Batch Traceability

When defects surface, every minute matters

In pharmaceutical manufacturing, a batch defect sets off a chain reaction. Quality teams need answers immediately: Where was this batch manufactured? Which suppliers were involved? What finished products contain material from this batch? Which patients could be affected? When a defect appears in a pharmaceutical batch at AbbVie, tracking down impacted products meant navigating multiple disconnected systems, spreadsheets, and paper records — a process that was slow, error-prone, and resource-intensive.

There was no single place to answer the critical questions a quality or supply chain team needs when investigating. Each department maintained their own workarounds: spreadsheets for logistics, system A for material sourcing, system B for manufacturing history, paper records for audits. A comprehensive defect investigation that should take hours could stretch into days.

One platform for complete batch visibility

Batch Traceability was designed as a unified web application that gives users a complete, navigable view of a product batch's full manufacturing history, spanning multiple sites and geographies. From a single search, users can trace upstream (raw materials, suppliers, component sources) and downstream (finished products, distribution destinations) genealogy, view detailed batch information, and surface associated quality issues, all without leaving one screen.

The application replaced the need to context-switch between multiple systems. A quality investigator could search for a batch number, see its complete lineage, understand every step in its journey, and identify related batches that might need investigation — all in one interface. For the first time at AbbVie, batch traceability became a real-time, accessible tool rather than a manual, error-prone process.

Understanding the stakeholder landscape

The foundation of this project was a comprehensive stakeholder interview program. I conducted in-depth sessions with subject matter experts across every business area that touched batch data — from Quality teams investigating defects to Supply Chain managing logistics, from FDA compliance officers ensuring regulatory traceability to Suppliers providing raw materials. Each group had their own mental models, workflows, and data needs.

This wasn't traditional user research with end-to-end observation — it was strategic, domain-focused discovery. These SME interviews revealed a shared frustration: no single platform existed where all batch-related information could be found. Every team was building their own workarounds, creating silos and inconsistency.

The fragmentation problem

The discovery process surfaced a consistent theme across all interviews: in a defect investigation, teams had to answer a series of critical questions, and answering any one of them required touching multiple systems, each with incomplete data. This meant investigations were significantly slower and more expensive than they needed to be.

When a patient complaint arrived, quality teams typically faced a sequence like this: Search the complaint system for batch ID, pull manufacturing records from another system, check supplier sourcing data from a third system, manually trace downstream finished products using spreadsheets, coordinate with supply chain on movement history, and piece together the story from paper records. What should be a 2-hour investigation became a multi-day effort.

User research — understanding how quality and supply chain teams investigate batch defects

From fragmentation to navigation

The core design challenge wasn't displaying batch data — it was structuring navigation through a complex, multi-layered genealogy. The genealogy visualization was the most challenging design problem: how do you show upstream and downstream traceability in a way that doesn't overwhelm the user but still gives them the complete picture?

The breakthrough was to treat genealogy as a navigation problem, not a data display problem. Rather than try to show everything at once, I designed a clear, hierarchical entry point (search), which would reveal the genealogy as users navigated through the batch's history. This approach prioritized clarity and accessibility for a domain where users were often working under pressure.

Task flow — mapping the investigation journey from defect report to resolution

UI & style guide — design system aligned with AbbVie's internal standards

What the platform delivered

The final design centered on four core capabilities that directly addressed the stakeholder needs identified in discovery. Each feature was designed to make a specific type of investigation faster and more reliable.

From discovery to prototype

The design process followed a structured path: stakeholder interviews to understand the problem space, persona creation to represent different investigation scenarios, task flow diagramming to map the investigation journey from defect report to resolution, and design pattern definition to align with AbbVie's internal design system. This foundation then translated into high-fidelity wireframes and interactive prototypes that were tested and refined through feedback loops with SMEs and the development team.

Each design decision was grounded in the actual workflows and pain points we'd observed in interviews. The interface evolved through several rounds of feedback from quality teams, supply chain leaders, and compliance officers, with particular focus on edge cases and investigation scenarios that occurred in real defect investigations.

Search — single entry point to find any batch by ID, material, or dates

Search results — ecosystem view showing batch lineage at a glance

Filters — narrowing traceability by material type, site, and date range

Batch details — complete manufacturing history, quality issues, and audit trail

Select a batch — navigating upstream and downstream genealogy step by step

Impact and adoption

The Batch Traceability application has become an actively used platform across multiple business areas, from routine compliance work to urgent defect investigations. Users report that the interface makes complex batch data accessible and the navigation intuitive — a significant achievement for such a data-heavy domain.