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2024
Designing a Scalable Monitoring System for 10,000+ Employees
Designing a Scalable Monitoring System for 10,000+ Employees
MY ROLE
Lead UX Design
Senior Product Designer
Senior Product Designer
TIMELINE
6 Months
2 Months
2 Months
RESPONSIBILITIES
UX Research
UX Research, Stakeholder Presentations, Prototyping, User Testing, UI Design, Dataviz Design
Stakeholder Presentations
Prototyping
User Testing
UI Design
Dataviz Design
A talent acquisition platform seeking a compelling UX approach and immersive experience.
BMW STEP is amongst the most extensive technician training schemes across North America. They are recognized for their practical methodology and thorough enhancement of technical skills. Yet, their official website seemed antiquated and overloaded with content, lacking a narrative to support its value proposition. As a result, the site faced increased bounce rates, diminished traffic, and reduced page duration.
Aflac’s marketing organization lacked visibility into how marketing materials were being used across a distributed workforce of more than 10,000 employees.
Teams relied on manual reports and local spreadsheets, leading to inconsistent data, delayed decisions, and fragmented operational visibility.
Leadership needed a centralized monitoring system that could provide clarity at scale without increasing workload or reducing regional flexibility.
Aflac’s marketing organization lacked visibility into how marketing materials were being used across a distributed workforce of more than 10,000 employees.
Teams relied on manual reports and local spreadsheets, leading to inconsistent data, delayed decisions, and fragmented operational visibility.
Leadership needed a centralized monitoring system that could provide clarity at scale without increasing workload or reducing regional flexibility.
MY ROLE
Senior Product Designer
RESPONSIBILITIES
UI Design
Stakeholder Presentations
Prototyping
User Testing
Dataviz Design
TEAM
I worked on this project
with the help of a mid-level
Product Designer
Aflac’s marketing organization lacked visibility into how marketing materials were being used across a distributed workforce of more than 10,000 employees.
Teams relied on manual reports and local spreadsheets, leading to inconsistent data, delayed decisions, and fragmented operational visibility.
Leadership needed a centralized monitoring system that could provide clarity at scale without increasing workload or reducing regional flexibility.
Aflac’s marketing organization lacked visibility into how marketing materials were being used across a distributed workforce of more than 10,000 employees.
Teams relied on manual reports and local spreadsheets, leading to inconsistent data, delayed decisions, and fragmented operational visibility.
Leadership needed a centralized monitoring system that could provide clarity at scale without increasing workload or reducing regional flexibility.
Main Goals
Main Goals
Main Goals
Reduce manual reporting effort across regions
Increase adoption of standardized marketing materials
Enable real-time visibility for leadership decisions
Maintain system consistency as asset volume grows
Initial Challenge
Initial Challenge
Since the former platform were underused, the client was confused of what kind of solution they would need to track downloads on the new system.
Since the former platform were underused, the client was confused of what kind of solution they would need to track downloads on the new system.
Research
Research
We discovered that regional teams were creating parallel tracking spreadsheets, revealing a lack of system trust and structural clarity rather than a lack of tools.
We discovered that regional teams were creating parallel tracking spreadsheets, revealing a lack of system trust and structural clarity rather than a lack of tools.
UX Strategy
UX Strategy
Progressive disclosure to avoid cognitive overload
Configurable modules instead of static dashboards
Role-based visibility to preserve structural clarity
Layered information architecture to support scale
Instead of extending the single-config model, we re-architected the system to support:
Multiple configurations per VIN
Scoped rule-based application
Permission-based overrides
Visualized impact before deployment
This shifted the platform from static assignment to dynamic logic orchestration. The design challenge became one of containment — shaping complexity instead of hiding it.
IMPACT
IMPACT
IMPACT
66x
increase in monitoring of material usage.
66x
increase in monitoring of material usage.
66x
increase in monitoring of material usage.
66x
increase in monitoring of material usage.
Tracking time
Reduced from days to minutes across distributed teams
Tracking time
Reduced from days to minutes across distributed teams
Tracking time
Reduced from days to minutes across distributed teams
Tracking time
Reduced from days to minutes across distributed teams
6+
New relevant metrics added to the product
6+
New relevant metrics added to the product
6+
New relevant metrics added to the product
6+
New relevant metrics added to the product
TRADE-OFFS
TRADE-OFFS
TRADE-OFFS
Balancing scalability, clarity, and usability in a growing monitoring ecosystem
Decision
Why
Risk
Mitigation
Modular Dashboard Architecture
High scalability
Higher initial complexity
Enabled long-term expansion without redesign or structural debt
Qualitative Feedback Integration
Nuanced decision-making
Increased data interpretation complexity
Enabled administrators to understand behavioral patterns and intent behind quantitative metrics rather than relying on raw numbers alone
Configurable Metrics
Flexibility
Higher QA and validation effort
Allowed contextual insights without compromising system integrity
Balancing scalability, clarity, and usability in a growing monitoring ecosystem
Decision
Why
Risk
Mitigation
Modular Dashboard Architecture
High scalability
Higher initial complexity
Enabled long-term expansion without redesign or structural debt
Qualitative Feedback Integration
Nuanced decision-making
Increased data interpretation complexity
Enabled administrators to understand behavioral patterns and intent behind quantitative metrics rather than relying on raw numbers alone
Configurable Metrics
Flexibility
Higher QA and validation effort
Allowed contextual insights without compromising system integrity
Balancing scalability, clarity, and usability in a growing monitoring ecosystem
Decision
Why
Risk
Mitigation
Modular Dashboard Architecture
High scalability
Higher initial complexity
Enabled long-term expansion without redesign or structural debt
Qualitative Feedback Integration
Nuanced decision-making
Increased data interpretation complexity
Enabled administrators to understand behavioral patterns and intent behind quantitative metrics rather than relying on raw numbers alone
Configurable Metrics
Flexibility
Higher QA and validation effort
Allowed contextual insights without compromising system integrity
HIGHLIGHTS
HIGHLIGHTS
HIGHLIGHTS
Creating a Metrics Inventory
First step of the challenge was gathering the necessary metrics to be tracked by the team. Then we categorized those metrics and group them strategically, to align with the dashboard’s information architecture.
Dashboard anatomy
After defining the key metrics, it was crucial to determine an arrangement of the charts, so that it was easy to digest, and one metric was a natural consequence of the other.
Navigation plan
Since 7 new dashboard pages would be added to the platform, I planned the Information Architecture in a way they would make sense and reduce time finding out their logig
Controls and Qualitative Feedback
Users needed to be able to select different time frames, to refine their analysis. It would also be helpful to provide a qualitative breakdown on the data, so users better understand nuanced information.
Creating a Metrics Inventory
First step of the challenge was gathering the necessary metrics to be tracked by the team. Then we categorized those metrics and group them strategically, to align with the dashboard’s information architecture.
Dashboard anatomy
After defining the key metrics, it was crucial to determine an arrangement of the charts, so that it was easy to digest, and one metric was a natural consequence of the other.
Navigation plan
Since 7 new dashboard pages would be added to the platform, I planned the Information Architecture in a way they would make sense and reduce time finding out their logig
Controls and Qualitative Feedback
Users needed to be able to select different time frames, to refine their analysis. It would also be helpful to provide a qualitative breakdown on the data, so users better understand nuanced information.
Creating a Metrics Inventory
First step of the challenge was gathering the necessary metrics to be tracked by the team. Then we categorized those metrics and group them strategically, to align with the dashboard’s information architecture.
Dashboard anatomy
After defining the key metrics, it was crucial to determine an arrangement of the charts, so that it was easy to digest, and one metric was a natural consequence of the other.
Navigation plan
Since 7 new dashboard pages would be added to the platform, I planned the Information Architecture in a way they would make sense and reduce time finding out their logig
Controls and Qualitative Feedback
Users needed to be able to select different time frames, to refine their analysis. It would also be helpful to provide a qualitative breakdown on the data, so users better understand nuanced information.
LEARNINGS
LEARNINGS
LEARNINGS
Structure Enables Scale
Clear system structure reduces friction and allows complexity to grow without overwhelming users or breaking consistency.
Structure Enables Scale
Clear system structure reduces friction and allows complexity to grow without overwhelming users or breaking consistency.
Structure Enables Scale
Clear system structure reduces friction and allows complexity to grow without overwhelming users or breaking consistency.
Structure Enables Scale
Clear system structure reduces friction and allows complexity to grow without overwhelming users or breaking consistency.
Metrics Need Context
Numbers alone create false confidence. Combining quantitative data with qualitative feedback leads to more informed decisions.
Metrics Need Context
Numbers alone create false confidence. Combining quantitative data with qualitative feedback leads to more informed decisions.
Metrics Need Context
Numbers alone create false confidence. Combining quantitative data with qualitative feedback leads to more informed decisions.
Metrics Need Context
Numbers alone create false confidence. Combining quantitative data with qualitative feedback leads to more informed decisions.
Flexibility Requires Boundaries
Allowing local adaptability works best when supported by invisible guardrails that preserve coherence across teams.
Flexibility Requires Boundaries
Allowing local adaptability works best when supported by invisible guardrails that preserve coherence across teams.
Flexibility Requires Boundaries
Allowing local adaptability works best when supported by invisible guardrails that preserve coherence across teams.
Flexibility Requires Boundaries
Allowing local adaptability works best when supported by invisible guardrails that preserve coherence across teams.
Clarity Beats Feature Density
Usability improves when information is layered and intentional, rather than exposing every capability at once.
Clarity Beats Feature Density
Usability improves when information is layered and intentional, rather than exposing every capability at once.
Clarity Beats Feature Density
Usability improves when information is layered and intentional, rather than exposing every capability at once.
Clarity Beats Feature Density
Usability improves when information is layered and intentional, rather than exposing every capability at once.
