The NCA philosophy is explained in four principles:
- Reduction of complexity
- Academic rigor
- Practical relevance
- History and future
Reduction of complexity
Necessary conditions help to unravel the complexity of social phenomena. When many factors contribute to social outcomes (“multicausality”), some factors are more important than others. Necessary conditions are extremely important: they must be present. If the necessary condition is not present, the outcome will not occur. Necessary conditions are essential, critical, crucial, vital, and cannot be replaced by other factors. Other factors cannot compensate for the absence of the necessary condition. Therefore the necessary condition operates in isolation from other factors. Necessary condition models can be parsimonious: simple, but also rigorous and relevant.
Necessary conditions are necessary, but not sufficient. A necessary condition allows the outcome to exist, but does not (automatically) produce it. Examples include:
- A high GMAT score is necessary (but not sufficient) for admission to a PhD-program
- HIV is necessary (but not sufficient) for AIDS
- Intelligence is necessary (but not sufficient) for creativity
- Management commitment is necessary (but not sufficient) for successful organisational change
- Contracts and trust are both necessary (but not sufficient) for successful buyer-supplier relations
Academic rigor
Surprisingly, necessity is not a common logic in the social sciences. When social scientists build or test their theories they attempt to predict the outcome. They identify (combinations of) factors that produce the outcome and use additive sufficiency logic. This means that single (combinations of) factors are sufficient (to increase the outcome), but not necessary and that (combinations) of factors can compensate for each other. However, when necessary conditions exist (factor or combination of factors) they can prevent the outcome to exist. Then sufficiency logic may not be able to predict the outcome correctly. NCA provides researchers with an approach and tool for identifying necessary conditions. This tool can complement the traditional sufficiency approaches and tools (e.g., regression, structural equation modeling) or configurational approaches and tools (e.g., QCA – Qualitative Comparative Analysis).
Practical relevance
Practitioners focus on necessary conditions. They usually adopt necessity logic: in complex situations they cannot manage all factors, so they focus on the believed “gotta have” (=necessity) factors that should not be absent for reaching a desired outcome. Results of a necessary condition analysis tell practitioners what (levels of) factors must be put and kept in place to prevent failure of a desired (level of) outcome, hence to allow the desired outcome to exist.
Researchers can use NCA to identify these necessary conditions. Gary Goertz’ (2003) first law states: “for any research area one can find important necessary condition hypotheses”.
History and future
Necessary conditions are everywhere. They have always been there, and they will always be there. Although the formal logic of necessary condition goes back to at least David Hume’s philosophy of science (1777) or even Aristotle, the necessity logic has been largely ignored in modern social sciences. Since Francis Galton’s (1886) discovery of correlation, the focus has been on OLS regression and the General Linear Model and related models (with variants like multiple regression modeling and structural equation modeling). Consequently the current focus of social science research is on sufficient causes.
Because of the enormous practical and theoretical relevance of necessary conditions, and the need for combining rigor and relevance in the social sciences, we expect a revival of attention for necessary conditions in academic social science research. It took sufficiency logic more than 100 years to become well-established. Building on this knowledge and with the currently available computer power, the growing NCA community will rapidly reach a similar level of understanding for necessity logic.