), but they do definitely lead to higher lead times and missed due dates. So in a way, one is paying worker incentives to actually mess up the deliveries.
Now we need a way to not only improve flow but also get the real efficiencies (prevent slackening of efforts). TOC approach calls for the Road Runner work ethics (If there is work do not slacken and move as fast as possible. However if there is nothing; sit idle but do not produce excess or ahead of time). Clearly there are two parts of the Road Runner behaviour – efficiency (doing fast what needs to be done) and effectiveness (not doing things which should not be done). Now do we need to have new measures to ensure these two parts of the behaviours? Like the (TRD) throughput rupee days for efficiency and (IRD) Inventory rupee days for effectiveness.
In my opinion, both these measures also have their own associated problems. Due to rupee value attached to orders, they can also lead to a cherry-picking. An importance of an order can never be judged by through-put value of the order. There can be so many different factors associated with long term importance of the order. Ideally, all the factors should be considered while taking in the order but once the order is in the shop floor, the due dates of all orders are equally important and hence the shop floor should only be managed with the buffer signals which provides the relative risk of missing dates of various orders (a priority system which treats all due dates as equally important).
If we cannot use TRD and IRD, how do we ensure the desired behaviours?
Do we always have to invent a new measure to get a desired behaviour?
Our experience shows that a “poka-yoke” process is much more powerful way of ensuring right behaviors, while preventing the wrong ones. The process of chocking the release prevents workers on working on unnecessary items – we got the effectiveness in place with this process. On the other hand, the visible colour signals in shop floor and daily buffer management are a way to ensure “real efficiencies” in the shop floor. With daily supervightsing of Reds and Yellows, any slackening is detected early and corrected. (In a conventional plant with a significant month end skew, the detection of delays and corresponding expediting is mostly towards the month end). The colour signals bring about increased sensitivity to reds and blacks. The entire plant suddenly looks “more visible” and “transparent” to everyone. The plant develops a self correcting system because no-one wants to be seen as the villain who created the reds and blacks in the plant (and in turn caused the failure of the team).
So we have a solution in place to replace the wrong measures
• Chocking the release for effectiveness
• Daily buffer management for efficiency
Now comes the next question. Do we fight to remove all the efficiency measures to start the implementation? We know wrong measures drive wrong behaviours. Then as a first step we need to remove them to “correct” the behaviour. Right?
To touch measurements as a starting point is a waste of time. Even though people would be convinced about the logic, sheer inertia is going to hold them back. The best way to overcome the inertia of old paradigm is to show significant results of using the new paradigm. So the best way forward is to get an agreement to implement the two important processes to a level where they become a routine.
So we implement the new processes, which in a way overcome the impact of wrong measures. But still the question remains, what do we do with the old measures?
It depends on the way the measure is being used. If along with the measure, there is a defined upper limit as a norm, we need to remove the upper limit as it becomes a self fulfilling prophecy and prevents release of capacity. In most plants, once the plant output goes up, the efficiency (even as per the old measures) of the work centres also goes up. Eventually the measures will become redundant – they do not drive any behaviour, positive or negative. Now is the time to remove them. You will hardly have any conceptual opposition provided one has worked out a way to compensate the workers.
Refer to the article “Standing on the Shoulder of Giants” by Eli Goldratt to understand the difference between flow and efficiency paradigms
TDD ( throughput dollar days) is measure for items done behind the schedule, measured as days delayed multiplied by throughput (sale value- material costs) of the order and IDD ( inventory dollar days) is measure for items done ahead of schedule and hence inventoried, measured as throughput value of the order multiplied by excess days in the finished goods
Chocking the release is the step 1 of Drum-Buffer-Rope implementation (TOC solution for improving flow in production) wherein, the material is released to shop floor only a stipulated time before the delivery date.
The time between order release and delivery, also called the production buffer, is divided into 3 colours zones based on elapsed time. The 3 zones green, yellow and red, provides easy guidelines to the shop floor on priorities and triggers for expediting