Designing with Intent: How I turn complex ideas into enterprise-ready, inclusive experiences
Great design is more than UI. Big-tech products live or die on speed, scale, and trust. After 15+ years leading design at SAP, IBM, Zillow, and UNEP, I’ve distilled a Lean, data-informed approach that keeps teams small, experiments fast, and outcomes measurable—all while embedding accessibility and ethical guardrails from day one
This process is structured around user-first thinking, cross-functional alignment, and data-driven decision-making. Here’s how I translate these principles into action across five essential phases:
1. EXPLORE – Align on the North Star
Outcome: a single, measurable vision everyone can recite
The journey begins by aligning all stakeholders around a shared purpose.
- Define the customer pain points and core user problem.
- Facilitate narrative workshops to craft a compelling North Star and future-state story.
- Surface risks early with assumption mapping and feasibility checks.
- Lock success KPIs and guardrails with product, engineering, and executive sponsors.
2. DISCOVER – Validate the Problem Space & Frame the Opportunity
Outcome: clear opportunity statements backed by real-world evidence
I dive deep to ensure the problem space is real and worth solving. This involves hands-on field research, ethnographic studies, and telemetry mining to uncover latent insights and edge use cases.
- Build Jobs-to-Be-Done (JTBD) maps and personas that reflect edge-case realities.
- Constructing concise opportunity statements.
- Engaging closely with UX researchers, data scientists, designers, and accessibility specialists to frame the problem effectively.
- Conduct field research, ethnography, and telemetry dives to surface pain points.
3. DESIGN – Co-Create, Prototype & Decide
Outcome: evidence-backed concepts ready for engineering
Step 1. Co-Create Concepts: Divergent design jams & storyboards
- I facilitate cross-functional design jams to explore a wide solution space, generating a range of divergent concepts. Using storyboards and lightweight prototypes, I collaboratively narrow down concepts for validation.
Step 2. Prototype & Prove: Sprint-length interactive tests
- Interactive design sprints test desirability, feasibility, and viability. By piloting with real users and capturing telemetry feedback, I quickly identify whether to persevere, pivot, or sunset a solution.
Step 3. Align & Decide: Roadmap commits, DRIs, and go/kill calls
- After prototyping, we review key learnings, analyze outcomes, and formalize the decision-making process. Deliverables such as updated roadmaps and DRIs (Directly Responsible Individuals) ensure clarity and accountability moving forward.
This phase integrates the efforts of product leads, engineers, designers, legal/compliance officers, and data analysts to ensure decisions are not only evidence-based but scalable.
4. DELIVER – Ship Fast, Audit Constantly
Outcome: production-grade releases that improve in real time
I favor shipping early and often, guided by trunk-based development and continuous integration. Real-time feedback loops from accessibility and performance audits ensure our output is inclusive and production-ready.
- Design/development pods work in parallel sprints.
- Launches are accompanied by rigorous A/B testing and progressive rollout strategies to de-risk at scale.
- Trunk-based development with continuous integration.
- Automated accessibility/performance audits in every pull request.
- Post-launch retros feed the next sprint within 24 hours.
Key collaborators during this phase include developers, QA specialists, copywriters, and customer support teams.
5. RUN & SCALE – Sustain Growth & Trust
Outcome: products that get better—and safer—the longer they live
Post-launch is not the end—it’s the beginning of continuous improvement. I focus on long-term trust through governance, personalization, and ethical oversight.
- Growth loops and adaptive onboarding drive adoption without extra headcount.
- Quarterly privacy, ethics, and accessibility checkpoints keep us future-proof.
- Live dashboards track OKRs, customer satisfaction, and reliability in one view.
This stage is a collaboration across growth teams, privacy officers, customer success, and executive stakeholders.
Four Principles Behind Every Decision
- User-First, ROI-Tied: Starts with real needs and ends with measurable business impact.
- Lean & Cross-Functional: Small pods, zero bureaucracy, continuous momentum.
- Evidence Over Opinion:Telemetry and user signals trump aesthetics alone.
- Governance by Design: Ethical AI, privacy, and accessibility aren’t add-ons—they’re baked in.
Ready to see this playbook in action?
Explore case studies where these methods scaled SaaS revenue, boosted conversion, and raised accessibility scores across millions of users.