Case Studies

Problem → solution → measured impact

Each engagement starts with a business and user problem, defines a product design response, and closes with validated metrics — the format I use when presenting to PM, engineering, and leadership stakeholders.

AI-Powered Enterprise Dashboard

Dell Technologies · Principal Product Designer · IT Operations SaaS
The Problem

Business pressure

  • Support tickets for the IT ops dashboard grew ~15% quarter-over-quarter on a 2M-user platform.
  • Only ~34% of shipped features reached meaningful adoption.
  • Leadership needed AI differentiation without risk to production infrastructure.

User pain

  • Incident triage required 12+ clicks; ~40% of session time spent navigating between modules.
  • AI suggestions were generic and ignored — no confidence score or alert-level context.

Constraints

  • Phased rollout only — no full rewrite or downtime window.
The Solution

Product strategy

  • Prioritized top 5 workflows using support-ticket and contextual inquiry data.
  • Phased: triage redesign → inline AI → role-based personalization.

Design decisions

  • Workflow-first information architecture with progressive disclosure.
  • Contextual AI at the triage decision point with confidence scores and expandable rationale.
  • 12 new patterns contributed to the enterprise design system.

Validation

  • 16 usability sessions; A/B test with 2,400 users over 6 weeks.
Impact
30%faster task completion
40%fewer support tickets
25%higher feature adoption
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Enterprise Design System Transformation

Dell Technologies · Design System Lead · Platform initiative
The Problem

Business pressure

  • 15 apps with 120+ UI inconsistencies; ~30% of frontend capacity spent rebuilding the same components.
  • Accessibility remediation treated as a post-launch phase on every release.

User pain

  • Users re-learned navigation and patterns every time they switched between applications.

Constraints

  • 8 teams on different frameworks; legacy apps could not stop feature delivery for a big-bang migration.
The Solution

Product strategy

  • Business case framed as duplicated eng cost and slower GTM — not "design consistency" alone.
  • Pilot with 3 teams, measure velocity, then scale to 8.

Design decisions

  • Token architecture from Figma to production; 50 WCAG 2.1 AA components.
  • Governance model with contribution guidelines and design review cadence.
  • Incremental migration guides — highest-frequency patterns first.

Validation

  • Adoption and time-to-ship tracked per team; quarterly ROI reporting to leadership.
Impact
40%less design-to-dev effort
60%faster delivery (adopting teams)
90%WCAG compliance in system
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AI Copilot for Enterprise Workflows

Dell Technologies · Principal Product Designer · AI UX
The Problem

Business pressure

  • AI troubleshooting layer shipped but adoption stayed under 10%; support costs still up ~20% YoY.

User pain

  • Admins would not auto-apply AI fixes on production systems without understanding why.
  • No audit trail for AI-assisted actions — blocked trust and compliance review.

Constraints

  • Redesign had to work with existing AI model outputs and eng timelines.
The Solution

Product strategy

  • AI augments human judgment; success metric shifted to recommendation acceptance rate.
  • Start with diagnostic suggestions before high-risk remediation actions.

Design decisions

  • Human-in-the-loop: suggest → explain → preview → confirm → execute.
  • Inline contextual panels with confidence scores — beat chat UI in usability testing.
  • Full audit logging and 8 new AI patterns added to the design system.

Validation

  • 20 admin usability sessions; phased rollout behind feature flags.
Impact
45%reduction in task effort
35%workflow efficiency gain
30%faster issue resolution
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Enterprise Data Platform Unification

Dell Technologies · Principal Product Designer · Data Platform
The Problem

Business pressure

  • 7 disconnected data tools created $1.2M/year in overlapping licenses and swivel-chair workflows.
  • 68% of data requests took 24+ hours; analysts stitched CSVs from 3+ systems in Excel.
  • 12% of executive dashboards showed conflicting KPIs due to divergent source definitions.

User pain

  • 73% of analyst time was spent locating and exporting data — not analyzing it.
  • Executives didn't trust self-serve numbers because lineage and freshness were invisible.

Constraints

  • Each tool had embedded business logic; migration had to preserve historical data fidelity and comply with SOC 2 Type II.
The Solution

Product strategy

  • Unified query layer with role-based access; phased migration by department to de-risk cutover.
  • Single-pane search, federated query builder, saved views with sharing, and lineage visualization.

Design decisions

  • Search-first interface matched consumer mental models; minimal training required.
  • Lineage visualization as expandable trace: source system → transformation → last refresh.
  • Role-based templates covered 80% of routine requests without writing SQL.

Validation

  • 22 contextual inquiry sessions; 6-week pilot with 180 analysts; error-rate monitoring post-launch.
Impact
50%faster data retrieval
38%fewer integration errors
42%higher daily active use
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IT Service Portal Redesign

Dell Technologies · Principal Product Designer · Employee Experience
The Problem

Business pressure

  • 65% of IT tickets were password resets, software access, or FAQ-level questions — burning $2.8M/year in agent time.
  • Average resolution time of 4.2 days; 30% of tickets reopening due to incomplete initial info.

User pain

  • Portal search returned irrelevant results 73% of the time — pushing users straight to ticket submission.
  • The 18-field request form had no guidance; 30% of reopened tickets lacked required info.

Constraints

  • Existing ServiceNow backend could not be replaced; redesign worked within current workflow engine.
The Solution

Product strategy

  • Shift from "submit a ticket" to "find and fix yourself" — intelligent search, guided workflows, predictive routing.
  • NLP semantic search across knowledge base; conversational request wizard; proactive status notifications.

Design decisions

  • Conversational request wizard replaced 18-field form with 4 smart questions that auto-categorize.
  • Hybrid search-and-guide approach served both explorers (search) and novices (guided workflows).
  • Proactive email/Slack updates eliminated 70% of status-check portal visits.

Validation

  • 18 usability sessions; A/B on search relevance with 3,200 employees over 4 weeks; 4-week pilot with HR and Sales.
Impact
55%ticket deflection via self-service
48%faster average resolution
34%higher employee CSAT
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Cloud Migration Portal

Dell Technologies · Principal Product Designer · Cloud Migration
The Problem

Business pressure

  • Cloud migration service underutilized — only 22% of eligible customers adopted; 70% abandoned mid-migration.
  • Average migration took 4–6 months with 15+ manual steps; support team overwhelmed with migration-specific tickets.

User pain

  • IT teams struggled with inventory assessment, compatibility checks, and cost estimation.
  • Real-time cost estimates required manual spreadsheets and took days to produce.

Constraints

  • Had to work within existing Dell cloud infrastructure; migration involved third-party tools and partner integrations.
The Solution

Product strategy

  • Self-service portal with guided workflows: inventory → assessment → planning → execution → verification.
  • Real-time cost estimator, automated compatibility scoring, and step-by-step execution tracking.

Design decisions

  • Guided migration wizard with progress tracking and clear next actions.
  • Interactive cost calculator that updates as users select options and configure workloads.
  • Automated compatibility assessment with visual risk indicators and remediation suggestions.

Validation

  • 18 contextual sessions with IT managers; 3-month beta with 45 enterprise customers; A/B test on cost estimator accuracy.
Impact
60%faster migration time
45%higher adoption
38%fewer support tickets
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Want to walk through any of these in detail?

Open to Principal, Staff, Lead, and Design Manager conversations at enterprise SaaS and AI-first companies.

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