Book Review: Lean Analytics – great primer for moving to DDE world

 

So O’Reilly has this great program for bloggers, called the Reader Review Program. They will let me pick out a book of my choosing & read it for free, as long as I write up an honest review of the book here on my blog site. Because I know that I will eventually posting reviews here, I will be picking books that I think might have value to the audience that is following me. This is my first foray into this model. Right now, I think it’s an “everybody wins” thing, but I will pay heightened attention to how this affects the integrity & reputation of the site. Since I am generally reading 5-10 books at a time, I highly doubt that I will post blogs like this more than once or twice a year. Your feedback is welcome.

 

Lean Analytics by Alistair Croll & Benjamin Yoskovitz; O’ Reilly Media

    The title above will take you to OReilly’s site so you can delve further if you choose.

 

Review

    As the title suggests, Lean Analytics is a solid combination of two powerful movements in the Software Engineering world, Lean Agile and Data/Business Analytics. While there are several books out there discussing the need for data science and growth in statistics, this book really covers the What, How, and Why for using data to drive decision making in your specific business. Without being too technicial or academic, it introduces readers to techniques, metrics, and visualizations needed for several common business start-up models in operation in today’s world.

    

    I am ***REALLY*** fond of the Head-First Series of books and that is just about the only thing that could make this book better. After The Lean Startup this is probably the most useful book for those trying to iterate fast in today’s software engineering world. I found the information to be very straightforward and easy to follow. While I think the authors really tried to cram everything they could into the book (at times, making it read awkwardly), they introduce you to practical examples of how to use the material and when.

 

Several sections of the book are quite good… looking at some lightweight case studies of startups and the analytics they used to navigate muddy waters. The book tries to make all types of software business accessible. Ranging from how to categorize the growth phase of your company, what things to use during your value phase, what analytics are appropriate for various types of companies (mobile apps versus SaaS e.g.), and even how to operate within enterprises. As a result, though, the depth at times can be lacking but if you are looking for a breadth book that covers all of the basics this one might be good for you. Reading it is one of the reason I have decided to start my Masters in Analytics. With more information in the case studies, and more examples of actual data to look at and suggestions on how to avoid false metrics and gives guidance on what to look for.

 

One of the struggles that I am seeing at my place of employ is that Test is shifting away from automation roles and into data pipeline roles. This means we are just changing the way in which we deliver information so that others can analyze it and make the “adult” decision. This, imho, is not good. But it falls within Test Wheelhouse, so it is safe. Please Please Please instead grab this book and take a leadership role. This book will help us start the disciple move into a direction setting role instead of just a measurement one.

 

This will likely be the topic of my next post. Thanks for reading…