Competing With Data & Analytics
Bruno Aziza is a self-professed big data nerd.
His title at data analytics company SiSense: Vice President of Worldwide Marketing & Data Geek. His LinkedIn profile photo is of a guy displaying a t-shirt hidden under his dress shirt, Superman style, emblazoned with the words (you guessed it) Big Data Nerd.
Aziza?s credentials, both as a nerd and a thought leader, are robust. Prior to SiSense, he ran data analytics programs at Microsoft, Apple and Business Objects (now a SAP company). He is the co-author of two books in the business analytics space, one of them the best-selling tome, Drive Business Performance: Enabling a Culture of Intelligent Execution (Wiley, 2008). He is a fellow at the Advanced Performance Institute, an independent advisory group specializing in organizational performance, and he has over 12,800 Twitter followers at @brunoaziza.
In a conversation with Renee Boucher Ferguson, Data & Analytics contributing editor at MIT Sloan Management Review, Aziza talks about the burgeoning role of data analytics in today?s organizations, what it takes to be successful in utilizing data and analytics effectively (in a word: culture) and the role of innovation in a data-driven organizations.
What do you think has changed in the last two or three years since you wrote Drive Business Performance, in terms of how companies are developing an analytic culture?
Joey Fitts and I worked with Tom Davenport, Robert Kaplan and David Norton on the book. We gathered insights through interviews of organizations to determine what it takes to develop an analytical culture. We developed a methodology called the Six Stages of Performance that you go through as an organization to develop an analytical culture. That hasn?t changed.
But there are quite a few things that have changed. The first thing, the motivation for why we wrote this book, is that we saw that there is a divide in the industry. The first divide was, there are lots of books out there that talk about the technical capabilities required in order to be more analytical. And while they were good, they focused so much on the dashboards and the bells and whistles that people kind of forgot why they were doing it.