Many decision-making process models show some level of interdependency between the decision-making (DM) process and its subfunctions and the information available to that decision-making process. One example is the well-known “OODA: Observe-Orient-Decide-Act” model of Boyd [1] and another well-known example is Klein's Naturalistic or Recognition-Primed Decision model [2]. In the Information and Data Fusion (IDF) community, the point of view for process/system development is often centered about forming a least-uncertain estimate of a situational state as derived from multiple sources and sensors. However, there has been, unfortunately, relatively little interaction between the IDF and DM communities', and the critical examination of inter-process interdependencies needed to co-design these processes for optimum performance. This paper argues that IDF, Sensemaking, and DM processes cannot be optimally designed without consideration of such interdependencies, and a variety of details of such interdependencies of these processes are discussed. Among the issues commented on are: little accounting for the “Dual-process Models” of decision-making (factors of which have in fact been addressed by Nobel Laureates), integration of Information Foraging operations and the link to Sensemaking processes supportive of DM, important temporal effects in interprocess design, metrics involved in measuring and evaluating process interdependencies, new factors on the input side such as unstructured and linguistic data, among other factors. The spirit of the paper is as a research challenge for the IDF, cognitive, and DM communities (i.e., the CogSIMA community) and an appeal for joint efforts to evolve optimal designs of these important interdependent processes.