Overview:
Developed product and executed go-to-market strategy for Part Snaps, an innovative aircraft part ordering app that uses machine learning to reduce parts ordering time by 98% and eliminate human error in the process.
Problem Statement:
Aircraft maintenance teams face significant delays in parts ordering due to inefficient manual processes, leading to prolonged aircraft downtime and increased operational costs.
Solution/Value Proposition:
Part Snaps is a mobile app that uses machine learning to cut parts ordering time.
Enhance operational efficiency, reduce costs, and ensure mission-critical readiness by eliminating human error and wasted time from the parts ordering process.
My Role:
Led market research to identify and validate depth of user needs and pain points.
Developed the product strategy, including feature prioritization and roadmap planning.
Oversaw the design and development of the machine learning algorithms.
Coordinated with cross-functional teams to ensure successful product launch and adoption.
Research and Planning:
Conducted extensive interviews and surveys with maintenance teams and industry experts.
Analyzed existing ordering processes to identify inefficiencies and potential improvements.
Design and Development:
Designed the user interface with a focus on ease of use and efficiency.
Trained machine learning algorithms to automate and optimize the ordering process.
Implemented robust backend systems to handle data processing and storage.
Testing and Iteration:
Conducted beta testing with select users to gather feedback and identify issues.
Iterated on the design and functionality based on user feedback and performance metrics.
Launch and Marketing:
Developed a comprehensive go-to-market strategy, including digital marketing campaigns and industry partnerships.
Organized product demonstrations and webinars to showcase the app’s capabilities to potential users.
Tools and Methods:
Tools: Python, TensorFlow, SQL, Sketch, Google Analytics
Methods: Agile Development, User-Centered Design, Lean Startup
Results and Impact:
Operational Efficiency: Reduced aircraft part ordering time by 98%, significantly minimizing aircraft downtime and operational costs.
Customer Satisfaction: Received positive feedback from users, with a 4.8/5 satisfaction rating on average.
Executive Level Recognition: Applauded by Pentagon and White House Senior Officials for initiative and innovative leadership.
Visuals:
Shawn Gregoire 