Maestro (EY) — Financial Dashboards & Product Design
DITU — Reimagining TV App Experience for CaracolTV (Reduced friction in content discovery for streaming viewers)
services
Sr Product Designer
client
Caracol TV
year
9 months (2025)
category
OTT, All platforms TV app
Agency
Monks.com
My Role:
I was embedded as the Senior UX Designer within the Globant team contracted by Ernst & Young — responsible for leading the design of Maestro, an internal engagement management dashboard built to help EY’s decision-makers navigate complex financial datasets and project performance data without drowning in it.
My ownership spanned the full design arc: facilitating stakeholder discovery workshops, mapping raw data structures to meaningful visual hierarchies, designing high-fidelity dashboard interfaces, and leading handoff to analytics engineers — ensuring that what was designed was actually what got built.
This was not a UI beautification project. It was a strategic design challenge: make one of the world’s most data-rich professional services organizations faster and more confident at the moment of decision.
Challenge:
EY runs thousands of client engagements simultaneously — each one generating financial performance data, milestone tracking, resource allocation figures, and risk indicators that engagement managers need to read, interpret, and act on, often under aggressive deadlines.
The data existed. The problem was what it demanded of the people responsible for it.
Engagement managers were spending significant time assembling reports manually — pulling figures from disconnected sources, formatting data into presentations, and making decisions based on information that was already hours or days old by the time it reached them. The cost wasn’t just time. It was decision quality.
The ask: turn complex financial datasets into actionable dashboards that give decision-makers the right information, at the right level of detail, at the right moment — so they can lead engagements with clarity instead of chasing data.
Context:
EY is one of the Big Four professional services firms — operating at a scale where the margin between a good decision and a slow one is measured in client outcomes, revenue, and organizational risk.
Maestro was conceived as an internal product to modernize how EY engagement managers run their portfolios. Rather than relying on manually assembled reporting cycles, Maestro would surface live engagement health — financials, milestones, resource utilization, and risk flags — in a single, role-appropriate interface.
The stakes were high in both directions. Build it too complex and engagement managers would revert to their spreadsheets. Build it too simplified and it wouldn’t reflect the real complexity of what they were managing. The design had to thread that needle precisely.
Compounding the challenge: EY’s internal audience is sophisticated, time-poor, and professionally unforgiving. These are people who scrutinize data for a living. The dashboard had to earn their trust — visually, structurally, and analytically — before they would rely on it for anything that mattered.
Platform:
Web application (desktop-first).
Maestro lived in the browser, designed for the context in which EY engagement managers actually work: at a desk, in a structured analytical workflow, often with multiple information sources open simultaneously.
Desktop-first was not a default — it was a deliberate product decision. The use cases that Maestro served — financial drilldowns, milestone reviews, resource allocation comparisons — require screen real estate, data density, and interaction depth that a mobile-first approach would have forced into compromises no senior analyst would accept.
The platform was also integrated with Tableau for advanced data visualization layers, with Figma as the design and specification environment, and handoff routed directly to the analytics engineering team responsible for building the data pipeline that powered the dashboard’s live data feeds.
What I led:
Stakeholder Discovery Workshops Facilitated structured workshops with EY engagement managers, analytics leads, and product sponsors to surface what decisions the dashboard needed to support, what data was available, what was trusted versus questioned, and where the current reporting process broke down. This wasn’t requirements gathering — it was organizational diagnosis.
Data Mapping & Visualization Architecture Worked directly with analytics engineers to map raw financial and engagement datasets to visual representations — determining what chart type, what aggregation level, and what interaction model best served each data relationship. This required both design judgment and enough analytical fluency to have credible conversations with engineers about data structure.
Prioritization Matrix Led a structured prioritization exercise with stakeholders to rank dashboard features against decision impact and implementation complexity — ensuring the product launched with the highest-value views first, rather than trying to visualize everything at once.
High-Fidelity Dashboard Design Designed the full suite of Maestro dashboard interfaces: engagement overview, financial performance views, milestone tracking, resource utilization panels, and risk flagging — each built to information design standards where hierarchy, grouping, and visual weight all carry analytical meaning.
Drilldown Interaction Design Designed the interaction model for dashboard drilldowns — how users navigate from fleet-level engagement overview to individual project financials without losing context, and how filters, date ranges, and segment selectors behave within the analytical workflow.
KPI Framework Design Proposed and documented a KPI tracking framework for the product itself — defining success metrics including decision speed, error rate reduction, and report assembly time saved — giving the product team a measurement model for evaluating Maestro’s business impact post-launch.
Engineering Handoff Led the handoff process to analytics engineers — delivering annotated dashboard specifications, data mapping documentation, interaction specs for dynamic components, and prototype interactions for drilldown behaviors. Remained embedded through the build phase to review implementations and protect design fidelity.
Outcome / Impact:
Maestro transformed the engagement management reporting cycle from a manual assembly process into a live analytical environment — giving EY engagement managers direct access to the financial and performance data they needed to make decisions, without the intermediary cost of building the view first.
Decision speed improved qualitatively — engagement managers reported faster access to the information that previously required manual report assembly, reducing the lag between data availability and decision readiness.
The drilldown interaction model preserved analytical context through navigation — eliminating the disorientation of moving between disconnected reports and enabling a continuous analytical workflow from portfolio level to individual project financials.
The KPI tracking framework designed for Maestro — measuring decision time, error rate, and report assembly time saved — gave the product team a structured model for quantifying business impact in post-launch evaluation, connecting the design investment directly to organizational outcomes.
Design system components built for Maestro — data visualization patterns, filter interaction models, and dashboard layout specifications — were documented for reuse across future EY digital product initiatives, reducing design and development overhead for subsequent data-driven tools.
The Investigation
The discovery phase revealed something that reframed the entire product strategy.
The engagement managers didn’t distrust their data. They distrusted their ability to find it in time.
The bottleneck wasn’t analytical capability — EY employs some of the most analytically rigorous professionals in the world. The bottleneck was the assembly process: the hours spent pulling figures from multiple systems, reconciling format differences, and building the view that would allow a decision to be made.
By the time that view was assembled, the decision window had often narrowed. Engagement managers were making calls on data that was correct at the moment of assembly but potentially stale at the moment of use.
This finding shifted the design priority from visualization sophistication to data immediacy. The most important design decision wasn’t which chart type to use for financial performance — it was ensuring that every figure on the dashboard was timestamped, source-attributed, and clearly current. Trust in the interface required trust in the data behind it.
A second finding shaped the drilldown architecture: engagement managers navigated between altitude levels constantly — moving from portfolio overview to single-project financials and back, multiple times per decision session. The existing reporting tools treated these as separate reports. Maestro needed to treat them as a single continuous navigation — preserving context through every level transition so the cognitive thread of the analysis was never broken.
Both findings are structural to the product. Neither would have surfaced without the investigation phase.
Takeaways
Data visualization is an information design problem, not a charting problem. The instinct in dashboard design is to reach for the chart library and start plotting. The right instinct is to start with the decision — what does this person need to know, what level of precision do they need it at, and what visual encoding communicates that most immediately. Chart type is the last decision, not the first.
Trust in the interface requires trust in the data. The most sophisticated dashboard fails if the user doesn’t trust what it’s showing them. Timestamping, source attribution, and clear data freshness indicators weren’t nice-to-haves on Maestro — they were the foundation on which every other design decision rested. Users who trust their data make faster, more confident decisions.
Drilldown is a navigation problem, not a feature. Most dashboard products treat drilldown as a feature — click here to see more. Maestro treated it as navigation — a continuous journey through levels of analytical altitude that needed to preserve context at every transition. That distinction changed every interaction design decision in the product.
Stakeholder workshops are a design tool, not a kickoff ritual. The workshops on Maestro weren’t status meetings or requirements sessions. They were structured discovery instruments — designed to surface the decisions the product needed to support, the organizational tensions around data ownership, and the trust dynamics between data providers and data consumers. That investment in facilitation quality paid back in every design decision that followed.
Designing for experts demands more rigor, not less. The temptation when designing for a sophisticated internal audience is to assume they’ll figure it out. The reality is the opposite — expert users have zero tolerance for interfaces that make them work harder than necessary. The standard for clarity, hierarchy, and interaction precision was higher on Maestro than on any consumer product, because the users knew immediately when the design was letting them down.
Aggressive deadlines are a design constraint, not just a project reality. EY’s operational pace meant the product had to be scoped precisely — not everything that could be visualized should be visualized in v1. The prioritization matrix wasn’t just a planning tool. It was a design discipline that protected the product from becoming too complex to be useful under the time pressures it was built to relieve.
Design process
More Details
What decisions does this product need to support?
The first question wasn’t “what should the dashboard show?” It was “what does an engagement manager need to decide, and when?” Stakeholder workshops were structured around decision scenarios — walking through real engagement situations to map what information was needed at each decision point and what friction the current process created getting there.
This phase also surfaced a critical organizational dynamic: different stakeholder levels had different relationships with the same data. An engagement manager and a partner-level sponsor looking at the same project financials were asking fundamentally different questions. The dashboard architecture had to accommodate both perspectives without building two separate products.
Structure before screens
Discovery output was synthesized into a prioritization matrix — ranking every potential dashboard view by decision impact and data availability. High-impact, high-availability views became the launch scope. Complex views dependent on data pipeline work were sequenced for later phases.
Information architecture was defined before any visual design began: what are the primary navigation surfaces, how does the hierarchy of engagement → project → task → financial line item work in the interface, and where do users enter the drilldown versus return to overview.
From data map to high-fidelity
With architecture defined and data mapped, design moved through structured fidelity layers. Low-fidelity wireframes validated structural decisions with stakeholders before any visual investment was made. Mid-fidelity flows confirmed the drilldown interaction model with engineering before it was built into the prototype. High-fidelity dashboards were produced to the standard that EY’s internal audience demanded — information design where every visual decision had analytical justification.
Tableau was used for advanced visualization components requiring live data connection; Figma governed the interface architecture, component specifications, and interaction documentation across the full product.
Handoff that engineers can actually build
from Annotated dashboard specifications, data mapping documentation, and interaction prototypes for drilldown behaviors were delivered to the analytics engineering team through Figma. Design remained embedded through implementation — reviewing builds against specifications and catching deviations before they became permanent.
