🚧 This site is a work in progress — New case studies and stories are coming soon. 🚀
Scaling Data Strategy
From fragmented dashboards to a unified data experience
At IAG, data is more than dashboards — it drives flight punctuality, financial planning, and the decisions that move millions of passengers every day.
My role as a Data Product Designer was to bridge the gap: turning fragmented reports into a unified experience and scaling a strategy across airlines, teams, and business needs.
↘︎ Scroll to follow the story, or choose an Act to explore in depth.
ACT 1
The challenge & goals
Scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
When I joined IAG, the data landscape looked more like a patchwork than a system. Each domain —Finance, Operations, Procurement, Fleet…— was producing dashboards on its own terms. Different colors, layouts, and rules. No common language.
Adoption was painfully low: less than half of critical dashboards were even opened on a regular basis. Business Owners admitted it was easier to ping someone on Teams than to search. Data Analysts were losing 30% of their time explaining where to look or how to read.
The goal became crystal clear: scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
ACT 2
The team & my role
A bridge between different worlds
I wasn’t part of a design team. In fact, I was the only designer inside Skynet, the Data & Insights group at IAG. Around me: Insight Managers with deep domain knowledge, Business Owners struggling with adoption, and Data Analysts overloaded with requests.
My role was to bridge these worlds — using governance, research, and design to translate complexity into a framework that could scale across the group.
ACT 3
Research: listening first
I started by listening.
In discovery sessions with each domain, patterns began to emerge:
Insight Managers: every team defined KPIs differently.
Business Owners: impossible to compare dashboards across OpCos.
Data Analysts: “We spend hours reformatting and re-explaining the same metrics.”
Governance workshops confirmed it: without a shared design language and clearer access, adoption would never grow. The problem wasn’t the lack of data. It was the lack of structure around it.
ACT 4
Phase 1: Standardization - Data Design System
The first step was to create that shared language. I designed a Power BI Design System, built in Figma, aligned with IAG’s brand guidelines.
The impact was immediate: in Finance and Operations, dashboard adoption grew by 35% in just three months. A Business Owner summed it up perfectly: “We finally speak the same visual language.”
ACT 5
Phase 2:
Centralization-Analytics Hub
Once dashboards spoke the same language, people needed a single place to find them.
That’s how the Data Marketplace came to life: a hub where datasets, reports, news, and tools all lived together.
In usability tests, the difference was clear. Stakeholders were 40% faster at finding what they needed. As one Data Analyst said: “Before, we’d ask on Teams where a dataset was. Now we know exactly where to start.”
ACT 6
Phase 3: Scaling with AI
With a common design language and a centralized entry point, the next step was scale.
I prototyped SkynetGPT, a chatbot embedded in the portal. Stakeholders could now ask questions in natural language, generate narratives, and receive dynamic visualizations in seconds.
During demos, one Business Owner captured the potential: “If I can just ask and get a chart ready to share, adoption skyrockets.”
This was the bridge into the future: from searching for dashboards to simply conversing with data.
ACT 7
Impact & Learnings
Scaling the data strategy at IAG wasn’t about building more dashboards. It was about designing governance and experiences that turned data into something people could actually adopt — and that the business could rely on.
The transformation unfolded in phases:
From fragmentation → to consistency with the Design System.
From dispersion → to centralization with the Marketplace.
From dependence → to autonomy with SkynetGPT.
The numbers told the story:
+35% adoption in Finance & Ops dashboards.
40% faster access to datasets and reports.
Stronger confidence in critical KPIs like operational punctuality and financial metrics.
🚧 This site is a work in progress — New case studies and stories are coming soon. 🚀
Scaling Data Strategy
From fragmented dashboards to a unified data experience
At IAG, data is more than dashboards — it drives flight punctuality, financial planning, and the decisions that move millions of passengers every day.
My role as a Data Product Designer was to bridge the gap: turning fragmented reports into a unified experience and scaling a strategy across airlines, teams, and business needs.
↘︎ Scroll to follow the story, or choose an Act to explore in depth.
ACT 1
The challenge & goals
Scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
When I joined IAG, the data landscape looked more like a patchwork than a system. Each domain —Finance, Operations, Procurement, Fleet…— was producing dashboards on its own terms. Different colors, layouts, and rules. No common language.
Adoption was painfully low: less than half of critical dashboards were even opened on a regular basis. Business Owners admitted it was easier to ping someone on Teams than to search. Data Analysts were losing 30% of their time explaining where to look or how to read.
The goal became crystal clear: scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
ACT 2
The team & my role
A bridge between different worlds
I wasn’t part of a design team. In fact, I was the only designer inside Skynet, the Data & Insights group at IAG. Around me: Insight Managers with deep domain knowledge, Business Owners struggling with adoption, and Data Analysts overloaded with requests.
My role was to bridge these worlds — using governance, research, and design to translate complexity into a framework that could scale across the group.
ACT 3
Research: listening first
I started by listening.
In discovery sessions with each domain, patterns began to emerge:
Insight Managers: every team defined KPIs differently.
Business Owners: impossible to compare dashboards across OpCos.
Data Analysts: “We spend hours reformatting and re-explaining the same metrics.”
Governance workshops confirmed it: without a shared design language and clearer access, adoption would never grow. The problem wasn’t the lack of data. It was the lack of structure around it.
ACT 4
Phase 1: Standardization
Data Design System
The first step was to create that shared language. I designed a Power BI Design System, built in Figma, aligned with IAG’s brand guidelines.
The impact was immediate: in Finance and Operations, dashboard adoption grew by 35% in just three months. A Business Owner summed it up perfectly: “We finally speak the same visual language.”
ACT 5
Phase 2: Centralization
Data Marketplace
Once dashboards spoke the same language, people needed a single place to find them.
That’s how the Data Marketplace came to life: a hub where datasets, reports, news, and tools all lived together.
In usability tests, the difference was clear. Stakeholders were 40% faster at finding what they needed. As one Data Analyst said: “Before, we’d ask on Teams where a dataset was. Now we know exactly where to start.”
ACT 6
Phase 3: Scaling with AI
With a common design language and a centralized entry point, the next step was scale.
I prototyped SkynetGPT, a chatbot embedded in the portal. Stakeholders could now ask questions in natural language, generate narratives, and receive dynamic visualizations in seconds.
During demos, one Business Owner captured the potential: “If I can just ask and get a chart ready to share, adoption skyrockets.”
This was the bridge into the future: from searching for dashboards to simply conversing with data.
ACT 7
Impact & Learnings
Scaling the data strategy at IAG wasn’t about building more dashboards. It was about designing governance and experiences that turned data into something people could actually adopt — and that the business could rely on.
The transformation unfolded in phases:
From fragmentation → to consistency with the Design System.
From dispersion → to centralization with the Marketplace.
From dependence → to autonomy with SkynetGPT.
The numbers told the story:
+35% adoption in Finance & Ops dashboards.
40% faster access to datasets and reports.
Stronger confidence in critical KPIs like operational punctuality and financial metrics.
🚧 This site is a work in progress — New case studies and stories are coming soon. 🚀
Scaling Data Strategy
From fragmented dashboards to a unified data experience
At IAG, data is more than dashboards — it drives flight punctuality, financial planning, and the decisions that move millions of passengers every day.
My role as a Data Product Designer was to bridge the gap: turning fragmented reports into a unified experience and scaling a strategy across airlines, teams, and business needs.
↘︎ Scroll to follow the story, or choose an Act to explore in depth.
ACT 1
The challenge & goals
Scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
When I joined IAG, the data landscape looked more like a patchwork than a system. Each domain —Finance, Operations, Procurement, Fleet…— was producing dashboards on its own terms. Different colors, layouts, and rules. No common language.
Adoption was painfully low: less than half of critical dashboards were even opened on a regular basis. Business Owners admitted it was easier to ping someone on Teams than to search. Data Analysts were losing 30% of their time explaining where to look or how to read.
The goal became crystal clear: scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
ACT 2
The team & my role
A bridge between different worlds
I wasn’t part of a design team. In fact, I was the only designer inside Skynet, the Data & Insights group at IAG. Around me: Insight Managers with deep domain knowledge, Business Owners struggling with adoption, and Data Analysts overloaded with requests.
My role was to bridge these worlds — using governance, research, and design to translate complexity into a framework that could scale across the group.
ACT 3
Research: listening first
I started by listening.
In discovery sessions with each domain, patterns began to emerge:
Insight Managers: every team defined KPIs differently.
Business Owners: impossible to compare dashboards across OpCos.
Data Analysts: “We spend hours reformatting and re-explaining the same metrics.”
Governance workshops confirmed it: without a shared design language and clearer access, adoption would never grow. The problem wasn’t the lack of data. It was the lack of structure around it.
ACT 4
Phase 1: Standardization - Data Design System
The first step was to create that shared language. I designed a Power BI Design System, built in Figma, aligned with IAG’s brand guidelines.
The impact was immediate: in Finance and Operations, dashboard adoption grew by 35% in just three months. A Business Owner summed it up perfectly: “We finally speak the same visual language.”
ACT 5
Phase 2:
Centralization-Analytics Hub
Once dashboards spoke the same language, people needed a single place to find them.
That’s how the Data Marketplace came to life: a hub where datasets, reports, news, and tools all lived together.
In usability tests, the difference was clear. Stakeholders were 40% faster at finding what they needed. As one Data Analyst said: “Before, we’d ask on Teams where a dataset was. Now we know exactly where to start.”
ACT 6
Phase 3: Scaling with AI
With a common design language and a centralized entry point, the next step was scale.
I prototyped SkynetGPT, a chatbot embedded in the portal. Stakeholders could now ask questions in natural language, generate narratives, and receive dynamic visualizations in seconds.
During demos, one Business Owner captured the potential: “If I can just ask and get a chart ready to share, adoption skyrockets.”
This was the bridge into the future: from searching for dashboards to simply conversing with data.
ACT 7
Impact & Learnings
Scaling the data strategy at IAG wasn’t about building more dashboards. It was about designing governance and experiences that turned data into something people could actually adopt — and that the business could rely on.
The transformation unfolded in phases:
From fragmentation → to consistency with the Design System.
From dispersion → to centralization with the Marketplace.
From dependence → to autonomy with SkynetGPT.
The numbers told the story:
+35% adoption in Finance & Ops dashboards.
40% faster access to datasets and reports.
Stronger confidence in critical KPIs like operational punctuality and financial metrics.
🚧 This site is a work in progress — New case studies and stories are coming soon. 🚀
Scaling Data Strategy
From fragmented dashboards to a unified data experience
At IAG, data is more than dashboards — it drives flight punctuality, financial planning, and the decisions that move millions of passengers every day.
My role as a Data Product Designer was to bridge the gap: turning fragmented reports into a unified experience and scaling a strategy across airlines, teams, and business needs.
↘︎ Scroll to follow the story, or choose an Act to explore in depth.
ACT 1
The challenge & goals
Scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
When I joined IAG, the data landscape looked more like a patchwork than a system. Each domain —Finance, Operations, Procurement, Fleet…— was producing dashboards on its own terms. Different colors, layouts, and rules. No common language.
Adoption was painfully low: less than half of critical dashboards were even opened on a regular basis. Business Owners admitted it was easier to ping someone on Teams than to search. Data Analysts were losing 30% of their time explaining where to look or how to read.
The goal became crystal clear: scale the data strategy by creating a unified, consistent, and trusted experience that people actually wanted to use.
ACT 2
The team & my role
A bridge between different worlds
I wasn’t part of a design team. In fact, I was the only designer inside Skynet, the Data & Insights group at IAG. Around me: Insight Managers with deep domain knowledge, Business Owners struggling with adoption, and Data Analysts overloaded with requests.
My role was to bridge these worlds — using governance, research, and design to translate complexity into a framework that could scale across the group.
ACT 3
Research: listening first
I started by listening.
In discovery sessions with each domain, patterns began to emerge:
Insight Managers: every team defined KPIs differently.
Business Owners: impossible to compare dashboards across OpCos.
Data Analysts: “We spend hours reformatting and re-explaining the same metrics.”
Governance workshops confirmed it: without a shared design language and clearer access, adoption would never grow. The problem wasn’t the lack of data. It was the lack of structure around it.
ACT 4
Phase 1: Standardization - Data Design System
The first step was to create that shared language. I designed a Power BI Design System, built in Figma, aligned with IAG’s brand guidelines.
The impact was immediate: in Finance and Operations, dashboard adoption grew by 35% in just three months. A Business Owner summed it up perfectly: “We finally speak the same visual language.”
ACT 5
Phase 2:
Centralization-Analytics Hub
Once dashboards spoke the same language, people needed a single place to find them.
That’s how the Data Marketplace came to life: a hub where datasets, reports, news, and tools all lived together.
In usability tests, the difference was clear. Stakeholders were 40% faster at finding what they needed. As one Data Analyst said: “Before, we’d ask on Teams where a dataset was. Now we know exactly where to start.”
ACT 6
Phase 3: Scaling with AI
With a common design language and a centralized entry point, the next step was scale.
I prototyped SkynetGPT, a chatbot embedded in the portal. Stakeholders could now ask questions in natural language, generate narratives, and receive dynamic visualizations in seconds.
During demos, one Business Owner captured the potential: “If I can just ask and get a chart ready to share, adoption skyrockets.”
This was the bridge into the future: from searching for dashboards to simply conversing with data.
ACT 7
Impact & Learnings
Scaling the data strategy at IAG wasn’t about building more dashboards. It was about designing governance and experiences that turned data into something people could actually adopt — and that the business could rely on.
The transformation unfolded in phases:
From fragmentation → to consistency with the Design System.
From dispersion → to centralization with the Marketplace.
From dependence → to autonomy with SkynetGPT.
The numbers told the story:
+35% adoption in Finance & Ops dashboards.
40% faster access to datasets and reports.
Stronger confidence in critical KPIs like operational punctuality and financial metrics.