6 years leading information architecture and research for myLiberty — Liberty Mutual's enterprise intranet, used by 45,000+ employees across 8 global markets. The core problem: a decade of organic content sprawl had made the site nearly unusable. The IA redesign gave it a structure employees could navigate without relying on search.
Context
myLiberty had grown organically over 10 years: 1,000+ pages, 400+ content editors, no shared structure, no placement rules, no naming standards. Search had become the primary navigation mechanism, and barely worked.
The trigger was a Drupal platform migration. 400 editors couldn't rebuild their content until a structural foundation existed: the IA was the critical path blocker for the entire migration.
myLiberty · enterprise intranet platform · post-redesign homepage
Research approach
Triangulated: IA-specific methods to surface mental models and validate structure, combined with existing behavioral data to diagnose where the system was already failing.
Information architecture
Four top-level (L1) categories aligned with employee task flows, validated through card sort data, each with terminology standards and placement rules that let 400 editors rebuild consistently without ongoing UX intervention.
L1 navigation · before (dark) → after (gold) · ICs and managers saw different nav bars; both received the same four-category structure
Content design
The IA defined where content lived. The content page design defined what it contained. We designed all content types for the Drupal platform, with one structural decision at the center: manager-only content would live on the same page as all-employee content, not in a separate section of the site.
A topic like "Benefits" existed in two places:
Two pages to find, two pages to maintain. Employees who became managers had to learn a parallel section of the site. Content editors updated the same topic in two places, with no structural relationship enforcing consistency between them.
One Benefits page, with role-aware content inline:
One page to find, one page to maintain. Managers see the full picture without navigating elsewhere. Content editors work within a single site structure.
Navigation design
The old menu surfaced a curated subset of subcategories: anything not featured was effectively invisible. The challenge: make the entire structure navigable from the menu without overwhelming the user.
Before · editor-curated L2 columns · subset of L3 links shown · anything not featured was invisible
Pattern 1 · L2 with 5+ subsections · compact L3 link list
Pattern 2 · L2 with ≤4 subsections · each L3 gets a column with L4 links
Request a Service · Technology Assistance · tool names paired with plain-language task descriptions
Impact
These results are attributable to the IA redesign and navigation work specifically, not the six years overall.
Full scope of work
The IA and mega menu were the structurally significant work, but not isolated projects. Every content problem, feature addition, accessibility initiative, and market expansion came back to the same person who built the foundation.
What this demonstrates
The IA and mega menu are the clearest examples, but the same capabilities show up across the full scope above. The question underneath them is the one I care about most now: as AI enters the systems people rely on, where does the human-system boundary break down, and what structural intervention makes it reliable at scale?
| Capability | How it showed up at Liberty Mutual |
|---|---|
| Information architecture as systems design | The site structure wasn't a navigation redesign. It was a decision framework. Terminology standards and placement rules let 400 editors rebuild consistently without constant intervention. One structural fix eliminated an entire category of recurring support costs. |
| End-to-end system context | For six years, I was the primary UX and IA practitioner on myLiberty. New features, market expansions, and content problems consistently ran through someone who understood the system's history, failure modes, and structural constraints. |
| Mixed-methods research to diagnose, not just validate | Card sorting revealed mental models; tree testing validated the proposed structure against those models; search logs and support tickets surfaced where the existing system was already failing. |
| Designing for scale and maintenance | The IA had to work for 35K US employees at launch and scale to 45K across 8 global markets. The placement rules and terminology standards were designed to be maintainable by 400 content editors independently, with no ongoing UX oversight required. |
| Translating ground-level friction into platform decisions | The "Request a Service" fix was structural, not cosmetic: pairing ambiguous tool names with plain-language task descriptions changed how the entire section was organized, not just the labels. It came directly from observing employees fail to navigate to tools they needed. |