Role
Lead Designer
Duration
Jan - Apr 2024
Team
Context
Competitive intelligence at AbbVie involves a systematic, multi-step process that enables the company to make smart decisions, particularly in the high-stakes area of developmental drugs. At a high level, it helps the company:
Stay ahead of competitors
Minimize risk and R&D waste
Have timely patient impact
Problem
Scientists at AbbVie faced a tedious and fragmented process for conducting competitive intelligence, slowing drug development efforts.
Outcome
My team and I created a platform that helps 8000+ scientists find up-to-date drug information within seconds, which are used to make strategic business development choices that save the company tens of millions of dollars.
Scope
A kickoff meeting was held to explore building a tool that would streamline the time-consuming process of competitive intelligence analysis. Stakeholders shared a clear vision and set aggressive deadlines, confident they understood user needs and what the solution should be.
I saw an opportunity to challenge that assumption. I advocated for and led user interviews, shifting the project from being assumption-driven to user-driven. These interviews uncovered critical insights, helping us map the user journey and define high-level jobs to be done.
Research revealed that while the proposed solution addressed some pain points, it overlooked deeper challenges that, if solved, could significantly improve scientists' workflows. Despite these findings, stakeholders remained committed to their initial vision.
Accepting the tradeoff of perfection for velocity with intention, I moved forward with a first iteration aligned to stakeholder goals while keeping future improvements in mind. I quickly ideated, wireframed, and prototyped key features which played a central role in the successful presentation of the tool at AbbVie's global innovation showcase, the Celebration of Science. The project generated excitement and strong interest from scientists eager to test and provide feedback.
After refining the prototypes, I packaged the final designs into a developer-ready handoff file, maintained close collaboration with engineering, and conducted thorough visual QA to ensure smooth implementation. The result exceeded expectations, earning strong stakeholder satisfaction and laying a foundation for future enhancements.
Research
The stakeholders wanted to modernize the competitive intelligence workflow to improve the drug development process. They identified the search phase within the competitive intelligence workflow as a major pain point that is time-consuming, inefficient, yet critical to the overall process. With validating this assumption as our focus, my team and I proposed conducting user interviews to understand how scientists currently perform competitive intelligence searches and to uncover key opportunities for improvement.
Through our research, we identified several key problems that scientists felt were most disruptive to their workflow. Addressing these issues would significantly improve the search phase of the competitive intelligence process and move us closer to our goal.
1
High friction when googling
Scientists noted that they felt pressure to work faster and expressed the concern of taking too much time to Google articles and press releases related to competitor drugs.
2
Low confidence
Scientists struggled to determine which results warranted deeper review, causing them to either miss important information or spend excessive time researching.
3
Possibilities are overwhelming
Scientists found it daunting to sift through multiple pharmaceutical databases like the National Institute of Health and thousands of Google results at the start of their investigations.
Opportunity
Insights from our user interviews revealed a key challenge. Although scientists could find useful content, the tools they used were not designed for navigating complex medical information, making the process frustrating and inefficient. This led us to a core hypothesis. Consolidating all relevant information into a single, streamlined interface could reduce the number of steps required to create a competitive landscape report and alleviate the friction outlined in problems 1 and 3, assuming the solution was technically feasible. To address problem 2, we hypothesized that adding clear trust signals would give users greater confidence that the information they were reviewing was credible, relevant, and up to date. Publication dates, source links, and confidence scores were some of the key trust signals that needed to be extracted from various drug databases and displayed to make it easy for users to assess the reliability of the information at a glance without overwhelming them with raw data.
Platform: Data Consolidation Tool
The search portion of the user journey plays a pivotal role in the competitive intelligence workflow. It shapes how efficiently scientists can produce a comprehensive analysis of competitive landscapes. To reduce friction and make the workflow more enjoyable for our users, I reimagined the way scientists discover and filter information on developmental drugs.
Previously, scientists had to manually navigate multiple sources, such as the National Institute of Health and other databases, just to piece together basic insights. This not only slowed their progress but also left them overwhelmed by fragmented tools and inconsistent interfaces.
With the Competitive Intelligence Search Tool, we centralized this process. The new search experience pulls relevant data from trusted sources into one cohesive view, enabling scientists to explore, compare, and analyze information without switching between platforms. This shift significantly reduced time spent searching and made it easier to uncover meaningful insights.
Feature: Custom Entry Point
To surface the precise information scientists needed, I designed a powerful and flexible search component tailored specifically for developmental drug research. Rather than relying on a generic search bar, this component was built to reflect how scientists think by offering contextual filters that let users narrow or broaden their search based on their specific goals.
Scientists could input as many or as few parameters as they wanted, giving them control over the depth and scope of their queries. We hypothesized that this level of search customization would reduce the number of steps required to find relevant data and significantly improve the speed and accuracy of the experience.
Early and close collaboration with developers was essential to building this component, as it relied on complex but intuitive interaction design. I worked with the engineering team from the start to explore different interaction models, aligning on what was feasible and user-friendly. Throughout the development process, we continued meeting regularly to review progress and ensure pixel perfect implementation. This tight feedback look allowed us to catch and simplify overly complex interactions early on, which not only improved the user experience but also made implementation smooth and more efficient.
Feature: Tools for Deeper Investigation
To help scientists verify and trust the information they were reviewing, I designed a detailed drug view page optimized for deeper investigation. The goal was to give scientists the context they need at a glance, while still giving them the flexibility to easily pursue additional trust signals if needed. Our hypothesis was that showing these trust signals in one place would increase user confidence in the data and make it easier for scientists to validate or act on the information efficiently.
Summary
By the end of the project, we successfully delivered on our north star by creating a platform that reduces the effort required to generate competitive landscape reports and removes key friction from the competitive intelligence workflow.
Scientists can now search for developmental drug information using flexible inputs, enabling quick comparisons and deeper exploration of individual compounds. What was once a fragmented, manual process is now centralized, faster, and more intuitive.
The platform also increases user confidence by surfacing trust signals like source links, publication dates, and validation statuses—helping scientists make decisions with greater speed and assurance.
A strong Net Promoter Score of 58 reflected high user satisfaction and energized the team to pursue additional features scientists had initially requested, including:
Improved performance through deeper engineering collaboration
Real-time alerts to track drug development activity
Drug history comparison tools
Integration with existing AbbVie platforms
These opportunities offer a clear path to expand the platform’s impact and further support scientists in their decision-making.
Takeaways
In this project, stakeholders had a clear vision and tight deadlines. They needed a working prototype to showcase at an internal innovation conference. However, early user research revealed that their proposed solution didn’t address the core friction scientists were experiencing in their workflow. Rather than reject the stakeholder direction outright, I took a hybrid approach. I moved forward with their concept to meet the immediate need, while layering in insights from user interviews to shape the design in ways that would be more usable and scalable long-term.
This experience taught me that user-centered design isn’t always about pushing back. Sometimes, it’s about meeting stakeholders where they are, building momentum with early wins, and embedding user value incrementally. By doing this, I was able to build trust, gain influence, and pave the way for deeper user validation in future iterations.
