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Lean Analytics book club questions

Here are 12 book club questions for Lean Analytics by Alistair Croll and Benjamin Yoskovitz, ordered to open easily and end somewhere worth arguing about. Copy them, print them, or bring them up one at a time.

Lean Analytics
Lean Analytics

Lean Analytics is Alistair Croll and Benjamin Yoskovitz's attempt to give early-stage companies a practical framework for using data to move faster.

Alistair Croll and Benjamin Yoskovitz · 2013 · 5h 45m

Full summary and key takeaways →

The 12 questions

  1. 1.

    What is the One Metric That Matters for the business or project you're currently focused on? If you can't name one number, what does that tell you?

  2. 2.

    Think of a metric you track that you suspect is a vanity metric. What would you replace it with that is more directly tied to value delivered?

  3. 3.

    Croll and Yoskovitz say the right metric changes at each stage. At what stage is your current project, and does your measurement focus match that stage?

  4. 4.

    The book distinguishes between leading indicators (metrics that predict future performance) and lagging indicators (metrics that confirm past performance). Which kind does your team primarily track?

  5. 5.

    Have you ever been in a situation where the dashboard was green but the business was declining? What was the gap between the metrics you tracked and what was actually happening?

  6. 6.

    They argue for qualitative research before quantitative metrics. How often do you actually talk to users before designing experiments or interpreting data?

  7. 7.

    Their business model matrix is prescriptive. Does your business fit cleanly into one of their six models, or does it straddle multiple ones? How does that complicate the framework?

  8. 8.

    What is the difference between a dashboard and an insight? When was the last time your data actually changed a decision?

  9. 9.

    The book was published in 2013. Which parts feel dated to you, and which principles seem timeless regardless of which tools or platforms are current?

  10. 10.

    Lean Analytics assumes you can run controlled experiments. What structural barriers — organizational, technical, or market-related — make experimentation hard in your context?

  11. 11.

    They distinguish between 'good enough' benchmarks and 'world class' benchmarks for each metric. Knowing the benchmark changes what counts as progress. What benchmarks do you use in your field, and where did they come from?

  12. 12.

    If you could only track three metrics for the next ninety days in your current work, what would they be and why?

How to run the discussion

  • Pick six to eight, not all of them. An hour of real discussion covers fewer questions than anyone expects, and racing the list is what makes a book club feel like homework.
  • Open with what people noticed, not what they concluded. Asking for a verdict first hardens opinions before anyone has heard each other.
  • Let the disagreement run. The questions below that split a room are the ones worth the time; the ones everyone answers the same way can be skipped.
  • Ask the quiet person a specific question. A direct, narrow question is far easier to answer than an open invitation to contribute.

Themes worth steering toward

If the conversation stalls, these are the threads that usually restart it.

Common questions

What are good book club questions for Lean Analytics?

Here are 12 book club questions for Lean Analytics by Alistair Croll and Benjamin Yoskovitz, ordered to open easily and end somewhere worth arguing about. The strongest openers ask what each reader noticed rather than what they concluded, and the discussion usually turns on startup metrics, data-driven decisions, product growth.

How long should a book club discussion of Lean Analytics last?

Most groups run 60 to 90 minutes of actual discussion. That is roughly six to eight questions, not all of them, so pick the ones that suit your group rather than working down the list in order.

What are the main themes in Lean Analytics?

Startup metrics, Data-driven decisions, Product growth, Business models, Experimentation. Those are the threads most likely to divide a room, which makes them the useful places to steer a discussion that has gone quiet.

Picking the next one? See books like Lean Analytics or questions for other book club picks.

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