Analyzing relationships of necessity is important for both scholarly and applied research questions in the social sciences. An often-used technique for identifying such relationships--"fuzzy set Qualitative Comparative Analysis" (fsQCA)--has limited ability to make the most out of the data used. The set-theoretical technique fsQCA makes statements in kind (e.g., "a condition or configuration is necessary or not for an outcome"), thereby ignoring the variation "in degree." We propose to apply a recently developed technique for identifying relationships of necessity that can make both statements "in kind" and "in degree," thus making full use of variation in the data: "Necessary Condition Analysis" (NCA). With its ability to also make statements "in degree" ("a specific level of a condition is necessary or not for a specific level of the outcome"), NCA can complement the "in kind" analysis of necessity with fsQCA.