Deciding which business processes to improve first is a challenge most corporate decision-makers face. The literature offers many approaches, techniques, and tools that support such process prioritization decisions. Despite the broad knowledge about measuring the performance of individual processes and determining related need for improvement, the interconnectedness of processes has not been considered in process prioritization decisions yet. So far, the interconnectedness of business processes is captured for descriptive purposes only, for example in business process architectures. This drawback systematically biases process prioritization decisions. As a first step to address this gap, we propose the ProcessPageRank (PPR), an algorithm based on the Google PageRank that ranks processes according to their network-adjusted need for improvement. The PPR is grounded in the literature related to process improvement, process performance measurement, and network analysis. For demonstration purposes, we created a software prototype and applied the PPR to five process network archetypes to illustrate how the interconnectedness of business processes affects process prioritization decisions.