Solving business problems with data

Data Fluency

Konstantinos Kattidis

Data Analytics Lead

Scenario - declining user engagement

Katia is working for a tech startup providing software solutions to businesses
She is reviewing KPIs (Key Performance Indicators)
She identified a drop in user engagement metrics:
- Decrease in the number of active users
- Increase in customer support tickets

Woman looking at a KPI dashboard

By combining analytical skills and business knowledge, she formulates several analytical questions:

What is the trend in active user numbers?

What features are causing customer support ticket increase?

Is there a correlation between user engagement and software performance?

Now she can investigate further with the use of data and analytics

Woman looking at a list of questions

Man looking at two options

Identify the business problem using clearly defined KPIs
Transform the business problem into specific analytical questions that can be answered using data

Data-fluency skills:

Strong understanding of KPIs that drive the business
Monitoring of those KPIs to identify problems
Defining new KPIs to monitor success of initiatives
Setting targets for the KPIs to make sure performance is in line with the desired outcomes

Man looking at a KPI graph which is below target

Translating business problems into well formed analytical questions
It helps using data to solve these problems
Forming SMART questions:
- Specific, Measurable, Actionable, Relevant, and Time-bound
So that the analytical solution addresses the business problem

Man showing the translation of business problems to analytical questions

People sharing ideas to form analytical questions

Collaboration with cross-functional teams is important as it helps:
- Gain access to diverse perspectives, domain expertise, and data sources
- Enriches their understanding of the business problem

Allowing them to ask more insightful and relevant analytical questions!

Data Fluency