BlueSG
I led discovery and delivery for a charger-less parking model that removed a fleet-growth constraint while making vehicle and return-station availability easier for customers to understand.
A concise project brief that makes my individual contribution, collaborators and definition of success clear before the detailed process.
BlueSG owned enough EVs, but third-party charging infrastructure limited where those vehicles could operate. Users also faced high cognitive load and uncertainty when reserving and returning cars.
The constraint wasn’t the number of cars. It was the certainty of where they could be returned.
I connected behavioural, operational and qualitative evidence before choosing a solution. Each signal created a concrete design implication.
Only 36% of 350K home-map visits progressed to reserving a car or parking location; 64% dropped before reservation.
Perceived availability was partly an information and decision-load problem—not only a fleet problem.
Unclear map states, five competing options and low-readability controls made it harder to choose with confidence.
The product needed fewer decisions, clearer availability and stronger accessibility.
Eight cross-functional participants spent 180 minutes exposing unknowns around charging, station operations and reliable end-rental confirmation.
The solution had to work as an operational service before it could work as a UI flow.
The blueprint keeps the customer journey, visible product behaviour and operational responsibilities connected across the same sequence.
Looks for an available car and a workable destination.
Map and station information distinguish what can be reserved and returned.
Availability rules combine vehicle, battery and parking-station states.
Chooses a car with confidence that the journey can be completed.
A simplified reservation flow reduces competing choices.
The system holds the correct vehicle and destination conditions.
Travels with a clear understanding of the return model.
Guidance prepares the customer for a charger-less return.
Operations can see the rental and expected parking location.
Parks and scans the station QR code to confirm the location.
The app guides scan, evidence capture and end-rental confirmation.
The system verifies the station and flags exceptions for operations.
Receives a clear completed-rental state.
A visible confirmation removes ambiguity and repeat attempts.
Operations can manage vehicles, stations and exceptions beyond charging-only locations.
Scroll horizontally on smaller screens to follow the complete service.
Explore the original discovery boardThe artefacts were useful because they helped the team make choices. This is the evidence-to-decision trail behind the final experience.
BlueSG had vehicles, but charging-site coverage limited where they could operate.
Expand the service model to charger-less parking rather than treating vehicle acquisition as the answer.
Hardware options differed in installation effort, cost and lead time.
Use a QR-based proof of concept as the quickest practical path to reliable end rental.
Abandoned vehicles, exceptions and system states crossed customer, product and operations boundaries.
Design one future-state journey with both user and operational lanes.
I treated the operating experience and the interface as one system. Each lens solved a different part of the same problem.
Shaping the ecosystem, hand-offs and operating model.
Turning service decisions into clear, usable product behaviour.
Facilitated a three-hour Assumption Smash with eight cross-functional participants. The output exposed the unknowns that mattered: perceived availability, charging requirements, station operations and reliable end-rental confirmation.
Mapped a future-state journey across customer and operations touchpoints. QR-based end rental emerged as the best proof-of-concept option after comparing installation effort, cost and time to launch.
Translated the service decisions into reservation, driving and return flows, then used wireframes to resolve decision points before investing in visual design.
Ran four usability sessions across ten tasks, iterated on errors and comprehension, and instrumented the shipped journey with Mixpanel for drop rate and time-on-task monitoring.
I built a fully functional Figma prototype, recruited participants who matched the study criteria and used task-based testing to validate whether people could understand availability, choose a location and move confidently towards a reservation.
The selected station was easy to lose within a visually dense map.
Strengthened the selected-location state and surfaced the station name and address as a single, scannable block.
Vehicle and parking information competed for attention at the moment of choice.
Created a clearer information hierarchy, with progressive details for the car and the available parking options.
The primary action did not make the consequence of the current selection explicit enough.
Made the main call to action respond to the selected station or vehicle and kept it consistently visible at the end of the decision path.
With four sessions, I treated the results as directional usability evidence rather than population-level proof. The value was in finding repeated friction quickly, improving the design and pairing the prototype results with post-launch behavioural data.
The final interface connected three moments that previously felt fragmented: choosing a charger-less station, keeping the return reservation visible during the rental and completing end rental with clear vehicle checks and QR guidance.
Station, vehicle and parking availability are grouped around one clear reservation decision.
The reserved return location and battery requirement remain visible throughout the active rental.
System checks, parking context and QR instructions make the end-rental sequence explicit.
These constraints shaped the solution, the order of work and the compromises I made with the wider team.
The product team could not simply add charging locations wherever customer demand existed.
We separated parking confirmation from charging infrastructure and designed charger-less stations as a new service type.
A robust physical solution could delay the pilot and increase installation effort.
I compared options against effort, cost and launch time; QR confirmation offered the strongest proof-of-concept balance.
A simple customer flow still had to handle wrong locations, incomplete evidence and abandoned vehicles.
The future-state journey included system checks and operations exception paths instead of hiding complexity behind the happy path.
Funnel movement and weekly rentals were observed after launch; usability evidence came from four sessions across ten prototype tasks.
Explore the original discovery boardExpanded the operating model beyond charging-only stations.
Reduced reservation drop-off while increasing weekly rentals.
Gave operations a practical, lower-cost way to manage return locations.
Created a measurement plan covering conversion, idle time and support volume.
I made the physical parking model, digital end-rental flow and operations workflow one design problem rather than three separate workstreams.
The Assumption Smash prevented the team from optimising the reservation UI before agreeing how a charger-less return could be verified and operated.
I would run a staged station pilot and track end-rental success, exception rate, vehicle idle time, redistribution effort and support contacts by station type.