Complexity is often regarded as a “problem” to solve. Instead of yet again attempting to solve complexity, we follow systems engineering practices and switch back to the problem domain. A major obstacle in the problem domain is the impossibility to universally define complexity. As a workaround, we explored complexity characterization and identified shortcomings of the existing characterizations. The shortcomings include lack of standardization, inconsistent semantics, system-centricity, insufficiently transparent reasoning, and lack of validation. To address these shortcomings, we proposed a framework to characterize complexity by adapting three questions (who, why, what) from the Five Ws information-gathering method. The answer to the WHO-question proposed four complexity viewpoints; the answer to the WHY-question proposed a two-dimensional structure to identify complexity drivers; and the answer to the WHAT-question derived generalized complexity challenges. We used a systematic mapping study (SMS) to validate the framework. In general, our findings suggest that papers with complexity solutions do not frame their research within the complexity problem domain, hindering the contribution evaluation. Through the viewpoints, we identified general research gaps of six solution directions. From the drivers, we noted three observations in the discourse of complexity origins: 1) a system-driven tendency, 2) a preference for concreteness vs. abstraction, and 3) an unclear distinction between origins and effects. Through the challenges’ findings we supported two hypotheses: 1) a system-centric preference; and 2) a solution-oriented vision. This application of our framework exemplifies its potential to facilitate and structure future research, both in the problem and solution domains.