Estimation question
Assume the US Govt wants to provide free internet storage to all its citizens. Create a program to manage it and estimate the 3 year cost for the program.
- Estimation
- Hard
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What this question tests
Structured estimation combining program design thinking with a defensible cost model over time.
How to approach it
- Scope the program: define storage tier, like 100 GB per citizen, and eligibility, all US citizens or opt-in only.
- Estimate the user base: roughly 330 million citizens, assumed with an opt-in rate around 30 to 50 percent in year one, growing over time.
- Estimate per-user infrastructure cost: cloud storage cost per GB per month, applied across the storage tier and active user count.
- Add program costs: initial build, ongoing engineering and support staff, and security or compliance overhead for a government system.
- Project growth over 3 years, assuming rising adoption and modest unit cost decline as storage gets cheaper over time.
- Sum year one through three costs into a total, stated as an order of magnitude range with assumptions clearly flagged.
What a strong answer includes
- Defines the scope precisely, storage tier and eligibility, before estimating cost, since these choices swing the answer by orders of magnitude.
- Uses a realistic adoption curve, not assuming instant 100 percent opt-in from all 330 million citizens.
- Separates infrastructure cost from program overhead, like staffing and compliance, which are easy to overlook.
- States a 3 year total as a range with visible assumptions rather than one falsely precise number.
Common mistakes
- Assuming full population adoption in year one with no ramp up curve.
- Estimating only cloud storage cost and ignoring staffing, support, and compliance overhead.
Likely follow-up questions
- How would the cost change if storage prices fell 20 percent over the 3 years?
- What would you cut first if the budget came in under this estimate?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop