Eric the BA Business Analysis Reading List

Eric’s Business Analysis Reading List #174 min read

It’s been a very long time since the last edition of my Reading List. So long that I have over 30 articles in my waiting list (which means I could publish 6 or 7 editions right now!). So long that the 16th edition was published almost one year ago 🙂

But the wait is now over! After spending some time to redesign the website, I started publishing new articles back in November, and I have new ones on their way. Since one of my previous posts was about the influence of Artificial Intelligence on Business Analysis, I thought that dedicating this edition of my Reading List to this subject would be a good idea.

Go ahead and enjoy the read!

Too busy to crawl the web for interesting Business Analysis content? Not interested by social networks noise? Once in a while, Eric’s Business Analysis Reading List brings you a review of some of the best Business Analysis articles and websites.

From Eric the BA.com

In case you missed them, here are the most recent and most popular posts since the last edition of Eric’s Business Analysis Reading List:

  1. Are you a requirements bully?
  2. Tales of a BA: Framing processes with the SIPOC diagram
  3. Don’t be that Poor, Lonesome Business Analyst
  4. Learning about Business Analysis through the Ages
  5. Should Business Analysts fear Artificial Intelligence?

The new Eric the BA store also features some of my best premium content, including my latest ebook Taking your Business Analysis Deliverables to the next Level. Grab your copy now! 

From the Web

1 I’m a big fan of visual requirements. This is probably why I really liked this recent article by Xin Li, which covers many dimensions of the world of data science using various schemas and models, and explains its importance for the Business Analyst.

After defining some key terms & concepts about data science and their relationships, the author highlights how this could be used by a Business Analyst through various activities in the project lifecycle. The article ends with some warnings about using data as a part of Business Analysis.

2 Much of what’s been achieved recently in this domain was possible because of the quantity of data that is more and more available to organizations (ie what’s usually call Big Data).

In a recent analysis published in The Economist, there’s an interesting discussion about how we should regulate the new data titans as a society to prevent similar issues we had with the oil giants at the beginning of the 20th century. Such regulations could eventually have an interesting impact on Business Analysis in organizations with new requirements 🙂

3 While Artificial Intelligence is not exactly a new technology, it’s one of the most powerful trends in organizations these years. The problem with trends is that many organizations follow them without having a plan to get the most of them.

In a recent study published by the Harvard Business Review, over 3000 executives were surveyed to identify how organizations can be successful with AI. The key insights of this survey were the following:

  1. Don’t believe the hype: Not every business is using AI… yet.
  2. Believe the hype that AI can potentially boost your top and bottom line.
  3. Without support from leadership, your AI transformation might not succeed.
  4. You don’t have to go it alone on AI — partner for capability and capacity.
  5. Resist the temptation to put technology teams solely in charge of AI initiatives.
  6. Take a portfolio approach to accelerate your AI journey.
  7. Machine learning is a powerful tool, but it’s not right for everything.
  8. Digital capabilities come before AI.
  9. Be bold.
  10. The biggest challenges are people and processes.

The funny thing about this survey on how to deal with a new technology (AI in this case) is that it could probably apply to any new technology introduced in organizations, especially the last point (on which Business Analysts are essential 🙂 ).

4 Have you heard about Hype Driven Development (HDD)? It usually happens when organizations take new directions based on the most recent trends instead of using a proven fact-based approach.

If organizations don’t follow the more serious tips highlighted in the Harvard study I mentioned above, HDD could probably happen in your AI initiatives!

If you want to have a good laugh, go read this post by the guys at DaftCode.  It also makes me wonder if there’s such a thing as Hype Driven Business Analysis?

Upcoming posts

These posts are in the works:

  • Discover your Thinking Style and how to use it for better collaboration with your stakeholders (February 2018)
  • 7 Lists to get things done as a Business Analyst (March 2018)

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