MECE principle
Encyclopedia
The MECE principle, pronounced 'meesee', mutually exclusive
and collectively exhaustive
, is a grouping
principle and one of the hallmarks of problem solving at McKinsey. It says that when data from a category is desired to be broken into subcategories, the choice of subcategories should be
The MECE principle is useful in the business mapping process. If information can be arranged exhaustively and without double counting in each level of the hierarchy, the way of arrangement is ideal.
Examples of MECE categorization would include categorizing people by year of birth (assuming all years are known). 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).
Mutually exclusive
In layman's terms, two events are mutually exclusive if they cannot occur at the same time. An example is tossing a coin once, which can result in either heads or tails, but not both....
and collectively exhaustive
Collectively exhaustive
In probability theory, 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 outcomes 1, 2, 3, 4, 5, and 6 are collectively exhaustive, because they encompass the entire range of possible outcomes.Another way...
, is a grouping
Grouping
Grouping is a form of hierarchical knowledge representation, similar to mind mapping, concept mapping and argument mapping, all of which need to observe at least some of the principles of grouping....
principle and one of the hallmarks of problem solving at McKinsey. It says that when data from a category is desired to be broken into subcategories, the choice of subcategories should be
- mutually exclusiveMutually exclusiveIn layman's terms, two events are mutually exclusive if they cannot occur at the same time. An example is tossing a coin once, which can result in either heads or tails, but not both....
-- i.e., no subcategory should represent any other subcategory ("no overlaps") - collectively exhaustiveCollectively exhaustiveIn probability theory, 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 outcomes 1, 2, 3, 4, 5, and 6 are collectively exhaustive, because they encompass the entire range of possible outcomes.Another way...
-- i.e., the set of all subcategories, taken together, should fully characterize the larger category of which the data are part ("no gaps"),
The MECE principle is useful in the business mapping process. If information can be arranged exhaustively and without double counting in each level of the hierarchy, the way of arrangement is ideal.
Examples of MECE categorization would include categorizing people by year of birth (assuming all years are known). 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).
Use
The MECE principle is referenced extensively in approaches used by many management consulting firms.Example
- If two friends need to physically meet each other and they are geographically distant, they have only three MECE options: (a) Friend A goes to Friend B's location; (b) Friend B goes to Friend A's location; (c) Both friends meet at a location that is not their original ones.