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The MECE principle (mutually exclusive and collectively exhaustive) is a grouping principle for separating a set of items into subsets that are mutually exclusive (ME) and collectively exhaustive (CE). [1] It was developed in the late 1960s by Barbara Minto at McKinsey & Company and underlies her Minto Pyramid Principle, [2] and while she takes credit for MECE, according to her interview with McKinsey, she says the idea for MECE goes back as far as to Aristotle. [2]
The MECE principle has been used in the business mapping process wherein the optimum arrangement of information is exhaustive and does not double count at any level of the hierarchy. Examples of MECE arrangements include categorizing people by year of birth (assuming all years are known), apartments by their building number, letters by postmark, and dice rolls. A non-MECE example would be categorization by nationality, because nationalities are neither mutually exclusive (some people have dual nationality) nor collectively exhaustive (some people have none).
Strategy consultants use MECE problem structuring to break down client problems into logical, clean buckets of analysis that they can then hand out as work streams to consulting staff on the project.
Similarly, MECE can be used in technical problem solving and communication. In some technical projects, like Six Sigma projects, the most effective method of communication is not the same as the problem solving process. In Six Sigma, the DMAIC process is used, but executive audiences looking for a summary or overview may not be interested in the details. By reorganizing the information using MECE and the related SCQA storytelling framework, the point of the topic can be addressed quickly and supported with appropriate detail. The aim is more effective communication. [3]
The MECE concept has been criticized for not being exhaustive, as it does not exclude superfluous/extraneous items. [4]
Also, MECE thinking can be too limiting as mutual exclusiveness is not necessarily desirable. For instance, while it may be desirable to classify the answers to a question in a MECE framework so as to consider all of them exactly once, forcing the answers themselves to be MECE can be unnecessarily limiting. [5]
Another attribute of MECE thinking is that, by definition, it precludes redundancies. However, there are cases where redundancies are desirable or even necessary. [6]
There is some debate regarding the pronunciation of the acronym MECE. Although it is pronounced by many as /ˈmiːsi/ , [7] the author insisted that it should be pronounced as /miːs/ . [2]
In traditional logic, a contradiction occurs when a proposition conflicts either with itself or established fact. It is often used as a tool to detect disingenuous beliefs and bias. Illustrating a general tendency in applied logic, Aristotle's law of noncontradiction states that "It is impossible that the same thing can at the same time both belong and not belong to the same object and in the same respect."
In logic and probability theory, two events are mutually exclusive or disjoint if they cannot both occur at the same time. A clear example is the set of outcomes of a single coin toss, which can result in either heads or tails, but not both.
In mathematics, a partition of a set is a grouping of its elements into non-empty subsets, in such a way that every element is included in exactly one subset.
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In probability theory and logic, a set of events is jointly or collectively exhaustive if at least one of the events must occur. For example, when rolling a six-sided die, the events 1, 2, 3, 4, 5, and 6 are collectively exhaustive, because they encompass the entire range of possible outcomes.
In probability theory, the complement of any event A is the event [not A], i.e. the event that A does not occur. The event A and its complement [not A] are mutually exclusive and exhaustive. Generally, there is only one event B such that A and B are both mutually exclusive and exhaustive; that event is the complement of A. The complement of an event A is usually denoted as A′, Ac, A or A. Given an event, the event and its complementary event define a Bernoulli trial: did the event occur or not?
DMAIC or define, measure, analyze, improve and control refers to a data-driven improvement cycle used for optimizing and stabilizing business processes and designs. The DMAIC improvement cycle is the core tool used to drive Six Sigma projects. However, DMAIC is not exclusive to Six Sigma and can be used as the framework for other improvement applications.
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An issue tree, also called logic tree, is a graphical breakdown of a question that dissects it into its different components vertically and that progresses into details as it reads to the right.
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Extreme programming (XP) is a software development methodology intended to improve software quality and responsiveness to changing customer requirements. As a type of agile software development, it advocates frequent releases in short development cycles, intended to improve productivity and introduce checkpoints at which new customer requirements can be adopted.
Barbara Minto is an American author and consultant focused on the subject of executive communication.
The following outline is provided as an overview of and topical guide to consulting: