Two Peas in a Pod: Big Data and Systems Thinking

“Big Data” is a term that is becoming more and more familiar these days. It’s one of those concepts that sounds so simple when you read about it, but when you try to figure out how to begin identifying your own big data and how it can work to increase revenue, reduce or cut costs, and improve service[1], it turns into the sequel of Inception.

However, since embracing the concept of “systems thinking,” the idea behind big data optimization has become a lot easier to understand and even envision for my company. Every firm can benefit from experimenting with big data projects, and perhaps the key to go about it should be from a holistic thinking approach. One of the “big data do’s,” according to The Business Value of Big Data, is to ask the right questions initially so that you can avoid getting sidetracked. You know, not immediately worrying about the little data. Additionally, understanding an optimization plan from a simpler, macro-level perspective initially can really help everything fall into place going forward.

This aids a key theme for successfully using big data: clearly identifying your problem or goals, and keeping it macro-level. For any big data strategy, a few basic questions from a holistic perspective would entail:

For a big data experiment, it could be helpful to understand:

1. From which systems do we collect data?

2. How do these systems connect (or not connect), and would they benefit from connecting or disconnecting?

3. What are some small wins and big wins that could result from this project (will it increase revenue, reduce cost, or improve service in any way?)

A systems thinking framework will not only help to keep the project clear and strategic, but will also help you to communicate the project outline externally. Oftentimes, when you present a project or experiment idea externally (outside of your group), others view solely how it affects them and their role. Systems thinking framework can help them to understand how the project fits as a whole within the entire firm, and then how their part fits within that whole.

But why is keeping it simple so NOT simple? In the past, the moment I started to think about this, my friend, analytical side of the brain, likes to join the conversation (pump the brakes- you’ll make an appearance at the end). It’s very difficult to turn that off, but when you finally do, it’s actually quite relieving. When working through sprints on recent projects, I’ve begun to identify the end goal for each sprint, ensure that it nods to the ultimate end goal, and found myself stressing less and less about everything else. If I can’t see a particular task helping to get to those end goals or creating value, I drop it like it’s hot.

For more on systems thinking, click here.

[1] 2013. The Business Value of Big Data. The IBIT Report, 12. Retrieved from http://ibit.temple.edu/wp-content/uploads/2013/05/IBIT_BigData_v5.pdf