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PM Hub Podcast Series features Product Leaders and Tech Entrepreneurs around the globe.
The Agile Data Science Playbook: Quarterly Sprints to ML Success featuring Lauren Creedon
Product Manager Hub (PM Hub)
44 minutes 26 seconds
1 year ago
The Agile Data Science Playbook: Quarterly Sprints to ML Success featuring Lauren Creedon
Summary
Summary
In this conversation, Cyrus and Lauren discuss the intersection of Agile and data science, specifically focusing on the challenges of shipping AI-enabled products quickly. They emphasize the importance of democratizing AI within organizations and the need for product managers to understand AI and ML concepts. They also discuss the prioritization of AI ML feature sets per quarter and the balance between quick wins and long-term strategic initiatives. Lauren shares her recommendations for getting buy-in and support from leadership, including listening, scenario planning, and making informed decisions.
Takeaways
Democratizing AI within organizations is crucial for enabling more people to understand and work with AI and ML.
Product managers should prioritize AI ML feature sets based on business goals and market expectations.
Balancing quick wins and long-term strategic initiatives is important for delivering outcomes and driving growth.
Getting buy-in and support from leadership requires listening, scenario planning, and making informed decisions.
Understanding the constraints and goals of different teams and stakeholders is essential for successful product management in the AI ML space.
Chapters
00:00 Introduction and Background
03:25 Challenges of Delivering Business Value Quickly
06:52 Democratizing AI within Organizations
11:05 Scoping AI/ML Feature Sets for Revenue Outcomes
14:12 Staying Up-to-Date with New Technologies
27:40 Incorporating AI into Product Strategies
28:54 Aligning Organizational Expectations and Goals
30:09 Understanding Constraints and Goals
33:10 Planning and Execution
36:04 Balancing Quick Wins and Long-Term Strategic Initiatives
