This episode’s guest is Doug Gray, Director of Data Science at Walmart Global Tech and co-author of Why Data Science Project Fail. Whether you are a business leader trying to capture value from your analytic investments, a practicing data scientist, or a student in a technical field aspiring to bring your skills to solve real world problems, this episode will provide you with valuable insights, examples, suggestions, and inspiration.

Chapters

0:00 - Preview, & Introductions

2:30 - Birth of Why Data Science Projects Fail?

4:36 - Top 5 People-Related Factors in Data Science Project Failure

13:00 - Cost and Complexity Beyond the Model

20:34 - Business User Resistance to “Black Box” Models

26:17 - Doug’s Estimate of an Optimal Failure Rate

31:20 - Organizational Maturity and Its Impact on Success

36:50 - Doug's Recommendations

Follow the show

Apple: ⁠https://podcasts.apple.com/in/podcast/the-decision-intelligence-lab/id1811085064⁠

Spotify: ⁠https://open.spotify.com/show/0lFoAVKqJHTYSZNpeN61ou?si=0ae973aab0174b3b⁠

Connect with guest

Doug Gray: https://www.linkedin.com/in/doug-gray-06bb4a4/

Books:

1. Why Data Science Projects Fail2: The Art of Data Science: A Practitioner's GuideConnect with hosts

Prof. Vijay Mehrotra (University of San Francisco): ⁠https://www.linkedin.com/in/vijay-mehrotra-ba9498/⁠

Prof. Michael Watson (Northwestern University): ⁠https://www.linkedin.com/in/michael-watson-07600a1⁠

Additional Notes:

BOOK: All in on AI

ARTICLE: "$100 of Implementation for $1 of modeling"

About the podcast

The Decision Intelligence Lab podcast delivers real-world insights for data professionals, business leaders, and anyone seeking to leverage data & AI for smarter decision-making & successful business outcomes.

For business inquiries, email at [email protected]

Keywords

Project failure, analytics, organizational maturity, change management, Doug Gray, decision science, business value, success rates, data science projects, AI implementation, analytics failure rates, organizational maturity, change management, communication challenges, project management, unrealistic expectations, technology focus, business value, key performance indicators (KPIs), stakeholder engagement, decision intelligence, model deployment, production systems, data pipelines, integration challenges, testing and validation, airline operations research, supply chain optimization, cost avoidance, AI adoption in business, center of excellence, subject matter experts, user interface design, interactive optimization, prompt engineering, business process alignment, success rates in analytics, learning from failure