Two Kinds of Metrics & Data Intelligence
2 sides of the same data intelligence coins.
There are 2 kinds of people in the world, one who keeps falling into data analysis rabbit holes, and the other who has no idea what I am talking about.
Since you are reading this, It is safe to assume you have had your own journeys through rabbit holes. If you did dig in, what you had done was rummage through all the data as you had to solve a problem, or find an opportunity. The metrics you look at, are Opportunity/Firefighting metrics. That is one of the two kinds of metrics:
Heath / KPI Metric:
These metrics are measured frequently, and once added are rarely removed from dashboards. Examples include:
Revenue
CAC
ARPDAU
Opportunities & Firefighting
These metrics are usually measured in an Ad-hoc fashion, and may be short-lived on dashboards, or might not be added to dashboards at all. They are used to figure out problems or improvements. It is hard to define examples here, as each analysis demands different metrics. Most KPI ratios turn out to be good opportunity/issue-finding metrics as they are made up of 2 metrics, and the best of them have a metric measured against a counter metric
Special thanks to Amit who coined the word opportunity metrics, it captures the concept
From these 2 metrics, we can also derive 2 modes of data analysis/intelligence. No points for guessing.
Standard
This is in practice more data consumption than analysis. Once these dashboards are built, they rarely change as they are health metrics. This is typically done on standard dashboards. Since they rarely change, they can also be shared as templates across industries
Ad-hoc
This is on-demand when someone asks for something or something breaks and you try to figure out what broke. Multiple tools may be used for this analysis, right from pure SQL to a combination of BI tools + Excel magic. In addition, Ad-hoc analysis begets more analysis.
Folks over at Omni capture these 2 splits in their blog too.