Service Delivery at Scale
Design leadership across federal programs serving millions. Working at the intersection of policy intent and delivery reality to improve how eligibility systems, intake processes, and service recovery work in practice.
The problem
Government services fail at the moments that matter most: when someone needs help navigating a complex system under time pressure.
The issue wasn’t just bad interfaces. Eligibility systems, intake processes, and case management tools were built to satisfy policy compliance and processing volume—not to support completion, recovery from errors, or the downstream consequences of ambiguous decisions.
The real question: How do we design services that help people complete what they started, even when the system wasn’t built with that goal in mind?
Understanding the landscape
Working across multiple federal programs revealed a pattern: the same failure modes kept appearing, regardless of the specific domain.
My approach
I led design work at the intersection of policy intent and delivery reality, focusing on three key areas:
1. Mapping decision points + failure states
Rather than starting with wireframes, I mapped where people actually got stuck. This meant:
- Identifying drop-off moments as operational failures, not UX quirks
- Documenting dead-end states where no recovery path existed
- Connecting design decisions to downstream support burden
:::quote attribution=“Program Director, Federal Benefits Agency” “Ron helped us see that what we called ‘user confusion’ was actually a design problem we could solve. The consequence mapping changed how we prioritize work.” :::
2. Building a shared vocabulary
Teams were talking past each other—engineers optimizing for throughput, policy experts focused on compliance, designers pushing for better UX. I created a framework that:
- Established terms teams could use to debate service mechanics
- Developed critique prompts focused on decision clarity
- Made the cost of ambiguity visible in operational terms
3. Developing reusable patterns
The real leverage wasn’t in perfecting one program—it was in creating patterns that could travel across programs.
Key decisions
Throughout this work, I made strategic choices that shaped the outcomes:
Optimized for recoverability over polish Because dead ends are the true failure mode in high-stakes services. A slightly rougher interface that helps people get unstuck is far more valuable than a polished flow with no escape hatches.
Surfaced requirements earlier instead of hiding complexity Late-stage surprises drive abandonment. Better to be clear upfront about what’s needed than to optimize for a happy path that only works for 30% of users.
Built patterns that travel across programs One-off fixes don’t create systemic change. I focused on developing reusable patterns that teams could adapt to their specific context.
Design principle: In high-stakes services, recoverability matters more than elegance. The goal isn’t a perfect happy path—it’s helping people complete what they started when things go wrong.
Outcomes & impact
The patterns and approaches developed through this work were adopted across multiple federal programs:
Beyond the numbers, the biggest impact was a shift in how teams thought about service design. “Consequence mapping” became a standard part of design critique and training. Teams started measuring success not by processed applications, but by completed journeys.
What this demonstrates
I can walk into complex, politically constrained delivery environments and find leverage points where design decisions create outsized impact.
I don’t need clean slates. I work inside real systems—policy constraints, legacy tooling, operational reality—and improve how decisions get made, communicated, and recovered from when they fail.
This is design leadership in the context of delivery at scale: finding patterns that travel, building shared language across disciplines, and connecting service design choices to measurable operational outcomes.