Designing for Clarity Beyond the Interface

The Challenge

Our healthcare manufacturing client developed a digital pathology platform that revolutionized patient-centered care and the pathology workflow. As the platform matured, it brought together a wide ecosystem of stakeholders — pathologists, lab administrators, product managers, developers, business stakeholders, and documentation teams — all working from different interpretations of the same product.

Teams were regularly discussing the same features, pages, and workflows without a shared mental model of how they fit together. This became especially apparent during UI reskins, UX improvement initiatives, and feature discussions. Before any design or product decision could move forward, teams first had to reconstruct context from multiple sources — navigating live environments, searching user guides, or relying on the institutional knowledge of individual team members.

New team member onboarding compounded the problem. Without a visual map of the platform, getting up to speed meant navigating an overwhelming development environment and working through extensive documentation with little orientation.

The challenge was not simply understanding the interface. It was creating clarity across the entire ecosystem of people designing, building, documenting, and using the product.

The Solution

To protect the speed and quality of cross-functional product decisions, Concord approached this as an ongoing UX intelligence and alignment initiative — not a one-time documentation exercise.

The work began with a bird's-eye view of the platform, mapping its major areas and progressively breaking them down into pages, sub-pages, features, and relationships. From there, the map evolved into a comprehensive living framework that brought together multiple layers of product understanding:

• Information architecture — mapped the platform's major areas, pages, sub-pages, and relationships to give teams a clear structural foundation.

• Journey mapping — documented how users move through key areas of the platform and where different experiences intersect.

• Workflow mapping — visualized complex workflows and the relationships between screens and actions.

• Click-count analysis — analyzed the number of interactions required to complete key tasks, surfacing friction points and opportunities to streamline.

• Platform version comparison — captured screenshots from both nDP 3.0 and nDP 2.x, creating an accessible visual reference for discussing design evolution and changes across versions.

• UX intelligence layer — added annotations to capture open questions, assumptions, development dependencies, parameters requiring clarification, and opportunities for future UX improvement.

• AI-assisted analysis — used NotebookLM and Claude to analyze platform documentation, identify relationships and inconsistencies, and accelerate the synthesis of large volumes of product information. Rather than replacing UX judgment, AI acted as an augmentation layer — allowing the designer to spend less time manually collecting and organizing information and more time interpreting it, identifying patterns, and applying design thinking.

The primary deliverable was a living, collaborative Lucid workspace that served as a shared visual reference across the full cross-functional team — connecting information architecture, user experience, workflow understanding, and continuous improvement in one place.