Estimation question
Estimate the time saved per employee using Glean and the resulting ROI.
- Glean
- Estimation
- Hard
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What this question tests
Estimation combining behavioral assumptions (search frequency) with a wage-based ROI calculation.
How to approach it
- State the goal: estimate average annual time saved per employee using Glean, and the resulting dollar ROI.
- Assume search frequency: an average knowledge worker performs roughly 5 internal searches a day across 230 working days a year, so about 1,150 searches annually.
- Assume time saved per search: Glean might cut average search-to-answer time from, say, 5 minutes of manual digging to 1 minute, saving about 4 minutes per search.
- Compute total time saved: 1,150 searches times 4 minutes equals about 4,600 minutes, or roughly 77 hours saved per employee per year.
- Convert to dollars using an average loaded hourly cost, say 60 dollars an hour, giving roughly 4,600 dollars saved per employee annually.
- Compare this to Glean's typical per-seat annual cost to frame the ROI ratio, noting all inputs are illustrative assumptions to be validated with real usage data.
What a strong answer includes
- Breaks the estimate into search frequency and per-search time savings rather than guessing an aggregate number.
- States every assumption (searches per day, minutes saved, hourly cost) explicitly and separately.
- Converts the time estimate into a dollar figure so it is directly comparable to the product's cost, which is the actual ROI ask.
- Notes that self-reported time savings tend to be optimistic and should be validated against real behavioral data like reformulation rates.
- Frames the result as a ratio against Glean's cost to make the ROI conclusion concrete.
Common mistakes
- Giving a final dollar figure without showing the search-frequency and time-saved assumptions behind it.
- Not comparing the result to the product's actual cost, missing the actual ROI framing.
Likely follow-up questions
- How would you validate the assumed time-saved-per-search figure with real data?
- How would this estimate change for a role that searches far more than average, like support agents?
- How would you present this ROI story to a skeptical CFO?
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More questions from Glean
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