Policymakers are in a balancing act when creating local energy transition strategies. Embedding new technologies in an existing energy system is highly complex. Policymakers must deal with multi-system interactions such as sector coupling, multi-scale effects such as bottom-up behavior and top-down policies, and requirements from local spatial planning, grid constraints, and resource availability. Decision support tools can help to navigate this complex landscape. This paper showcases a tool to support policymakers with heating strategies for Dutch neighborhoods. The tool is a GIS-based simulation model of the energy system developed using a collaborative approach and applied in a scenario study. Energy calculations are done over a year with an hourly resolution, while scenarios can include any future energy system configuration. The results highlight trade-offs between heating strategies, interaction effects with the mobility and electricity transitions, and bottlenecks in transition pathways. Collective district heating has less grid impact but higher emissions and costs, while individual (hybrid) heat pumps have lower emissions and costs but more grid impact. No-regrets and enabling technologies are insulation and smart charging of electric vehicles and boilers. Collaborative modeling with a GIS-based user-interface increases system understanding, including trade-offs, transition pathways, and bottlenecks, in a collective and interactive way. This creates a shared and well-grounded vision, resulting in robust local renewable energy strategies. •A multi-system, multi-scale decision support tool is an essential contribution to local renewable energy system planning.•There is no clear winner in renewable heating strategies in residential neighborhoods in The Netherlands.•Trade-offs occur in terms of costs, grid congestion, and emission reductions.•Models can be used to identify lock-ins and bottlenecks in energy transition pathways.•Collaborative modeling for renewable energy strategies increases system understanding and more robust decision-making.