PRODUCT DESIGN OPS at ResMed Saas

About ResMed

ResMed is a global health technology company known for its sleep and respiratory devices, as well as its expanding digital health solutions. As part of this strategy, ResMed has a division focused on EHR and software products for post-acute care: MatrixCare provides EHR solutions for home health, hospice, and long-term care, Brightree supports DME, pharmacy, and home infusion operations and billing, and Citus Health enables patient communication and engagement. Together, they create a connected ecosystem to improve care coordination and efficiency.

Project Details

Role: Product Design Director
Company: ResMed
Year: 2024 - 2025

CHALLENGE

In 2024, I stepped into a Product Design Director role at ResMed RCS, leading a team of 13 designers supporting a diverse portfolio of products, including Brightree (DME), Citus Health, and MatrixCare solutions across Home Health, Skilled Nursing, and Senior Living. While all products operate within the U.S. healthcare ecosystem, they serve different users, care settings, workflows, and regulatory requirements.

The organization was globally distributed, with designers and PMs across Brazil, the U.S., Canada, and India, in addition to collaboration with teams in Germany and Australia. At the time, the design function lacked standardized processes, clear role expectations, and structured career development, impacting delivery quality, team growth, and predictability. Rapid changes in AI and emerging technologies further exposed gaps in adoption speed and competitive positioning. Additionally, multiple products with different levels of maturity and inconsistent designer to squad ratios created challenges in prioritization, scalability, and resource allocation.

To address these challenges, I established a set of foundational pillars running in parallel, focused on improving delivery quality, career development, and operational efficiency. This included defining a career framework and feedback structure, standardizing design processes in partnership with Product Ops, implementing a studio model for centralized intake and prioritization, and strengthening execution quality through closer collaboration with designers and cross-functional teams.

SCOPE

Led career management, performance, and professional development for a team of 14 designers, including hiring and growth planning
Standardized design processes and improved the quality and consistency of design deliverables
Partnered with business and product stakeholders to support strategic decision-making through user experience insights
Led discoveries, research, and data-driven analysis to inform product and business strategies
Planned and aligned roadmaps, annual initiatives, and design resource allocation with product and business leadership
Managed financial planning, budgets, and design tools aligned with organizational priorities
Contributed to user flows, new experiences, usability testing, and insights analysis to continuously improve products
Drove cross-functional collaboration between design, product, and engineering to align business goals and user needs
Advocated for a design-test-iterate approach to ensure high standards of innovation and experience quality
Partnered with senior and executive leadership on initiatives impacting multiple business units and customer segments

14

Product Designers on the team

7

Business Units

+8

Different Platforms

Product Design Process

When I joined ResMed RCS, the design function lacked a standardized process, which created inconsistency in how and when Product Design was engaged. Designers were often involved too early, leading to wasted effort, or too late, compromising discovery, iteration, and delivery quality. There was also limited clarity around roles and responsibilities across teams and platforms.

This was compounded by a 1:6 designer to PM ratio, resulting in fragmented and uncoordinated demand. Requests of varying sizes, priorities, and maturity levels were sent directly to designers without structured intake, prioritization, or allocation. Additionally, teams operated with different documentation tools and levels of agile maturity, and PM involvement in design varied significantly, often leading to gaps in context and insufficient discovery.

What Was Done

To address these challenges, I established the Design Studio as a centralized model for intake, prioritization, and allocation of design work. All requests were funneled through this structure, with Product Ops supporting cross-business prioritization.

I defined and implemented an end-to-end design process, from ideation to delivery, in alignment with Product Ops, ensuring consistency across design and product workflows. I also introduced Definition of Ready (DOR) and Definition of Done (DOD) frameworks for both design and projects, in collaboration with DevOps, to clarify expectations and improve delivery quality.

To improve visibility and workload management, I centralized tracking through a dedicated Jira board for design epics, independent from squad structures when needed. This allowed better control over dependencies, timelines, and allocation.

Given the decision not to scale the team immediately, I also accelerated the adoption of the design system, enabling development teams to use tokens and components directly, reducing dependency on design for smaller initiatives and increasing scalability.

Main Outcomes

End to end design process documented and adopted across teams
Reduction from up to 9 concurrent projects per designer to a maximum of 4
Clear DOR/DOD frameworks improving role clarity and accountability
Higher quality delivery through stronger alignment with engineering
Centralized prioritization improving focus and resource allocation
Improved ability to define MVPs based on insights and business impact
Increased scalability through design system adoption and reduced design dependency

Product Design Career

When I joined ResMed RCS, the design team was highly fragmented, embedded directly within product squads without centralized structure, clear expectations, or standardized ways of working. Designers received demand inconsistently, with no shared understanding of responsibilities, deliverables, or quality standards. The team was also split between UI-focused and UX-focused roles, which limited strategic contribution and reduced depth in product thinking. As a result, designers were often positioned as executors—translating predefined PM solutions—rather than actively shaping problems, exploring user needs, and influencing outcomes holistically across the user journey.

This lack of structure extended into career development. Without defined processes, scopes, or quality benchmarks, it was difficult to establish consistent and fair performance cycles. Designers lacked clarity on how to grow, what was expected at each level, and how to evolve toward more strategic roles. Retrospectives and stakeholder interviews revealed a strong perception of stagnation and misalignment with market expectations, especially given the rapid evolution of the product design role, new technologies, and increasing demand for broader skill sets. Additionally, the global and multicultural nature of the team introduced variability in how career growth, compensation, and performance were perceived, requiring further alignment and standardization.

What Was Done

To address these challenges, I started by conducting stakeholder interviews across Product, Engineering, and adjacent teams to understand how design was perceived, alongside team retrospectives to identify gaps in career clarity and development. Based on these insights, I established a structured career framework with clearly defined pillars, outlining how designers are evaluated and how each dimension contributes to professional growth. These pillars were designed to reflect both current expectations and evolving market demands, reinforcing that career progression is dynamic, requiring continuous learning and adaptability.

I introduced recurring feedback structures, including bi-weekly one-on-ones with each designer and more formal performance cycles supported by HR. To further support individual growth, I implemented a mentorship model, pairing designers with mentors aligned to their development goals, whether focused on accelerating growth or supporting current project challenges.

To strengthen team cohesion and knowledge sharing, I established weekly design sessions where designers present work at any stage, enabling critique, feedback, and broader discussions around product context, user problems, and design strategy. This helped shift the team from isolated execution to collaborative problem-solving, improving both skill development and product understanding.

Additionally, I introduced Research and Design System office hours to support capability building beyond UI, enabling both designers and PMs to improve research practices, documentation, and technical consistency. I also worked to increase transparency around performance expectations, compensation structures, and company standards, aligning global perspectives and reducing ambiguity across regions.

Main Outcomes

Structured career framework with clearly defined evaluation pillars
Formal performance cycles with semi-annual reviews based on documented criteria
360º feedback model incorporating stakeholder input across projects and phases
Increased clarity on roles, expectations, and growth paths across the team
Improved team maturity in strategic thinking beyond UI execution
Recurring retrospectives and continuous feedback loops embedded into the culture
Mentorship model supporting personalized career development
Stronger collaboration and knowledge sharing through weekly design critiques
Expanded capabilities in research, AI, and process through internal sessions and office hours
Greater alignment across regions on performance, compensation, and career expectations

Design System

When I joined ResMed RCS, a previous attempt to establish a Design System had failed, leaving the organization without a consistent foundation for UI and front-end development. This resulted in highly inconsistent user experiences across platforms, with flows, interfaces, and patterns varying significantly. At a technical level, multiple front-end stacks were being used within the same product, often driven by individual developer preference, leading to incompatibilities, increased maintenance complexity, and performance issues such as heavier load times.

There was also a clear gap between design and implementation. Even when solutions were validated with users, final delivery often diverged from design specifications, impacting experience quality. Accessibility standards such as WCAG AA were not consistently followed—critical in a healthcare context. Additionally, as multiple products began integrating more frequently, the lack of shared standards intensified fragmentation across the ecosystem.

From a team perspective, not all designers had the technical maturity to create scalable, standardized UI, and external pressures from PMs and stakeholders often influenced delivery quality. The absence of a system not only impacted consistency and efficiency but also limited scalability, slowed development, and reduced overall product quality.

What Was Done

I led the creation of a Design System from scratch, starting with a small, dedicated team composed of a designer selected based on performance and growth potential, a front-end developer, and senior engineering support. We began by defining the technical foundation, selecting a stack based not only on current usage but also on developer adoption and long-term scalability, validated through direct input from engineering teams.

We established a robust token architecture to support multiple brands and white-label solutions, ensuring consistency while maintaining flexibility. In less than a year, we built a foundation of 50+ core components, alongside more complex, context-specific components developed in partnership with product squads.

To drive adoption, we selected pilot projects to validate and accelerate usage, while also implementing a community model: a centralized team governs the system, but squads actively contribute by proposing improvements and new components. This ensured scalability and continuous evolution of the system.

We also integrated modern tooling and AI capabilities into the workflow. This included connecting Figma directly to code through MCP, enabling synchronization of tokens and components without manual engineering effort, and leveraging tools like Storybook and Supernova for documentation, testing, and scalability. Documentation was structured to support both human and AI consumption, enabling faster front-end development and experimentation.

In parallel, I led training initiatives to standardize how designers structure files, use tokens, and prepare designs for development. This included defining clear stages (concept vs. ready-to-dev), improving Figma practices (auto layout, components, token usage), and introducing foundational front-end concepts to designers. These efforts improved collaboration with engineering, enabled better use of AI-assisted development, and reinforced overall process and career development.

Main Outcomes

Design System built from scratch and adopted across multiple products
50+ foundational components created within the first year
Standardized UI and improved consistency across platforms and brands
Reduction in front-end fragmentation and improved technical scalability
Increased alignment between design and development, reducing implementation gaps
Adoption of WCAG AA standards improving accessibility compliance
Faster development cycles through reusable components and tokenization
Reduced dependency on design for smaller initiatives through self-service consumption
Scalable contribution model enabling squads to extend the system
Integration of AI and modern tooling accelerating front-end development
Improved designer technical maturity and collaboration with engineering
Expansion to different stacks but with centralized UI strategy optimized by AI

Research Ops

When I joined ResMed RCS, research practices were largely unstructured and inconsistently applied. Research responsibilities were informally distributed between PMs and designers depending on time, scope, and individual comfort, with no standardized methodology or documentation. In many cases, anecdotal feedback from a single client was treated as a validated insight, leading to decisions based on assumptions rather than evidence. Interviews were often conducted as unstructured conversations, introducing bias and limiting the ability to separate user problems from proposed solutions.

Additionally, there was no centralized repository for insights or raw data, making it difficult to reuse knowledge across teams and products. Some platforms lacked basic feedback mechanisms such as NPS or structured tagging, and even where data existed, it was not deeply analyzed to inform decision-making. Designers, working in a studio model across multiple products, also struggled with lack of context due to fragmented knowledge across platforms, while PMs and developers remained more deeply embedded in specific domains. This created misalignment and limited the team’s ability to make holistic, data-informed decisions.

What Was Done

The goal was not to centralize all research under design, but to ensure that decisions across the organization were grounded in structured data and accessible insights. I selected a designer with strong research potential to lead this initiative, providing space for further development while building the foundation for Research Ops.

We established a centralized research framework, including standardized methods for interviews, data collection, and documentation, as well as the creation of a research repository to store both insights and raw data. Office hours and training sessions were introduced to elevate research knowledge across designers and PMs, ensuring more consistent and rigorous practices.

I structured discovery into three levels: strategic discoveries for leadership, focused on business impact (revenue, churn, market changes) supported by AI for speed and scale; product-level discoveries led by designers, combining internal and external data with structured research methods; and execution-level validation, where existing data supports rapid testing and iteration aligned with approved design strategies.

To ensure consistency, a formal design plan was introduced at the start of each initiative, defining research approach, timelines, and objectives, aligned with both design and product leadership. We also implemented mandatory validation processes—either with end users or internal SMEs—before delivery.

Finally, we worked on centralizing knowledge across platforms and integrating AI agents to improve access and usability of research data. This not only improved decision-making but also supported the evolution of designers from UI/UX roles into more strategic product designers with stronger analytical capabilities.

Main Outcomes

Centralized research repository with structured insights and raw data accessible across teams
Standardized research practices reducing bias and improving decision quality
Increased adoption of data-driven decision-making across design and product
Three large-scale strategic discoveries supporting prioritization, churn reduction, and market expansion
Key feature development (e.g., shift-to-shift for nurses) directly informed by research insights
Improved product validation with all initiatives tested with users or SMEs before release
Enhanced collaboration with PMs through shared research frameworks and AI-supported insights
Broader impact beyond product, influencing service design (training, customer support, sales)
Improved designer maturity in research, strategy, and product thinking
Faster and more scalable insight generation through AI integration

+55

Design System Components

+144

Epics Delivered

+19%

Epics delivered per month

+24%

in delivery to intake ratio

HIGH

Performance and role expansion