Scheduling with AI
As the Product Design Lead, I worked directly worked with MIT Lincoln Laboratory and Air Mobility Command to strategize the design process to integrate smart recommendations for Puckboard’s scheduling tool.
Summary:
The RVCM team collaborated with MIT Lincoln Laboratory to optimize Puckboard’s scheduling tool through recommendations.
Schedulers are assisted by intelligent recommendations to calculate optimal aircrew for events while considering aircrew currency, availability and burden distribution across the unit.
Team:
Primary Audience:
Pilot, Scheduler and Aircrew members within Air Mobility Command’s C-17 Airframe.
Specific Units: 21st Airlift Squadron, Travis AFB | 8th Airlift Squadron, Joint Base Lewis-McChord | 15th Airlift Squadron, Hickam AFB
MIT Lincoln Laboratory
Principal Investigator
Algorithm Engineers
Human Factors Researcher
User Experience Designer
Dept of Air Force / MIT AI Accelerator Director of AI Research
United States Air Force
Mobility Officer
AMC Chief, Systems Branch, Requirements Manager
AMC GTIMS Requirements Manager, Systems Branch Chief
Various Aircrew Members
Puckboard / RVCM
Program & Project Managers
Tech Lead
Software Engineers
Subject Matter Experts
Product Designers
Discovery & Research
Discovery & Research
June 2022
RVCM, MIT Lincoln Laboratory and Air Mobility Command stakeholders from the United States Air Force collaborated in Honolulu, HI to kick off the initiative. The main goal was to understand the algorithm capabilities, build trust and strategize the product development.
July 2022 - Present
Continuous feedback from Aircrew to understand their needs and expectations for the “solver” recommendations.
Soft Launches to specific USAF units who are interested in “solver” capabilities.
User Working Group Feedback Sessions to include a more diverse pool of users.
January 2023 - Present:
Continue to validate or invalidate if current users benefit from scheduling recommendations through 2 week iterations for the following scenarios:
Fuel savings
Optimal aircrew
Burden distribution
Upcoming events
Aircrew currency
Research Methodology:
Feedback sessions via Zoom: 1:1 user interview, feedback sessions and larger group discussions
In-person visits: observational research on USAF bases that include product demos, usability tests and focus groups
Public Mattermost Channels: Track interest, post updates and understand user needs by chatting directly with participants.
Research Synthesis:
Affinity Mapping
Scheduler Persona & Workflow
Aircrew Member Persona & Workflow
Participant Feedback
Design Process
Agile Ceremonies:
The design team works on a Scrum team and participants in
Sprint Planning
Design Collab
Design Sync
Sprint Review and Retrospectives
Additional Design Ceremonies:
Vector Check: Check in with stakeholders to validate or invalidate design progress and pivot as needed
Puckboard AI Working Session: Collaboration between MIT Lincoln Laboratory and Puckboard Design teams
MIT/PB Sync: Check in to confirm design, development and solver teams are moving towards the same unified direction for integration of AI into Puckboard
Design Audit: Confirmation that live product matches the designs
Problem Statements:
As a Scheduler, I need to assign optimal aircrew members to events in Puckboard so I can save fuel and distribute burden effectively across my unit.
As a Scheduler, I need to view recommendations so I can assign optimal aircrew members to events in Puckboard.
As an Aircrew member, I need to view upcoming events and currency status so I can request events that will fulfill requirements to stay mission-ready.
Constraints & Opportunities:
Building Trust: adjust to “Recommendation” vs. AI language. Communicate the solver as a tool enhance scheduling rather than a replacement of the scheduler role in Puckboard.
Wait time: some participants were resistant to the solver tool because it took a few minutes due to limitations with ARMS and Platform 1.
Design Tasks: The solver team was a resource for initial research and data. The design team was tasked with integrating the AI solver into the Puckboard product and workflow.
Key Takeaways
The following features would be helpful for participants:
Individual aircrew dashboard
Unit level (scheduler role) dashboard
Upcoming Events
Aircrew Recommendations
Event detailed currencies
Flight hour views
Legality constraint data
DNIF status
Impact statements