Necessary Condition Analysis (NCA) is a methodological approach that uses a necessity causal perspective for identifying necessary conditions from data. Necessity causal logic implies that if a certain level of a specific condition is not present, a certain level of the outcome will not occur: if not X, then not Y. For example, a student will not be admitted to a university without a high school diploma; high levels of creativity will not exist without a certain level of intelligence; AIDS will not develop without HIV; and organizational change will not occur without management commitment. Such conditions allow an outcome to exist, but they do not guarantee that they will (the condition is necessary but not sufficient). A necessary condition may thus act as a bottleneck for the outcome. NCA provides the logic and analytical technique appropriate for studying these conditions. For the most up-to-date information on NCA, see Jan Dul’s book Necessary Condition Analysis (NCA): Principles and Application.