Strategy question
Should Google Cloud build or buy a visualization tool like Looker?
- Strategy
- Hard
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What this question tests
Build versus buy strategic reasoning, weighing time to market, capability gaps, and integration cost.
How to approach it
- Clarify the goal: Google Cloud needs a strong BI and visualization layer to compete with AWS QuickSight and Power BI.
- Assess build: Google has strong internal data tools but lacks a modern, enterprise grade governed BI layer with semantic modeling.
- Assess buy: Looker already has an enterprise customer base, a modeling layer called LookML, and integrates well with BigQuery.
- Weigh time to market: building an equivalent from scratch would take years versus immediate enterprise credibility from buying.
- Recommend buy, noting Google in fact acquired Looker in 2019 for about 2.6 billion dollars, validating this reasoning.
- Define success as combined BigQuery and Looker deal attach rate and enterprise BI market share gains.
What a strong answer includes
- Structures the answer as a clear build versus buy framework, cost, speed, capability, and risk, rather than a gut call.
- References the real outcome, Google did acquire Looker, to ground the reasoning in fact.
- Gives an illustrative number, for example assuming building a comparable semantic layer would take 2 to 3 years internally.
- Flags integration risk post acquisition, like merging Looker's semantic model with BigQuery's native tooling.
Common mistakes
- Not knowing Google already made this real decision, which undermines credibility if the candidate seems unaware.
- Giving a build or buy answer with no framework, just a preference.
Likely follow-up questions
- What integration risks would you watch for in the first year post acquisition?
- How would you measure whether the acquisition succeeded 2 years later?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop