Like manufacturing in the 1800s, the field of analytics needs to go through its own industrial revolution. Analytics processes today are usually created in an artisanal fashion with a lot of care and customization. That’s okay in many cases, and the artisanal approach often still is appropriate. However, we must also push analytics forward to another level of scale and impact. The industrial revolution took manufacturing processes from an artisanal practice to a modern technological marvel that is able to manufacture quality items at massive scale. The same type of revolution must happen with analytics. Operational analytics deploys analytics at industrial scale just like traditional manufacturing processes enable bowls to be produced at scale.
Making analytics operational doesn’t remove any of the steps historically required to build an analytics process. Rather, it takes the process further. Framing and designing each new analysis is still necessary. Building a prototype of the analysis and testing multiple iterations of it to make sure everything works correctly is still necessary. Only at that point can the analytics process be promoted to an operational process, turned on, and executed in an automated fashion. After being turned on, the performance of the analytics process must be monitored constantly just like a real assembly line is monitored.
Operational analytics is about embedding analytics within business processes and automating decisions so that thousands or millions of decisions every day are made by analytics processes without any human intervention. Five to ten years from now, virtually no business will remain untouched by this trend. Resistance is futile. Your organization needs to implement operational analytics, and this book will help you get started. How has this evolution come to pass and what is required to understand and implement operational analytics in your organization? Sit back, get comfortable, and prepare to find out!