Abstract: Our field’s growing attention to interorganizational network structure frequently builds on the Watts and Strogatz (1998) small world model. Our literature has identified “small worlds” — actual networks which simultaneously obtain relatively high clustering and short path length — in many contexts. Yet as we illustrate, these approaches use incommensurable methods and overgeneralized data, while yielding equivocal findings of structure on performance. To address these issues, we discuss underlying characteristics of primary network data and encourage researchers to detail their data and measures in order to facilitate comparative assessments. Further, we demonstrate a more rigorous approach, the “small world omega” statistic (Telesford et al., 2011), which may serve as a basis for comparing small world networks more systematically. We close with suggestions for ongoing research.