Enterprise B2B · 2021–Present
Signals Notebook
Lineage visualization for global pharma R&D teams
Impact Snapshot
TL;DR
Cut lineage tracing time 66% in task-based usability checks (2 hours to 40 minutes) by designing an interactive visualization for tangled biological material relationships. The number measures the tracing workflow itself — adoption and NPS also moved with rollout timing, product maturity, and customer context.
Pain
Scientists needed 2+ hours to reconstruct one material lineage.
Decision
Make the lineage map primary, with tables as evidence support.
Result
Tracing time dropped from 2 hours to 40 minutes.
Evidence
Scaled inside a $100M+ enterprise product context.
+20%
NPS Score
25 → 30, post-release pulse
-66%
Tracing Time
Task check: 2hrs → 40min
$100M+
Annual Revenue
Contribution
1M+
Workflows
Annually
Measurement boundary: I present the -66% as a task-based usability outcome for the lineage tracing workflow, not as a claim that design alone changed all product behavior. NPS and revenue figures describe post-release/product context; the clearest design contribution is reducing the steps scientists needed for discovery, orientation, and export.
1My Role & Context
My Responsibilities
Owned the end-to-end lineage workflow design: research synthesis, IA, wireframes, prototypes, usability checks, engineering handoff, and PM/engineering alignment on scope
Team
Me (Sr. Product Designer), 1 Product Manager, 10 Dev Engineers
Timeline
~5 months (2021-Present)
Tools
Figma, Jira, Confluence, Miro
Role boundary: I was the sole product designer on this workflow, so I owned the design strategy and interaction model. Product prioritization, technical feasibility, and release timing were shared with the PM and engineering team; my senior-level contribution was making the trade-offs explicit enough for the team to commit.
2Understanding the Product
Signals Notebook is an AI-powered electronic lab notebook (ELN) trusted by 10,000+ scientific teams worldwide. It talks to ChemDraw, Spotfire, and lab instruments over APIs, and runs 1M+ workflows a year.
Key Clients: Pfizer, Roche, Novartis, Johnson & Johnson, Takeda, Moderna, GSK, Merck, AstraZeneca, Bayer, and more. These pharmaceutical giants rely on our software for mission-critical research.
3The Challenge
“Scientists spent 2+ hours just to trace where a single cell line came from”
User interviews with bench researchers at major pharma companies surfaced four pain points:
- Data Fragmentation: Lineage data was scattered across different experiments, tools, and formats—making it error-prone to piece together a complete history.
- Complex Relationships: Biological materials (cell lines, proteins, antibodies, viral vectors) have layered parent-child connections that existing tools couldn't visualize clearly.
- Scalability Issues: As research grew, systems struggled to handle large datasets and real-time collaboration.
- Non-Technical Users: Current visualization tools were designed for data scientists, not bench scientists who needed quick answers.
4Competitive Analysis
I sized up the existing life-sciences solutions:
WormWeb
✓ Simple, interactive lineage tracking for model organisms
✗ Can’t scale to complex biologics workflows
LabKey
✓ Flexible data integration and lineage grids
✗ Weak on real-time collaboration and large datasets
IDBS
✓ Robust cell line genealogy and compliance features
✗ Interface too complex for non-technical users
Key insight: scientists don’t think in database queries — they think in relationships. “Where did this cell line come from? Which experiments used it? What batches were derived?” The solution had to mirror that mental model.
Design Decision
Map-first, not table-first
Competitors all default to table views. But interviews showed scientists think in relationships, not rows. I made the interactive map the primary view and demoted tables to secondary — matching how they actually model biological lineage. In task-based usability checks this cut tracing time 66%: users no longer had to mentally rebuild hierarchies from flat data. The design contribution showed up strongest in discovery, orientation, and export readiness.
Influence & Alignment
Turned a risky visualization shift into a buildable enterprise workflow
The hard part wasn’t convincing anyone lineage mattered. It was getting PM and engineering to trust a map-first experience inside a compliance-heavy product. So I reframed the proposal as a low-risk workflow change rather than a visual experiment: keep Smart Folder for discovery, put the graph inside a dedicated Lineage tab, retain table/export for audit, and never force users into a new information architecture. That compromise handed PM a cleaner scope and gave engineering a buildable path.
Trade-offs
Rejected: Table-only
A table-only fix was safer to build, but it kept the core cognitive load: scientists still had to reconstruct parent-child relationships manually.
Constraint: Scale
Large material graphs could become unreadable and expensive to render, so I used progressive exploration rather than exposing every relationship at once.
Cut from v1
Full cross-product lineage was kept as a direction, while v1 focused on Materials Smart Folder, Lineage tab, table support, and export readiness.
5Design Process
I designed a streamlined workflow that lets scientists trace lineage in seconds instead of hours:
1
Materials Smart Folder
2
Select Material
3
Go to Lineage Tab
4
View Map & Table
5
Configure & Export
6Design Showcase
Complete design flow for the Lineage Visualisation feature — from existing state to final high-fidelity screens:
Before: Existing experiments table — lineage data scattered across views
Recommended: Materials Smart Folder with unified search and filtering
Materials Smart Folder — view all material types in one interface
Material Detail Page — view and edit single material properties
Lineage Tab — interactive lineage map and lineage table view
Configure/Export — advanced actions for lineage data management
7Solution: Key Features I Designed
Materials Smart Folder
A unified view of all material types (Cell Lines, Proteins, Antibodies, Viral Vectors) organized in one searchable, filterable interface. Scientists can now find any material in seconds.
Interactive Lineage Map
Visual representation of parent-child relationships with clear distinction between Asset Level (black nodes) and Batch Level (orange nodes). Users can click to expand, collapse, and explore relationships.
Lineage Table View
Tabular alternative for users who prefer data grids. Supports sorting, filtering, and bulk export to Excel/PDF for compliance documentation.
Cross-Product Integration
Seamless integration with Signals Inventa and BioDesign—scientists can trace lineage across experiments, projects, and even different product lines.
💭 What I Learned
Enterprise B2B design isn’t consumer design. Users can’t just switch to a competitor if they hate your UI — they’re locked into multi-year contracts. So every friction point compounds into hours of lost productivity across thousands of users. The lineage map taught me that visualization isn’t about being clever. It’s about being invisible. Best compliment we got: “It just shows me what I need to know.”