Below is a summary of lessons learned acquired from the expert interviews and the implementation of the project. 

• The MOD Sandbox Program was found to be a critical enabler for bringing diverse public agency interests together to approach the private sector with unified data standards and data-sharing expectations.
• Strong communication among project partners was important to establish a clear timeline of deliverables and foster discussions about how to visually represent certain trip planning concepts such as customer expectations for pickup location markers.
• Field tests revealed that although the City requires accessible transportation network company (TNC) vehicles, that does not necessarily result in accessible vehicle availability. Trip planning options for people requiring wheelchair-accessible TNC vehicles were ultimately removed, as it would be inappropriate to allow a user to plan a trip with a TNC connection if that connection was unreliable for users. 
• Replicating the exact trips during the testing interview was difficult because testers were attempting to plan a trip further into the future. This is a result of future trips being based on public transit schedules and not accounting for real-time vehicle availability (of both public transit and TNC vehicles).
• Accurate curb-level data can improve pedestrian routing for people with disabilities and older adults, but it would have required a great deal of field work and been cost prohibitive for the agency.
• It was technically challenging for the geocoder to interpret varied inputs in and appropriately geocode them.
• Allowing flexible timelines to accommodate different types of project demonstrations was suggested.