Deep analytics discovers new patterns and trends in your data
You already have KPIs, critical variables that you monitor using dashboards. How can you identify new ones? What patterns exist in your data that you don’t know? How can you find data-driven solutions to your biggest problems?
It’s time to start asking deep questions – as many as you can, and as fast as possible.
You have a problem.
Visitors don’t convert.
Patients have bad outcomes.
Players have bad performances.
Your users aren’t getting enough value, etc.
The core concept of deep analytics is to focus on some entities (in this case, “problems”), and compare them to a background of “peer” entities. Deep analytics scans all variables, and combinations of variables, to find the strongest indicators that differentiate “problem” from “peer.” The results are returned instantly, sorted by strength of confidence, visualized and explained in language you understand.
As you view the results, you notice some indicators for “problem” with which you’re already familiar. But there are other strong indicators that give you insight…and generate new questions. You follow the rabbit hole, asking question after question, until you discover new insight that fundamentally changes your business.
If deep analytics is confined to data scientists, your organization will fall behind . . . slowly
How many years of experience do you have in your industry? What is the cumulative sum of years-of-experience for all employees in your organization, or across your user base? The knowledge stored in your brain and in the brains of your workforce/users is a critically-important “organic” data source.
Deep analytics is designed to integrate your digitally-warehoused data with the organically-stored data in the brains of your workforce/user base. The key component to success in deep analytics is “organic intelligence” – the ability of a business expert to ask deep questions, integrate the answers with their own knowledge, and communicate insights to other business experts.