
Aspect Intelligence
AI forecasting platform
B2B
B2C
Contribution
Strategy; Prototyping; Design Sprint Host; Design System
Duration
1+ year
Date
2024-2025
TL; DR : My impact in a nutshellBalanced two systems with opposing needs, B2B efficiency (manager) & B2C flexibility (employee).
Shifted scheduling from reactive fixes to preference informed planning.
Reduced manual work through simpler, scalable workflows.
Designed and shipped features across forecasting, scheduling, engagement, and performance.
Contributed to the workforce design system.
40% fewer schedule change requests
2,500 hours saved annually in manual admin work
$9.5M annual savings for enterprise customers
Source: 2024 Annual Report
The Challenge: Scheduling was a constant balancing act. Managers were trying to meet staffing demands and keep operations running smoothly. Employees were trying to fit work around their lives.
How might we give employees more control over their schedules while helping managers run the workforce with less effort?
How I Contributed:Employees often reacted to schedules after they were created, creating more requests for managers. I brought employee preferences earlier into scheduling, giving employees more flexibility and control while reducing manager intervention, benefiting both side of the customer.

I designed an AI workflow that uses workforce rules and historical scheduling data to predict approval outcomes before employees submit schedule changes. It provides dynamic recommendations and suggests alternative dates in advance, reducing backend requests and resulting in 40% fewer schedule change requests.

I shifted the focus from one off tasks to the bigger picture, connecting occupancy, monitoring, and employee self-service into workflows that help managers see staffing gaps, respond to changes, and keep the right people working at the right time, without constantly managing one request at a time.
I connected experiences across forecasting, scheduling, engagement, and performance, while evolving the workforce design system to keep the product consistent as multiple teams shipped in parallel.