Importance of Root Cause Analysis in the Data Analysis Process

A Simple Yet Powerful Tool for Uncovering the Real Problem

You might be naturally good at analytical thinking, but to be great at data analysis, you also need to learn how to think in creative and critical ways. This helps you come up with new ideas and look at problems from different angles. That’s what makes you a versatile thinker — something very important in data analysis.

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In this field, solutions are almost never right in front of you. You need critical thinking to ask the right questions and creative thinking to discover new and unexpected solutions.

Let’s look at some common questions data analysts ask while trying to solve a problem. One important question that often comes up is: What is the root cause of the issue?

A root cause is the reason why a problem occurs.

If we can find and fix the root cause, we can stop that problem from happening again.

One simple and useful method to find the root cause is the “5 Whys” technique. This means you keep asking “Why?” again and again until you get to the real reason behind the problem.

Most of the time, people find the answer after asking “Why?” five times, but it’s not a strict rule — it might take fewer or more questions to reach the root cause.

Example

Let’s check some business problems given as examples in this program to see how the “5 Whys” technique helps to identify the root cause of the problem during analysis.

Problem 1: An online grocery store is continuously receiving customer complaints regarding poor delivery.

To find the root cause, the data analyst uses the 5 Whys method.

1st Why: Why are customers complaining about deliveries? — Because many products arrive damaged.

2nd Why: Why are the products arriving damaged? — Because the packaging is too weak to protect the items during shipping.

3rd Why: Why is the packaging too weak? — Because the company switched to cheaper packaging materials.

4th Why: Why did the company switch to cheaper materials? — Because the procurement team was told to cut costs.

5th Why: Why was the procurement team asked to cut costs? — Because the company’s profits went down last quarter due to high advertising costs.

Root Cause: The poor delivery experience started because of a budget cut, which led to cheap packaging, causing damaged goods and unhappy customers.

Problem 2: A software company is receiving many complaints about slow app performance.

To find the root cause, the data analyst uses the 5 Whys method.

1st Why: Why are users complaining about slow app performance? — Because the app takes too long to load certain features.

2nd Why: Why do certain features take too long to load? — Because the server response time is very slow.

3rd Why: Why is the server response time slow? — Because the server is overloaded with too many requests.

4th Why: Why is the server handling too many requests? — Because the app doesn’t have proper load balancing in place.

5th Why: Why doesn’t the app have load balancing? — Because it wasn’t included in the initial development plan due to time and budget limits.

Root Cause: The app’s slow performance is caused by a lack of load balancing, which happened because of rushed development and limited resources.

In the world of data, asking the right questions is the key to solving problems. The 5 Whys method is a simple way to find smart solutions.

Keep asking, keep learning — and you’ll get better at finding the answers that matter.