Open science is critically important for tackling today’s most pressing scientific challenges – especially those that demand complex interactions between large and distributed project teams (and increasingly teams-of-teams). The benefits of open science are vast (e.g., increased usability, reproducibility, and impact), but its requirements create barriers to entry for many researchers. Open science demands more intentional and explicit workflows for developing and managing data, models, experiments, and publications. These changes may require scientists to learn new skills, and the overall level of effort expended to deliver a research product may increase. As a result, many scientists view open science as theoretically good but practically burdensome. Lack of training in open science methods, time-scale mismatches between the cost (now) and benefits (later), and inconsistent cultural norms across different scientific communities all contribute to this perspective. Additionally, it can be easy to be overwhelmed by the plethora of tools and myriad of mandates designed to facilitate open science. More often than not this leads to an “as little as possible” approach in which open science is viewed as a box-checking exercise standing between a scientist and publication. In this presentation we offer ten bite-sized, cost-effective actions that scientists can start implementing to move toward a more open way of executing and publishing their research. These recommendations individually target “boots on the ground” scientists, project managers, and funding agencies and are based on our experiences as a data management lead, lead software engineer, and project PI for a large collaborative project in the field of MultiSector Dynamics. Our goal is to recast open science as a series of small, tractable actions as opposed to a monolithic all-or-nothing decision.