MECE Framework MECE stands for "Mutually Exclusive and Collectively Exhaustive", which means "think without omission or duplication". It is a kind of Logical Inference.
In the Problem-solving steps , it is useful in each situation of grasping the current situation, analyzing factors, and planning countermeasures. Based on the MECE concept, we will proceed with why- why analysis and creation of a system diagram .
Quantity Way of Making Hypothesis assumes that there is data, so there is a weakness in that it is difficult to notice the cause of the lack of data. MECE thinks in terms of principles, so it is easy to notice the reason why there is no data.
Below, as an example of MECE analysis, I wrote how to express branching by affirmation and negation using a logic tree. This is the method I use myself. In the explanations of MECE in the world, there are cases where the method of identifying items as much as possible and classifying them is generally called "MECE".
As a physical principle , we will identify what can happen. The point is to branch out into affirmations and denials, such as "same as usual" and "not the same as usual." This way, you will miss fewer possibilities. Even if you think "this is impossible", it is also a point to write it down at least once. There are things that can't actually happen, and writing it down can lead to other possibilities.
The reason the very first branch is "true length" is because I doubt the quality of the data . No matter how much you look at the data, you won't be able to tell, but there are times in the factory data analysis where "the data and the reality are different."
For example, regarding the "same as usual" in the "materials" section, "If the movement of the machine is the same as usual, and the material is the same as usual, but the material is still over-cut, is there any reason?" Think about it, and if you can think of it, you can branch it out further. By branching out into affirmations and denials, it 's easier to think "what if it still happens" and focus on things you wouldn't normally think about.
For example, "Materials" can be divided into three by saying "There are three differences between companies A, B, and C." In some cases, branching like this is better.
However, it is necessary to be careful not to overlook it, such as "Company D actually has it." It is difficult to overlook things if they are classified from the same point of view, such as "Company A, Company B, and Company C". So, if you write things with different granularities side by side, MECE will become ambiguous.
After qualitative hypothesis exploration in the MECE format , the next step is to verify the hypothesis (empirical analysis) .
Check the data to see what actually happened.
Regarding data confirmation, the most reliable thing is the data of what you want to verify. For example, the best way to check whether the length before processing was the same as usual is to check the data "Length before processing".
However, in actual verification, there are times when there is no data for the "length before processing."
In that case, the first thing you can do is to measure the data. Sometimes I say, "Since the material should be the same as this, measure the length of this."
In some cases, the material has been used up and the original length cannot be confirmed. In those cases, you're looking for indirect data. As indirect data, we check whether there are points such as "the material is from a different supplier" or "the material was purchased on a different date." I don't know the length itself, so I'll check if the length could be different.
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