ADFI Case Study

Case study · Data visualization

Making Africa’s digital financial inclusion data useful.

I designed a clearer way for researchers, analysts and policymakers to discover, understand, compare and utilize digital financial inclusion data.

My Role

UI/UX Designer

Company

Determinas Technologies & Africa Digital Financial Inclusion (ADFI) Facility

Product

ADFI data portal

Company

Determinas Technologies & Africa Digital Financial Inclusion (ADFI) Facility

Product

ADFI data portal

01 · Overview

The Africa Digital Financial Inclusion (ADFI) Portal is a data platform designed to make digital financial inclusion data across Africa more accessible and usable.

The portal brings together information covering financial inclusion rates, financial-service uptake, mobile money and digital payments, financial inclusion regulations, and socio-economic indicators. Its data sources include organisations such as the World Bank, GSMA, African central banks, national surveys, and industry associations.

A search-led entry point with country availability, indicators, reports and supporting content.

02 · The challenge

The challenge was to design an experience that could help very different users move from:

“I need information about financial inclusion in Africa.”

to:

“I found the right indicator, I understand what it means, compared the relevant countries, and can take the data with me.”

The ADFI Portal needed to support a wide range of users with very different levels of data literacy. The requirements therefore called for a user interface that could handle complex data without making the experience feel complex.

03 · My Design focus

Mapping the user’s journey gave the requirement a clear shape.

Direct Beneficiaries (DBs)

Discover

Find a country, indicator or topic through guided search.

Understand

See the data in a visual form suited to the search question. E.g table, map, bar chart, line graph.

Compare

Explore differences across countries, regions and time period.

Validate

Review information about data origin, source and freshness.

Export

Share directly or download the data or visualisation for use elsewhere

Compare

Explore differences across countries, regions and time period.

Validate

Review information about data origin, source and freshness.

Export

Share directly or download the data or visualisation for use elsewhere

04 · search-first architecturee

Let people begin with what they already know.

The architecture prioritises guided search where users are not just presented with a generic search bar, it went further by hinting on what they could search for, and what they can expect so that they have context when they arrive at the result page.

05 · The visualization workspace

Depth for experts, Orientation for everyone

Not every user wants to read a chart, however researchers and analysts may need the actual values. The requirements therefore called for the ability to convert charts into data tables, with sorting and filtering capabilities. I treated the chart and table as two representations of the same dataset rather than separate experiences.

Building trust into the interface

For a data platform, visual clarity alone is not enough.

Users need to know:

Where did this data come from?

Each visualisation should provide enough context for users to understand the origin and source of the data

When was it last updated?

This is particularly important when the platform is being used for research, policy decisions or further analysis.

When was it last updated?

This is particularly important when the platform is being used for research, policy decisions or further analysis.

I therefore treated metadata as part of the interface rather than something hidden elsewhere.

07 · What I learned

“Make complex information understandable without hiding its complexity.”

“Make complex information understandable without hiding its complexity”

That is the role I believe good product design plays in data-heavy products. The project reinforced that complex products need simple mental models. The answer was not to remove analytical depth, but to design it around a journey users could recognise.

It also shaped my understanding that data visualisation is largely an interaction problem. Choosing the right chart is only one part of the experience. Users also need to understand what they're looking at, change the parameters, compare values, inspect data and know where the data came from.

Need a clearer story
for complex data?

Need a clearer story for complex data?

Need a clearer story
for complex data?

Let's work together

Juliet Opara · UI/UX Product Designer

Dribble

Juliet Opara · UI/UX Product Designer

Dribble