What Are You Reading?
The Idea: If you’ve been reading my blog posts, you know that I’m always reading Harvard Business Review online. It’s a fabulous place for inspiration, idea generation, and staying current. But what business books are you currently reading? That was a question once posed to me by the then-CEO of a company I was seeking to join as chief audit executive. Back then I didn’t have a great answer — I was reading a lot of industry/professional magazines but nothing in-depth. That interview question changed everything: The next time I was asked, I wanted to have a great answer. Read on.
The Execution: On my desk at the moment:
- Keeping Up With the Quants by Thomas H. Davenport and Jinho Kim.
- Management's Guide to Sarbanes-Oxley Section 404 (updated to align with COSO 2013) by Norman Marks (available in the IIARF bookstore!).
- The Complete Idiot's Guide to Project Management by Sunny and Kim Baker.
Let me tell you a bit about the first book and why I recommend you put it on your desk, too. We’ve all heard about “Big Data” (ad nauseum at this point), but do you really know what it is? We all want to be more engaged and relevant in conversations about data. But do we know how to start? This book answers both questions.
The book is a practical guide to improving your understanding of data analytics. It helps enhance your critical thinking and analysis skills — the No. 1 skill that CAEs are hiring for according to The IIA’s 2014 Pulse of the Profession survey. It is easy to read and is filled with tools and examples that illustrate each topic. You do not need to be a statistician to understand it — but you will understand statistics better after you’ve read it!
I really want you to read the book and get tactical with data. But here’s a teaser to show you why I think it’s valuable.
Davenport and Kim break down the 3 stages and 6 steps of quantitative analysis (p.17) so that you can see what you’re dealing with and formulate a plan to address each step:
Stage 1 – Framing the Problem:
- Problem recognition — defining the question the analytics will answer and the decision to be made on the basis of the result
- Review of previous findings — “Has a story similar to this one been told before?”
♦ Fully understand the problem and why it matters. Develop a testable hypothesis (an educated guess).
Stage 2 Solving the Problem:
- Modeling and variable selection — “What is the dependent variable, the one you are trying to explain?”
- Data collection — finding primary and secondary data
- Data analysis — finding consistent patterns in the data
♦ Build a model to prove (or disprove) the hypothesis. Solve the problem.
Stage 3 – Communicating and Acting on Results
- Presentation of results and action — communicating results in an interesting and attention-getting way. “Nothing good happens unless this step is done well.” (p. 96)
I’m going to use this book as the foundation of my team’s approach to cracking the code on data analytics. Each step of the analytical process is a building block to the key competency of analytical/critical thinking, and a learning plan for each will be built.
If you’ve got a favorite business book or an approach to building your team’s or your own data analytics skill set, please share!
Posted on May 15, 2014 by Carolyn Saint
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