I have data, but I need information

I have a confession:  I am a statistics and data junkie.  I’m not sure where it came from… perhaps it’s from my love of baseball growing up, from playing Fantasy Football (in which I never missed a Fantasy playoff in a league I’ve played in), or tracking the Rivals star status of Texas A&M’s football and basketball recruits to assess whether I should get excited about the upcoming seasons or start blogging in support of a coaching change.  Regardless of where it came from, I have built my post-MBA career on an ability to leverage data to decipher insights and recommend future strategy.  Especially working in the BI space, I have found that organizations that understand the importance of leveraging data for competitive advantage tend to be more successful than others.

This is a good time to be an analytics professional.  Today, like no other time in history, there is a plethora of data in the world.  From organizations siphoning terabytes (and even pedabytes) of operational business data into massive data warehouses, to all of the information you can search for on Google, to the clickstreams of your website visitors, to the massive amount of data aggregators providing syndicated lists & analyst reports, to all of the chatter on the blogosphere and Twitterverse, we are swimming in an ocean of data and organizations have an endless appetite for it. 

In fact, every company can probably say these two things:  1.) We have too much data and 2.) We don’t have enough data. 

Or perhaps this is what they are saying:

• “We have too much data”  We are having a difficult time getting value out of the data we have. 
• “We don’t have enough data”  We don’t know what we don’t know or need to know.

Both of these statements/issues are related.  I have heard multiple times, especially on consulting engagements, this term:  “We are data rich, but information poor.”  This is a good statement, because it recognizes the reality that a company has a lot of data at its disposal (like most organizations) but that’s all it is… data.  It means that the organization is spending a lot of energy collecting and delivering data but what it really needs is information… insights that can drive actions that get results. 

How do I do it?  How do I take all of the data I have, or better said want to collect, which has limited value and transform it into information and insights which are extremely valuable? 

At a high level, here’s how you make it happen

1.  Follow Steven Covey’s rule from “The Seven Habits of Highly Effective People” and start with the end in mind.  In order for your data to be effectively leveraged, you must first ask the question:  “What do I want to learn?” and evaluate the questions that you will answer through your data.  
2. Pre-define your data to support the questions you want to answer and develop systems to ensure that it is consistently collected and codified according to this definition.  Your data must support your analysis, rather than your analysis support your data if the quality of your information will drive the maximum value you want to achieve.  This is the hardest work, because in many cases you may not know what you don’t know yet.  As a result, this is fluid process.
3. Collect data consistently, accurately, and with proper governance.  This is especially important when your analytical data is coming from many sources in your organization.  If your organization is truly going to be data and insights driven, then data governance and data quality must be a high priority and governed at a high level in the organization. 
4. Review, analyze, and refine often.  Once you start gaining insights, you will start to ask deeper questions and create a market for intelligence in your company.  At this point, we would start over at #1 and once again ask the question:  “What do I want to learn and how do I need to collect and define my data to get me the answer I need?” 

This is key to truly becoming data-driven.  Good data is intelligently conceived and is supported by good processes.  You can’t have good processes without good data and you can’t have good data without good processes.  The two work hand-in-hand.  It is hard work, but the value that insights can give over mere data is well worth the effort to align an organization from being a data consumer to an insights creator.