AI Decision Intelligence for Blood Drive Operations

created for

Designed an AI-supported planning platform for blood drive operations, unifying forecasting, resource allocation, field reporting, and performance tracking into a single operational decision environment. The platform transformed fragmented planning workflows into a unified decision system supporting operational visibility, explainable AI recommendations, and coordinated decision-making across regional blood services teams.

My Role: Lead Product Designer
Timeframe: 2025–Present
SERVICE DESIGN
SYSTEMS UX
OPERATIONS
AI WORKFLOWS
Cropped image of left half of a laptop screen, showing a SaaS dashboard of metrics for blood drive analysis and reporting.
THE CHALLENGE
Fragmented operational planning of blood drives limited confidence in strategic decision-making.
Blood drive planning relied on disconnected forecasting, scheduling, resource allocation, field reporting, and performance tracking, forcing regional teams to assemble information from multiple sources before making operational decisions. The original concept centered on using AI to score blood drives, but early conversations suggested the larger challenge required understanding the operational blood drive service ecosystem itself.
UNDERSTANDING THE SYSTEM
Research uncovered how operational decisions were actually made.
Through user research interviews with regional executives, operations managers, and field representatives, I mapped how blood demand fluctuated, how collection goals were established, how resources were allocated, and how information flowed between planning, field operations, and post-drive analysis. Rather than isolated workflows, I found a continuous operational ecosystem with fragmented visibility and inconsistent feedback loops.
IMAGE: A diagram of mobile blood drive apps pointing to a central laptop labeled 'AI-Generated Insights, Red Cross Operations'. A diagram of circles leading to each other follows a process: FORECAST Targets, ALLOCATE Resources, Launch Drive, MEASURE Outcomes, REFINE Future Plans. An arrow loops around to show the process is cyclical.
DEFINING THE PRODUCT
Moving beyond AI performance scoring to a unified operational decision system.
Instead of designing another reporting dashboard, I reframed the product as a unified operational platform connecting forecasting, scheduling, field inputs, and resource allocation into a continuous decision workflow supporting regional and field teams. The integration of AI strategic recommendations would coexist without reducing user trust or removing human judgment.
IMAGE: A diagram of mobile blood drive apps pointing to a central laptop labeled 'AI-Generated Insights, Red Cross Operations'. A diagram of circles leading to each other follows a process: FORECAST Targets, ALLOCATE Resources, Launch Drive, MEASURE Outcomes, REFINE Future Plans. An arrow loops around to show the process is cyclical.
SYSTEM DESIGN
The platform was organized around real-world operational workflows instead of individual features.
I designed multi-role workflows connecting forecasting, scheduling, CRM data, field observations, and analytics into a shared decision environment. AI functioned as an advisory layer that surfaced explainable recommendations while preserving human oversight and creating structured feedback loops to improve future predictions. The platform coordinated the distinct responsibilities of field representatives, operations managers, and regional executives through shared operational visibility and role-specific workflows.
IMAGE: A flow diagram depicts system architecture for how Blood Drive inputs lead to an AI & Analytics Ingestion Loop.
EXPERIENCE DESIGN
Interfaces surfaced complex operational information in ways teams could confidently act upon.
The experience included planning dashboards, forecasting tools, recommendation workflows, mobile field reporting, data visualizations, and reusable design system components that helped each role understand operational status, evaluate tradeoffs, and take action with confidence.
A collage of pages from a User Research Test Plan is shown along with a wireframe of the Blood Drive Dashboard, and a screenshot of a video chat showing a Blood Drive Dashboard protoype.
OUTCOME
A unified decision platform replaced fragmented planning workflows.
The project evolved from an AI scoring concept into an enterprise decision-support platform connecting forecasting, planning, field operations, and performance analysis into a shared operational environment. The result was a system designed to improve coordination, visibility, and trust across regional blood services teams.
An image shows a dashboard of Upcoming Blood Drives on a laptop, alongside a mobile device showing an interface entitled 'Drive Manager'.
END OF CASE STUDY SUMMARY
Full case study available with additional research and design documentation.
✕

🔒 Security Check