(this book review was originally published on The UX Bookclub)

The “Lean” idea has been around for a little less than a decade. It was first introduced by the author, Eric Ries, way back in 2008. Since then, Lean has taken a life of its own. Every entrepreneur, product manager, developer and tech designer has had to at least contend with and discuss the Lean practice if not fully adopt it as their own. And there is also a whole series of Lean books with an intense and loyal following (including Lean UX, which we reviewed in the past).

I am not an outsider to this way of thinking. I talk with my clients about the need to build minimum-viable products, or MVPs, all the time. I follow and have internalized a Lean philosophy when it comes to design and testing. I even have my own mantra I use to keep my Big Ideas in check, it’s:

“design simple, build small, test often.”

You can count me solidly in the Lean club, which is why I decided to “go back to the source” and read this book for myself.

I expected to read this book with a self-satisfied smile on my face punctuated by occasional nods of agreement and note taking. But I didn’t. I was left a little disappointed.

What Lean Is (aka. “the good parts”)

Ries defines a Lean organization as one that (1) tests their vision continuously, and (2) constantly adapts and adjusts as needed. He also says that this is a strategy uniquely suited to help entrepreneurs, because startups operate with too much uncertainty for the “plan, strategy, and market research” approaches big organizations can take.

Also, when you take a “learning centered” approach to what you design and build you will eliminate any wasted time and effort. If you are only ever building just enough to conduct an experiment and test your hypotheses (aka. the MVP or minimum-viable product) then you will never have wasted development or design time on features that never make it into the final product.

“The lesson of the MVP is that any additional work beyond what is required to start learning is a waste, no matter how important it may seem at the time.” (p. 96)

One of my favorite sections of the book is when Ries describes the relationship between quality and an MVP. In this section he succinctly explains that quality is only measurable after you know what exactly you need to build.

“If we do not know who the customer is, we do not know what quality is.” (p. 107)

Quality is an undefinable concern until after you know your users and what exactly they need in a product. Once you know the answer to those questions you will know exactly what a high-quality product should accomplish.

What Lean Shouldn’t Be (aka. “the not-so-good parts”)

I think my disappoint in this book arises from the fact that Lean has moved on and evolved from the time this was first published. It has expanded and grown to include a lot of design and user-centric practices. So when I encountered a few not-so-user-centric ideas in the book I balked.

For example, I saw several instances where Ries perpetuates the myth that “users don’t know what they want,” and puts a lot of focus on the “quantitative” ways to measure while discounting the “qualitative.”

Ries says that entrepreneurs should follow the “scientific method” and conduct “true experiments” in which they “generate a hypothesis that makes predictions and empirically test that hypothesis.”

Please don’t get me wrong. I love quantitative and experimental studies. There is nothing quite so satisfying as generating a hypothesis, establishing your metrics, and then gathering the data you need. Numbers are inherently pleasing and comforting and can answer big questions. But they can’t answer ALL the big questions.

And I would argue that they can’t come close to answering the big questions that start-ups, in particular, are facing. For example, a quantitative study will never be able to answer a “why” question. Lets say you have questions like…

A quantitative study will not tell you the answers to those questions. But there are all types of equally scientific and equally valid qualitative methods that will.

Furthermore, quantitative studies are usually beyond what startups are capable of because they have no metrics to measure. In order to have quantitative analysis you need the quantity of users to gather data from.

Ries also waxes poetic about the role and distinction of entrepreneurs from any other class of human. Entrepreneurs are placed on a shelf throughout the book. Granted, he makes it a very inclusive shelf, that he defines as “anyone trying to create new products or services under conditions of extreme uncertainty.” But it is a high shelf none the less.

“Startups are great, but for heaven’s sake, don’t make a religion of it!” — Alan Kay (CHI 2016 panel)


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