Data-driven decision making

Introduction to Data Literacy

Jess Ahmet

Content Developer, DataCamp

Why data-driven decisions matter

Data-driven decision making is the process of using data to make an informed decision about a specific problem and acting upon it.

Optimize performance
Gain a better understanding
Protect against risks
Determine the best course of action

Misconceptions about data-driven decision making

Data-driven decision making is not just for large organizations
It is not only the responsibility of the data team
It is not the only or the best answer to solve problems

headlines about being data-driven

Data-driven process

flow chart of the data-driven process

5 main steps that underpin every data-driven process
Defining the problem statement is very important
Taking action based on insights is the end goal

Problem statement

What is the problem you want to solve?
Guides the data-driven process

Typical problem categories:
- Describing the state of an organization or process
- Diagnosing causes of events
- Detecting anomalies or predicting events

question mark

How to define a problem

Guiding questions:
- What is the current situation?
- What do we need to know?
- Where do we want to be?
A good problem statement is:
- Clearly defined
- Actionable
- Realistic
It can help to start from a question that needs to be answered

Person placing parts of a problem into place

Example: customer satisfaction

How can we improve customer satisfaction?

Customer satisfaction is currently under our target. We need to know the main reasons for a negative score so we can take measures to improve customer satisfaction.

person taking a survey

Example: student performance

Why are average math scores of students in decline for the last three years?

The last three years math scores of students have declined. We need to know what the main causes are of this decline so we can take measures to counter it.

student filling in a test

Let's practice!

Introduction to Data Literacy