1. Discovery & Research

I started by interviewing 12+ stakeholders across operations, nutrition, and kitchen staff. These conversations uncovered pain points ranging from clunky cost workflows to broken navigation in the current system.

In parallel, I ran a heuristic audit and accessibility scan, surfacing 40+ usability issues (keyboard traps, contrast failures, and inconsistent interactions). I also benchmarked against SaaS leaders like ClickUp, Mailchimp, Notion, and Asana to map gaps in enterprise usability.

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2. Information Architecture, Navigation Restructure & Progressive Disclosure

When I joined the project, the platform was overloaded with features scattered across multiple screens—a clear case of cognitive overload.

I mapped critical workflows like creating new meals, managing costs, updating production schedules, and handling multi-location operations. Then I restructured the IA into five logical domains: Dashboard, Meals, Orders, Users, and Settings.

To make navigation feel intuitive, I designed role-based dashboards so each persona (kitchen lead, nutritionist, or ops manager) saw only what mattered to them.

To further reduce complexity, I applied progressive disclosure principles (NN/g):

• Show primary tasks upfront (e.g., KPIs, “Add Meal” button, ingredient lists).
• Reveal advanced options only when needed (expandable filters, accordions, and “Advanced” toggles).
• Use breadcrumbs and cues to help users drill down without losing context.

The result was a platform that felt clean, approachable, and scalable—first-time users were no longer overwhelmed, while power users could still access advanced functionality on demand.

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3. Rapid Competitive Case Studies

Before locking patterns, I ran quick case studies on micro-interactions—things like table filtering, inline editing, and order management flows. I compared how different SaaS platforms solved them (e.g., Airtable vs. Asana vs. Monday).

By dissecting these approaches, I could cherry-pick the most effective patterns and adapt them to UpMeals OS’s domain. This not only accelerated decision-making but also ensured we were learning from best-in-class tools, not reinventing wheels.

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4. Integrating the Old While Building the New

I inherited a partial design system from the previous vendor. Some pieces were salvageable; most weren’t scalable.

I conducted a system audit to rescue usable tokens and patterns while building a new design system from scratch in parallel. The new system introduced:

• WCAG 2.1 AA–compliant tokens and components
• Dynamic, enterprise-grade components (tables, bulk actions, inline editing, dashboards)
• One unified source of truth for dev handoff

This hybrid design system balanced speed of adoption with future scalability—a win for both design and engineering.

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5. Prototyping & Early User Testing

With the first redesign prototype ready, I ran user tests with 10 real UpMeals partners (kitchen staff, nutritionists, and operations managers).

• Key feedback: the IA felt clearer, but cost tables were still overwhelming.
• Iteration: I simplified data tables further, added progressive disclosure, and visualized dependencies with clear network-style diagrams.

Testing this early not only validated design direction but also built trust with stakeholders who saw their feedback implemented quickly.

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6. Communication Through Design Annotation & Comparison Decks

To align stakeholders across operations, product, and engineering, I prepared detailed design annotations and comparison decks.

• Annotations: Every flow and component had clear notes for behaviour, accessibility, and dev logic, making handoff smoother.
• Comparison decks: I presented side-by-side comparisons of “old vs. new” and multi-platform references, so non-design stakeholders could easily see why decisions were made.

This approach eliminated ambiguity, streamlined decision-making, and gave stakeholders confidence that the redesign was data-driven, not just aesthetic.

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7. Simplifying a Complex SaaS Into an Intuitive Experience

The heart of the redesign was taming operational complexity and making it approachable. I simplified through three levers:

1. Restructured IA → Clear domains & role-based dashboards
2. AI-Driven Indicators → Predictive alerts for cost variance, low inventory, scheduling conflicts
3. Data Visualization + Progressive Disclosure → Dense spreadsheets became layered charts; advanced options stayed hidden until needed

The result: workflows were 40% faster, error rates dropped significantly, and users actually described the platform as “less overwhelming.”

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8. UX/UI Execution & Iterative Refinement

I built interactive prototypes in Figma and iterated quickly, layering in:

• KPI-focused dashboards
• Real-time “meal builder” with costing + label previews
• WCAG-compliant forms with inline validation
• Bulk management tools for users and locations

These refinements were tested in rapid design-test cycles, allowing me to address usability concerns beforehand.

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9. Developer Handoff & QA

I delivered a hybrid design system in Figma Dev Mode, with tokens mapped into the library and design system for engineering. Weekly QA involved WCAG testing, keyboard navigation checks, and screen reader reviews, ensuring the accessibility standards carried into production.