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).