The work was not just to ship redesigned surfaces. It was to give dozens of teams a shared system for how customer experience transformation would actually get delivered.
Context
Wayfair was in the middle of a large customer-experience transformation spanning web and native app experiences across five brands and multiple markets. The program involved upper, mid, and lower funnel work, deep platform dependencies, and a very large cross-functional footprint.
I was recruited into a new portfolio-level CX program role to help make the transformation more coherent, more measurable, and more executable across teams.
The challenge was as much operational as it was experiential. The work needed a system for planning, prioritization, dependency management, and outcome visibility, not just more project tracking.
Problem
- Replatforming work was broad, complex, and distributed across many teams.
- Customer-journey migration had started from a low baseline and needed visible adoption progress.
- OKRs and reporting were inconsistent, which made priority and progress harder to interpret.
- Dependencies and milestones were difficult to understand across such a large org footprint.
- Leadership needed faster, more reliable visibility into how delivery mapped to business outcomes.
Constraints
- The effort spanned five consumer brands, multiple markets, and different funnel stages.
- Teams worked with different cadences, systems, and delivery realities.
- Reporting had to work for both executive audiences and day-to-day program teams.
- The replatforming effort was live, phased, and dependent on many parallel workstreams.
Research Findings
The underlying issue was not simply lack of effort. It was lack of a shared operating model for how experience transformation should be planned, measured, and communicated.
A few patterns showed up repeatedly:
- Teams could not always see how daily work connected to portfolio goals.
- Reporting was too manual and lagged behind actual delivery conditions.
- Dependencies, milestones, and risks were often visible locally but not systemically.
- Leadership needed a clearer signal on what was truly moving and what was blocked.
To address that, I worked across teams to map journey scope, delivery structure, planning cycles, and reporting needs into a single operating model.
Key Decisions
1. Treat delivery visibility as a product problem
Instead of accepting fragmented reporting, I designed a clearer experience for how progress, confidence, risk, and outcomes should be surfaced across the portfolio.
2. Connect OKRs to real delivery signals
Teams needed more than high-level goal language. They needed a system that linked roadmap work, Jira data, milestones, and outcomes in one place.
3. Make phased rollout visible
The transformation was intentionally sequenced across upper, mid, and lower funnel work. The planning model needed to reflect those phases in a way that teams and leaders could actually use.
4. Reduce reporting friction with AI-assisted synthesis
Manual status creation was slow and inconsistent. I designed a GenAI-assisted reporting workflow to translate delivery signals into more useful planning and reporting summaries.
System / Workflow / Experience Design
The work spanned three connected systems:
Customer-journey transformation model
I helped define how experience scope, rollout phases, and team dependencies would be organized so the replatforming effort could scale coherently across brands and touchpoints.
OKR and reporting system
I built and normalized a portfolio OKR model that made customer-experience goals easier to plan against, report on, and prioritize.
Dependency and milestone visibility
I created systems for tracking inter-team dependencies, key milestones, and delivery health across the broader program footprint.
Validation / Rollout
The operating model and reporting workflows were refined through live use rather than treated as static governance documentation.
Rollout included:
- progressive replatforming across customer journeys
- portfolio planning cycles tied to OKRs and milestones
- executive reporting and steering materials
- pilot use of GenAI-assisted reporting before broader normalization
- continuous adjustment based on team and leadership feedback
Outcomes
What I Learned
- Transformation needs an operating system. Large experience programs fail when planning, reporting, and dependencies stay fragmented.
- Visibility changes behavior. When teams can see how work connects to outcomes, prioritization gets sharper.
- AI is most useful when it removes reporting friction, not context. The summaries worked because they were grounded in real program structure.
- Journey transformation is both product work and organizational work. One without the other is not enough at this scale.
