There are many times when you need to explore your data from different perspectives and layers of detail. Your dashboards have superb visualizations and overviews of the current situation. But what if you want to do a root-cause analysis without a pre-described path for analyzing and quickly spot outliers?
Think about situations like these:
- What can be the reason behind a mark being identified as an outlier?
- How can I identify possible areas of improvement to my processes and systems.
- When something goes wrong, you need to determine what caused the situation to prevent it from happening again.
- When you need to identify and correct systemic issues that lead to errors or adverse events.
- When you need to identify and correct production problems or problems with curriculum or instruction.
And these are only some of the potential use cases for drilling down into your data.
In situations like these, where the problem is complex or a quick fix is not possible, Root Cause Analysis (RCA) can be a helpful method to solve it.
You can use RCA to identify all the possible causes of a problem, then test each one to see if it is the real source of the problem and optimize your process and resources or prevent future incidents from occurring.
Performing a root-cause analysis enables you to find a viable solution for a problem, rather than simply treating the symptoms, and can help you streamline your operations and boost your bottom line.