Professional/Case Studies/Case Study 01
Professional · Case Study 01
Enterprise UX Operating Model Transformation · Lowe's
A 30-person UX organization was absorbing a structural failure the company kept reading as a design problem. I rebuilt how work entered the system — and turned volatile delivery into a measurable, durable operation.
Organization
Lowe's Companies, Inc.
Fortune 50 Retail
Role
Senior UX Manager
Director-scope authority
Scope
30+ practitioners · 12 reports
40+ stakeholders
Window
2022–2024
Design · Research · Content
The Problem
UX was being pulled in after product decisions were already locked. Requirements arrived incomplete. There was no unified process across designers, content, and research — no sprint schedule, no pointing system, no shared definition of “ready.” Rework was constant and untracked, and Product had lost trust in UX delivery.
Designers were absorbing a structural failure. The organization was reading it as a design-quality problem.
50%
Jira ticket carryover
<50%
Sprint commitment accuracy
35–45%
Mid-sprint requirement changes
Weekly
Stakeholder escalations
Untracked
Rework absorbing capacity
Zero
Unified process across disciplines
The Diagnosis
I audited how UX was actually delivering, not how we assumed we were — Jira reopen and carryover data, clarification meeting tracking, and a map of how work moved from intake to handoff. No RACI. No consistent tracking. Ad hoc alignment with Product on no defined cadence.
The Operating Model
Every intervention targeted the operating model, not individual behavior — and was designed to be maintained without the person who built it.
Defined schedules, agile pointing, and structured touchpoints that make commitments visible and reliable.
A UX Ready gate that validates requirements before design begins. Scope creep stops at entry.
AI-assisted synthesis and a centralized insight repository, fast enough to influence sprint decisions.
Jira telemetry, RACI clarity, and weekly reporting that convert delivery into measurable data.
Prompt frameworks, mandatory human review gates, and cross-discipline guardrails.
The Intervention
I aligned designers, content, and research to a single delivery model and defined who owns what at every stage. Ambiguity inside the team was eliminated before I addressed anything external — you can't ask Product to trust a process you don't have yourself.
An agile pointing system where one point equals one day. Jira UX projects with custom dashboards made delivery measurable for the first time, and the team could finally communicate level of effort and set realistic commitments. Underneath it sat a defined engagement lifecycle.
Intake
Problem definition & success criteria validated
Discovery
Research activation & requirement refinement
Design
Structured iteration within sprint guardrails
Validation
Stakeholder & feasibility alignment
Delivery
Engineering handoff with stable scope
Measurement
Sprint performance tracking
Two structured Product touchpoints per sprint: one to show progress and gather feedback, one for final review and sign-off. Transparency replaced assumption, reinforced by a defined rhythm every discipline operated from.
Mon · D1
Stand-up · Sprint Planning · UX/PM Sync
Wed · D3
Stand-up · Design Review
Fri · D5
Stand-up · Lead Review
Mon · D6
Stand-up · UX/PM Sync
Thu · D9
Stand-up · Backlog Refinement
Fri · D10
Stand-up · Sprint Review
The keystone. Requirements were validated before design started — and if a level of effort couldn't be determined, work didn't begin. That was the signal requirements were missing. Scope creep was stopped at the entry point. All five must be present at intake before work is committed.
The Result
Mid-sprint requirement changes
35–45%
<15%
Rework cycles
baseline
−50–65%
Sprint commitment accuracy
<50%
~80%
Escalation frequency
Weekly
Occasional
Governed AI adoption across disciplines
—
<60 days
Source: Jira sprint analytics & ticket tracking; sprint retro analysis · Lowe's, 2022–2024
Influence wasn't a single moment — it accumulated across sprints. As the UX Ready gate surfaced the real cost of incomplete requirements through carryover and escalation data, I took that evidence to product leadership. The argument was never about design quality. It was about delivery risk.
Governance
The gate produced hard data
Evidence
Carryover & escalation rates
Credibility
Risk framed in Product's terms
The Seat
UX invited before features locked
Leadership in Action
When pushback came, I returned to the Jira audit, the carryover rates, and the escalation logs. The data removed opinion from the conversation.
Product initially pushed back on UX Ready. I held the standard. Within two sprints, incomplete requirements dropped sharply and the gate became expected.
I didn't ask Product to trust UX. I gave them visibility into the work and let the results speak.
Leadership also meant building capability inside the system. An associate designer carried real fear about presenting to stakeholders. Rather than waiting for readiness, I created it — an internal presentation assignment, pairing with a content designer, and five coaching sessions. She presented confidently and engaged stakeholders directly from that point forward.
The frameworks outlasted me. Intake discipline, sprint governance, and the AI operating model were still running after I left. I don't build systems that need me in the room.