This paper argues that the foreign direct investment (FDI) data commonly used to test political science theories about FDI often diverge from the theorized about phenomena in ways that can introduce bias and complicate hypothesis testing. I describe some of the key conceptual issues surrounding the quantification of FDI, how commonly used data deals with these issues, and the extent to which those coding rules allow or prevent these data from speaking to political science theories. I show that the empirical relationship between democracy, political risk, and multinational corporations behavior is significantly impacted by "getting the measure right." I conclude by arguing that political science theories about FDI speak to such a wide variety of empirically and conceptually distinct phenomena that conflating them as "FDI" does a disservice to the complexity of the topic.