Building Analytics Teams: Harnessing analytics and artificial intelligence for business improvement

by John K. Thompson, Douglas B. Laney (Foreword)

Master the skills necessary to hire and manage a team of highly skilled individuals to design, build, and implement applications and systems based on advanced analytics and AI In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success. The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs. The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects. By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization. This book is for senior executives, senior and junior managers, and those who are working as part of a team that is accountable for designing, building, delivering and ensuring business success through advanced analytics and artificial intelligence systems and applications. At least 5 to 10 years of experience in driving your organization to a higher level of efficiency will be helpful.

Genres: Business, Artificial Intelligence, Management, Technical

394 pages, Paperback

Published June 30, 2020

About the author

Two years after publication, the book remains in the top 10 best selling books in the analytics category on Amazon.

The book is targeted to non-technical C-level executives. The premise of the book is to give these executives a glimpse into what analytics are, what can be accomplished, what successful projects and teams look like and how they can engage with technical professional to implement successful analytics projects to drive operational results.

The book is available at:
- Amazon & Audible: https://lnkd.in/evpeU6p
- Hudson Books online: https://www.hudsonbooksellers.com
- Selected Hudson Books stores.
- I have seen the book in Hudson's in Newark Airport.
- Please tell me where you have seen the book.
- Technics Publications: https://technicspub.com/
- Barnes&Noble: https://www.barnesandnoble.com/w/anal...

I hope that you find the book valuable and useful

Reviews

[Charl Botha · Rating 2 out of 5]

I bought both the Kindle and the Audible versions of this book.

I really had to force myself to finish this book, primarily via audible, because there's really not much topical value in it, and it's not well-written.

It doesn't help that the narration is also sub-par. It was hard getting used to her voicing of each and every letter in each and every acronym, and there are many. Listening at 1.7x reduced the discomfort.

As an example of the writing issues, Thompson really loves using at least three synonyms for a thing in the same sentence.

As an example of the lack of valuable and applicable content: Thompson often falls back into his personal views of the world, which generally are pretty OK, but the book's title is "building analytics teams" not "John's tips and rants about how people can be really irrational and data science folks are different".

There is some non-obvious value in the book, but the ratio between that and the rest is too low.

I'm sure Thompson has been quite successful and he does sound like a good guy, but this book does not excel in the teaching of how to build analytics teams.

[Jess · Rating 4 out of 5]

I'm giving it 4 stars for the content and how informative it was. I'd give it 3.5 for my interest in it and how it was written. I think overall, it could be cherry picked for what someone would need from it. And it wasn't poorly written, it just was written in a textbook way, which I guess is what it is. But there are anecdotes in there that are unlike a textbook, so I think a different presentation to it could have made the book a faster and more interesting read. 

Even though this is work-related, I think a lot of it was pretty interesting. Though, I still have a massive dislike and distrust of AI, and it's not because I think they're going to become sentient and take over. The book does mention we can just "turn computers off" and it's "not like the movies where you won't be able to," and I don't know anyone who truly thinks that. But I do know that AI has gotten out of control. It is in places where it shouldn't be, looking at you people using it for art. It is bad for the environment. And it is taking away jobs and not even doing them well or properly. I'm sorry, but add absolutely IS a word, and I NO I DID NOT mean dad!!!!!!!!!!!!!!!

[David · Rating 3 out of 5]

Overall, I probably wasn't the ideal audience. I see a book title with the word "analytics" and I am all in. Inteded for a data science or more technical audience. I have listened to hundreds of books and this was the worst editing of a book ever. So many errors, duplication, and just sloppy editing. Also, strange to have a female narration given the author is a male. Parts of the book where he is talking about his wife were unnecessarily confusing. I did love the "don't worry too much. You'll make yourself sad." quote from Danny Elfman. Back in the Oingo Boingo days. Not too many seem to appreciate or know that music.

[Ross Beck-MacNeil · Rating 4 out of 5]

I enjoyed this book, even though it wasn’t the best written. One of my key takeaways is that an analytics team should be driving strategy, so they way the team works with stakeholders is crucial. When Daveport provided a list of traits that make for a good leader of an analytics team, I recognized myself in most of them, although I should probably work on cultivating “intense” curiosity. It also seems that while leaders of analytics teams don’t need to be extroverted, they should enjoy talking to everyone and anyone about their analytics problems/questions. I am not quite there, instead enjoying coding up solutions much moire, so I will be sticking to a sole contributor role for now.

[Miguel · Rating 3 out of 5]

Good book, not much practical advice

[João Maia · Rating 2 out of 5]

Achei a leitura chata, excesso de exemplos mas encaro isso como gosto pessoal , e não me acrescentou muita coisa.

[Kris · Rating 5 out of 5]

Definitely worth re-reading again many times.

[Kevin · Rating 1 out of 5]

Was really disappointed by the quality of the writing in this book. Felt disorganized and that it needed more editing.

[Carlos · Rating 4 out of 5]

A broad look at how to create and run an analytics team by scratch...lots of helpful insights included.