Visual Process Analytics (VPA) is emerging as a discipline where Process Mining (PM) and Visual Analytics (VA) experts collaborate to simplify the analysis and enhance the understanding of complex processes. In this work, we focus on Directly-Follow Graphs (DFGs), a common visualization technique used in PM, and identify how some of its limitations can be overcome by complementing DFGs with a timeline-based visualization strategy used in VA systems analyzing event sequences obtained from event logs. To illustrate this, we have chosen the Road Traffic Management Process dataset, a well-known dataset to the PM community. We have identified four cases where DFGs struggle to easily convey the exact nature of the underlying processes and show how timeline-based visualization strategies help disambiguate findings.