Role
Lead UX/UI Designer
Scope
Research, UX strategy, interaction design, UI design, design system
Platform
Enterprise internal process monitoring web application
Team
1 designer, 4 engineers, enterprise client stakeholders
5 fragmented tools
→ 1 unified platform
65%
faster issue resolution
$1.8M
annual operational savings
01
PROBLEM & CHALLENGE
Data quality was managed across more than 200 sources with fragmented, engineering-first tools. Site managers and executives lacked a clear way to understand issues, assign ownership, or act before problems affected operations.
40%
of business decisions delayed due to unreliable data
$2.5M
annual cost from manual data quality checks
14 days
average time to identify and fix an issue
5
disconnected tools required for a full picture
Lack of visibility
A recurring blocker surfaced across roles and locations.
Complex workflows
A recurring blocker surfaced across roles and locations.
Poor collaboration
A recurring blocker surfaced across roles and locations.
Limited executive insight
A recurring blocker surfaced across roles and locations.
02
RESEARCH INSIGHT
Five weeks of mixed-method research across three roles and twelve manufacturing sites grounded the product in real operational needs.
18
user interviews
87
survey responses
8
contextual inquiries
6
competitor platforms reviewed
Key insights
01
Users spent roughly 40% of their time manually checking data across disconnected systems.
02
85% of participants found existing tools too complex to use confidently.
03
The recurring workflow was: identify issue → assign team → track resolution → verify fix.
04
Executives needed trend-level visibility, while stewards needed technical depth.
05
Real-time alerts were essential to prevent issues from cascading unnoticed.
Sarah Chen — Data Steward
“I need to see which data issue is mine, what broke, and what changed since yesterday.” Goals: resolve data issues quickly; maintain rule accuracy; trust alerts. Pain points: noisy dashboards, manual checks, unclear ownership.
Mike Rodriguez — Site Manager
“I don’t need the SQL. I need to know whether production reports can be trusted today.” Goals: understand operational risk; assign issues; prevent delays. Pain points: technical tooling, email chains, weak visibility.
Jennifer Park — VP of Operations
“I need the trend, the business impact, and whether the teams are getting better.” Goals: track quality trends; prioritize investment; report progress. Pain points: no executive view, inconsistent definitions, late escalation.
03
STRATEGIC OPPORTUNITY
Goal 1
Consolidate five fragmented tools into one platform
Goal 2
Make data quality legible to non-technical stakeholders
Goal 3
Shift teams from reactive to proactive detection
Goal 4
Replace email-thread tracking with a shared workflow
04
DESIGN PROCESS
Discover
Interviews, contextual inquiry, competitive scan, stakeholder workshops
Define
Personas, journey maps, problem framing, success metrics
Ideate
Design studio, sketching, Crazy 8s, concept validation
Design
Wireframes, high-fidelity mockups, prototypes, design system
Test
Usability testing and iteration
Measure
Post-launch analytics and satisfaction survey
Key decisions
1
Dashboard and Task Tracker were prioritized first because they addressed the $2.5M manual-cost baseline.
2
Testing showed that one shared dashboard did not suit every role; the solution became role-based views on one data model.
3
Two rounds of usability testing improved the heatmap’s legend and drill-down behavior.
4
Post-launch analytics and surveys measured success against initial research goals.
Sketches
Early wireframes
User flows
Design-system components
05
SOLUTION SYSTEM
Unified Dashboard interface
Unified Dashboard
One view, not five tabs
Problem
Getting a full picture meant switching between five tools.
Decision
Card-based layout, color-coded quality scores, and alerts above the fold.
Benefit
Stewards can understand status and act without leaving the page.
Metric
85% reduction in time spent gathering quality information.
Task Tracker interface
Task Tracker
From email threads to a shared board
Problem
Issue context was trapped in email threads.
Decision
Kanban board with automated tasks created from rule violations.
Benefit
Every issue has one owner and one visible resolution thread.
Metric
92% of tasks resolved within SLA, up from 45%.
Quality Heatmap interface
Quality Heatmap
Trends, readable in one glance
Problem
Executives could not identify which data domains needed attention.
Decision
Hierarchical drill-down, hover details, and temporal slider.
Benefit
A high-level summary with technical depth available one click away.
Metric
60% reduction in incident rate through proactive management.
Pipeline Monitor interface
Pipeline Monitor
Catching failures before the report does
Problem
Pipeline failures were noticed only after downstream effects.
Decision
Node-based flow visualization, color-coded status, and history charts.
Benefit
Teams see breaks the moment they happen.
Metric
15-minute mean time to detection, down from 6 hours.
06
VALIDATION & IMPACT
Issue resolution time
14 days
5 days (65% faster)
Manual quality checks
Baseline
80% reduction
Tools needed for a full picture
5
1
Missed issues from alerting gaps
Baseline
85% decrease
Post-launch satisfaction
—
92% (n=45)
Annual operational savings
—
$1.8M
From feedback to confidence
1
Tested moderated mid-fidelity prototypes with 8 data stewards and 3 site managers.
2
Users did not trust heatmap colors without a clear legend and struggled to find trend data.
3
Added a legend and temporal slider, then retested; time-to-insight was roughly halved.
Before mockup placeholder
After mockup placeholder
07
REFLECTION
What I learned
Progressive disclosure has to be structural, not cosmetic. A larger font does not make a metric executive-friendly if the underlying data model cannot support drill-down.
What I’d test next
I would instrument persona-level product analytics from day one, rather than relying on aggregate satisfaction data.
A trade-off I’d own
Role-based dashboards resolved a core user tension, but I would surface that fork earlier—before high-fidelity design.