I went straight to the obvious stuff, security lines, boarding delays, and kind of lost the thread on what Uber could actually own versus what's just the airport's problem.
Start by clarifying the scope: focus on airport-related waiting pain points where Uber can play a role, such as curb pickup, drop-off, and inter-terminal transfers. Then segment passengers by trip type (e.g., business vs. leisure, with/without checked bags) and prioritize pain points by frequency and severity. Finally, brainstorm solutions that leverage Uber's assets (network, data, app) and evaluate them using impact vs. effort, considering feasibility and regulatory constraints.
Pro tip: Acknowledge that airports are complex ecosystems with multiple stakeholders (airport authorities, TSA, airlines) and that Uber's influence may be limited; propose solutions that create win-win partnerships or leverage Uber's existing user base and data to reduce friction without requiring infrastructure changes.
Define which waiting pain points to address (e.g., curb pickup, drop-off, security, baggage claim) and what improvement means (e.g., reduce wait time, increase predictability). Confirm that the focus is on Uber's role within the airport experience.
Break down passengers by trip purpose, frequency, and needs (e.g., business travelers value speed, families value space). Map the end-to-end journey and pinpoint where waiting occurs and its impact.
Use a framework like frequency vs. severity or impact vs. effort to select the most critical waiting pain points that Uber can influence, such as pickup coordination or real-time information.
Generate ideas that use Uber's network, data, and app: e.g., dynamic pricing to reduce wait times, predictive ETAs, dedicated pickup zones, partnerships with airports for fast-track lanes, or in-app coordination with flight status.
Assess each idea on impact, feasibility, and alignment with Uber's business model. Recommend a prioritized set of solutions, noting potential metrics (e.g., wait time reduction, satisfaction) and next steps for validation.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.