Scaling Data Strategy at IAG
From fragmented dashboards to a unified data experience
At IAG, data is more than dashboards and KPIs. It’s the fuel behind flight punctuality, financial planning, and the decisions that keep millions of passengers moving every day.
But data only creates value when people trust it, understand it, and adopt it. My role as a Data Product Designer was to bridge that gap — to turn fragmented reports into a unified experience, and to design a strategy that scaled across airlines, teams, and business needs.
This is the story of how we scaled data strategy at IAG — one phase at a time.
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 (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.