MECE principle

an example of MECE

The MECE principle, pronounced 'meesee', mutually exclusive and collectively exhaustive, is a grouping principle and one of the hallmarks of problem solving at McKinsey.^[1] It says that when data from a category is desired to be broken into subcategories, the choice of subcategories should be

1. mutually exclusive -- i.e., no subcategory should represent any other subcategory ("no overlaps")^[2]
2. collectively exhaustive -- i.e., the set of all subcategories, taken together, should fully characterize the larger category of which the data are part ("no gaps"),^[2]

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.

References

1. ^ Spencer, Tom (2008). McKinsey’s MECE framework. Sydney: Tom Spencer. http://www.tomspencer.com.au/2008/06/14/mece-analysis-framework-mckinsey-and-company/. 
2. ^ ^{a b} van Gelder, Tim, What is MECE, and is it MECE?, http://timvangelder.com/2010/06/04/what-is-mece-and-is-it-mece/, retrieved 5 June 2010 

See also

• Case analysis
• Partition of a set for a mathematical treatment