To truly be able to assist the business you support, you must understand what pitfalls to avoid when analyzing their data. All too often, people jump into “data mining mode” without thinking about what they are doing. They just play around and start drawing conclusions. I’m a huge fan of playing around in the data;

“Consistency” doesn’t have to mean “overkill.” How many meetings do you attend where several presenters show the same 20 slides – and often show a slide when there is no real need, just to meet a consistent format? Excel charts and tables embedded in PowerPoint slides may be the most commonly used format for business

There usually isn’t a shortage of opinions around the hot topic of performance metrics. My take is performance metrics are great. I love them! Now that you are angry with me, let me explain why by referencing the saying, “Don’t Hate The Playa/Playette, Hate The Game”. Urban Dictionary defines this saying as “Do not fault

This is the second in a two-part series. See Part 1 here In my last post, I introduced six guiding principles for creating real business intelligence. The first three were: Look at your business from the customer’s point of view Improve communication One version of the truth Now for the last three: 4. Hold management

In my last few posts, I spoke about the emerging Data Scientist role and the systems thinking approach that is so essential to it. I’ve been on a journey for several years now, supporting Tony Kolish, Senior Vice President of the Customer Support Services organization As part of this journey we’ve learned, among other things, that all the