In general, suppose that a given MCDA problem is defined on m alternatives and n decision criteria.
Then, the total (i.e., when all the criteria are considered simultaneously) importance of alternative Ai, denoted as AiWSM-score, is defined as follows: For the maximization case, the best alternative is the one that yields the maximum total performance value.
[2][clarification needed] It is very important to state here that it is applicable only when all the data are expressed in exactly the same unit.
For a simple numerical example suppose that a decision problem of this type is defined on three alternative choices A1, A2, A3 each described in terms of four criteria C1, C2, C3 and C4.
These numerical results imply the following ranking of these three alternatives: A2 = A3 > A1 (where the symbol ">" stands for "greater than").