How to Turn Yourself into a Big Data Leader

Big Data, predictive analytics, intelligence, customer insight, petabytes, social media analytics, data veracity and volume, the internet of things. A lot of new terms have entered the business vernacular in the past 5 years! These concepts are reshaping the way we think of business today and the way we prepare for the business challenges and opportunities for tomorrow. The term that seems to capture most the imagination of managers today is Big Data.

Big Data is essentially extremely large quantities of data (on customers, machines, operational processes, etc.) that allow for enhanced analysis and potentially revealing patterns, trends, and associations. I say potentially, and only potentially, because the power to unlock insight resides in the mind and capabilities of those who ask the right questions, create the right infrastructure, etc.

Understanding and unlocking the power of data is increasingly becoming non-negotiable. Just as we expect our managers today to have some degree of financial acumen, we should expect our managers to understand data and unlock its power through meaningful analysis. The University of Arizona where I work has developed a deep understanding of what data analysis can offer. Today my colleagues can predict with 75 percent accuracy how many asthma-related emergency room visits a hospital could expect on a given day just based on an analysis of data gleaned from electronic medical records, air quality sensors, and Twitter. 

What we are also developing is a deep understanding of the leadership and organizational skills that allow for such powerful analysis to be unlocked. Our research suggests that leaders need to build new skills and capabilities to drive deeper insight. Here are three things that you can do to become a Big Data leader:

1. Start by asking the big questions. A common myth around Big Data is that you need to understand data analytics inside out. The reality is that you need to be able to see the big picture first and understand what is changing in your world. Ask yourself what your most pressing challenges are first (e.g. customer loyalty, employee retention, etc) and then break these down into progressively smaller questions (e.g. which customer segments are most loyal/disloyal?). By doing this, you will start to discover where your insight is missing and where Big Data can help shed a light. What General Mills did is a great example of what's possible. Learn to collaborate. Many data analysts complain that they are expected to ask the questions and provide the answers. They are not the business managers, you are. Your success in Big Data will depend very much on your ability to collaborate. My advice is that you spend some quality time with your analytics team and ask them to give you a high-level view of what types of data they own, where it comes from and what timeframe can they cover. You will be surprised how much it will help you with defining what questions you can ask today and what data you will want to see captured in the future.
2. Try and then try some more. The nice thing about Big Data is that you can arrange it in a variety of ways, over different domains and periods of time. If the first attempt at gathering new insight does not give you what you are looking for, try again with a different data set or over a different period of time. You will be surprised what you will learn in the process. As a beginner, cut yourself some slack and don't be intimidated. Oh and you can always find yourself a mentor who has done this before!
3. Think of opportunities not just problem solving - Big Data will truly reward you only if you use it as a tool to figure out the futures you want and not just THE solution to your current problems. The wider is your perspective on what's possible, the easier will be to get breakthrough ideas that create a wider/richer future.

Big Data and the digital disruption that goes along with it is not something you can avoid, so the sooner you get on your digital journey the better.

Oh, and let me know if I or my colleagues can help!