“ How Today's Entrepreneurs use continuous innovation to create radically successful businesses ”

by Eric Ries

Book Cover

Outline

  • Entrepreneurship is everywhere, and is the genuine essence of innovation
  • Starting a product or service is only a matter of learning what the customer wants. Therefore the only important thing for a startup is learning.
  • The only way to actually learn what is working and what is not is validated learnings: through a scientific approach (formulate hypothesis and validate them through experimentation and measurement of the impact on core-metrics of the startup.)
  • Work in short cycles of Build-Measure-Learn feedback loop: Learn → Ideas → Build → Product → Measure → Data. Should be as short as possible / reduced WIP to increase agility.

Summary

  • New products/services are based on two main hypothesis:
    • Value hypothesis - the value that customer will get from the product/service
    • Growth hypothesis - how customer will discover the product or service
  • Start by leaping, but start by validating fundamental business assumptions, through communication (see by yourself, on the terrain, talk to prospects) or MVP. Anything else than validating core assumptions in an MVP is waste.
  • Launch new features as split-test experiments and measure impact. Follow a true scientific approach: clear hypothesis, predictions on what is supposed to happen, validation through experiment, measures on actual core-metrics.
  • Small batches are applicable to entrepreneurship as well. The smaller the releases, the faster the return on innovation.
  • Pulling instead of pushing: reacting to customer demands is more important than creating a three-years product strategy.
  • Strongly recommends to have complete cross-functional teams: full-time members from each functional department that is involved in the launch of a new product / service

Reading notes

  • The question is not can this product be built but should it be built
  • Lean startup method is considering 5 concepts:
    • Entrepreneurship is everywhere, not only startups
    • Entrepreneurship is a form of management
    • A startup’s only goal should be to acquire validated learning
    • Its fundamental activity should be a build-measure-learn feedback loop, after each should be decided: persevere or pivot.
    • Its progress should be measured through innovation accounting (based on how the growth and value engines are fundamentally working, not just row numbers)

Organization / entrepreneurship is everywhere:

  • Recommendation that a company is built through cross-functional teams which are accountable for learning milestones
  • Innovation is bottom-up and not predictable.
  • Give opportunities to the team to be the engine for innovation by allowing innovation sandboxes / split-tests
  • Entrepreneur is a job-title: inside an organization that already works, there should be entrepreneurs.

Starting / the leap of faith:

  • Acting on untested assumptions is called a leap of faith / have to go through that and that’s where courage must show.
    • Some empirical testing should be done first: Let’s make sure there are really some hungry customers eager to embrace the product/tech
    • Go see for yourself -> Validate it on the street / through prospects / by asking customers
    • This verification of assumptions should not be too short or too long.
    • MVP’s goal should be to test fundamental business hypotheses. Any work beyond what’s required to start learning is waste
  • Anything can be an MVP, even doing the work manually, or solving one customer’s problem.
  • If we do not know who the customer is, we do not know what quality is.

Looping / Build - Measure - Learn

  • On validated learning
    • (not post-rationalization neither basing strategy on assumptions which can be deadly for startups).
    • Value is not only having a better product but knowing better the direction to take.
    • Anything that does not contribute to learning is a form of waste.
  • Innovation accounting is done through three milestones:
    • Establish baseline (determine current state)
    • Tune your engine (try making better without changing strategy)
    • Pivot or preserve (compare to baseline and verify that we are truly doing better)
  • Cohort analysis segments the customer into groups based on their behaviour, then analysis based on %age. This gives better visibility than row numbers which can hide reality through big numbers that don’t tell anything.
  • It’s important to make formal hypothesis and establish a baseline to be able to establish causality links (determine that a decisions actually had effects).
  • Reports on evolution and changes should be Actionable (establish causality), Accessible (don’t need big explanations), Auditable (reliable enough for not doubting the data)
  • Pivoting is changing the strategy - can be through lots of things, like zooming in or out, changing customer segment or need,etc
  • Delivery strategy can have an immune system: if something breaks the product, we should be able to remove it quickly.

Accelerating / taking-off:

  • Three kinds of growth engines: retention based, viral (each % of current brings 1 new), marketing. Only one should be pursued at a time.
  • Knowing the growth engine can help predicting the growth and differentiating what comes from natural growth and what comes from product enhancement
  • The Five Whys: important problems should be diagnosed through asking oneself why 5 times at least. This permits to define where to push the investments.
  • Start with small specific changes at each level of the 5 whys, don’t re-process everything.
  • Proportional rule: invest proportionally to the symptom’s size
  • Training: the training program for new employees is the beginning of training generally speaking.
  • When making progress: be tolerant of the mistake the first time, make sure it never happens again.

About Reading Notes

These are my takes on this book. See other reading notes. Most of the time I stop taking notes on books I don't enjoy, and these end up not being in the list. This is why average ratings tend to be high.