9.2 Introduction

Have you stopped to think about how much data we produce on a daily basis these days? You probably have heard some version of “data is the new oil” or “data is gold” or some variation. These mental images suggest a picture of our modern collective online footprint. Social media and online shopping are part of our daily routine and generate a tremendous amount of data. Most of us do not think about it, but the numbers are mind-blowing and continue to grow.

The Internet of Things (IoT), the billions of physical devices around the world that are now connected to the internet, all collecting and sharing data, contribute to the growth of data in organizations. The amount of data in the world was estimated to be 44 zettabytes in 2020. By 2025, we should have around 75 billion IoT devices in the world. Google, Facebook, and Amazon store north of 1,200 petabytes of information. Learning to work with this data has become increasingly essential, and coding has become a crucial skill.

Do you code? If you are new to coding, one of the things that may challenge you is knowing where to start. This issue often gets people and sometimes leads to a sort of panic. More important than memorizing syntax is learning the process. Coding involves creating something that solves a problem. Breaking big scary problems into small manageable ones is a core skill for coders. The same is true for problems in general: it is always easier to decompose complex problems into smaller, easier to explore and solve sub-problems. Such a process is somewhat similar to what you will accomplish during the Analyze phase of the DMAIC framework.

The purpose of this topic is to take you through the key activities of the Analyze phase of the lean six sigma DMAIC framework so that you can eventually apply them to projects at your organization. We also discuss crucial tools that you need to add to your lean six sigma toolset or use and that are essential to this phase of the DMAIC process.