I started with engineering headcount and then kind of spiraled into infrastructure costs, licensing for map data, QA cycles.
Start by clarifying the scope and assumptions (e.g., which feature, team size, timeline) to show structured thinking. Then break down the cost into major components like engineering, design, data, and infrastructure, using rough order-of-magnitude estimates. Finally, tie the estimate back to product strategy and prioritization, emphasizing trade-offs and ROI.
Pro tip: Anchor your estimate in a simple formula (e.g., cost = team size × duration × fully loaded rate) and state your assumptions explicitly; this demonstrates both business acumen and the ability to communicate uncertainty effectively.
Ask clarifying questions to define the feature, target platform, expected quality, and timeline. State any assumptions you make to ground the estimate.
Break down costs into categories: personnel (engineering, design, PM, QA), infrastructure (servers, data storage), third-party services, and ongoing maintenance.
Use rough order-of-magnitude estimates: e.g., team size × duration × fully loaded salary for personnel; cloud costs based on usage; licensing fees for third-party data.
Sum the components to get a total cost range, then sanity-check against similar past projects or industry benchmarks. Adjust for risk and uncertainty.
Discuss how the cost estimate informs prioritization, ROI, and trade-offs. Consider opportunity cost and strategic alignment with Apple's goals.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.