The Decision Intelligence Lab

In this episode of the Decision Intelligence Lab podcast, hosts Vijay Mehrotra and Michael Watson engage with Ben Alamar, a PhD economist and sports analytics expert. They explore the evolution of sports analytics, the impact of motion tracking technology, and the challenges of integrating data into decision-making processes in sports. Ben shares personal anecdotes about his experiences with teams, the importance of understanding risk, and the role of leadership in fostering a data-driven culture. Ben offers advice for aspiring sports analysts and concludes with recommendations for further reading.

Chapters

00:00 - Preview

1:30 - Meet Ben Alamar

3:21 - The Evolution of Sports Analytics

7:04 - Motion Tracking and Its Impact

10:03 - Translating Sports Analytics to Business

12:00 - Behavior Change and Mindset Shifts

14:40 - Risk Perception in Decision Making

19:16 - Fan Engagement and Business Objectives

20:20 - Draft Decisions: Case Studies

28:00 - Fostering Evidence-Based Culture in Sports

33:43 - Advice for Aspiring Sports Analysts

36:46 - Recommendations for Further Reading

Book Recommendations:

- "Basketball Beyond Paper" by Dean Oliver

- "Ballistic" by Henry Abbott

Check out P3 Applied Sports Science: https://www.p3.md/

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

Benjamin Alamar: ⁠https://www.linkedin.com/in/benalamar/

Connect 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

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]⁠

In this episode, Mike & Vijay sit down with Peter Cacioppi, Principal Operations Research Scientist at Decision Spot to dive into the intersection of model building and production software development. Peter shares insights on the tools he's developed, the role of Python in the Gurobi ecosystem, and the transformative impact of LLMs on software development workflows, particularly in real-time optimization. Tune in to explore the challenges and innovations in bringing production models to life.

Chapters

0:00 - Preview

1:20 - Meet Peter Caccioppi

1:47 - Integrating Computer Science in OR

7:16 - Tidy, Tested, and Safe

16:55 - The History & Utitlity of Ticdat

31:21 - GenAI's Role in OR and Software Development

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

Peter Cacioppi: ⁠https://www.linkedin.com/in/peter-cacioppi-86519210/

Connect 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

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]⁠

In this episode of the Decision Intelligence Lab podcast, host Vijay Mehrotra and co-host Michael Watson engage with Zahir Balaporia, an expert in analytics and decision-making. They explore the concepts of the 'last mile' and 'extra mile', and the politics of analytics. Zahir also shares real-world examples of how organizational dynamics can impact the success of analytics initiatives. The conversation highlights the significance of beliefs in decision-making, the necessity of building trust, and the challenges of change management in the face of evolving technologies like AI.

Chapters

0:00 - Preview

1:00 - Meet Zahir Balaporia

2:00 - The Last Mile & Extra Mile Problems in Supply Chain

7:24 - Real-World Examples of Analytics Failures

11:54 - Building Trust and Relationships in Analytics

21:25 - Cultural Dynamics in Technology Adoption

29:15 - The Future of Work with AI and Change Management

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

Zahir Balaporia: ⁠https://www.linkedin.com/in/zahirbalaporia/

Connect 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

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]⁠

In this episode of the Decision Intelligence Lab podcast, Ganesh Ramakrishna joins our hosts Vijay & Mike to share his journey from co-founding Opex Analytics to launching Lyric. He discusses the challenges of building a software company, the importance of fundraising with scaled ambitions, and the critical role of product-market fit. Ganesh emphasizes the need for an AI-first mindset in supply chain intelligence and the responsibilities that come with venture capital. He also highlights Lyric's innovative approach to solving supply chain problems through a comprehensive platform that integrates data, algorithms, and user experience.

Chapters

00:00 Introduction to Ganesh Ramakrishna

03:05 The Birth of Lyric: Vision and Challenges

06:05 Navigating the Startup Landscape: Fundraising Insights

08:59 Building a Software Company: Early Stages and Funding

12:07 Achieving Product-Market Fit: Lessons Learned

14:58 The Role of Venture Capital: Control and Responsibility

17:58 Supply Chain Challenges: Lyric's Approach

21:02 AI-First Mindset: The Future of Supply Chain Intelligence

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

Ganesh Ramakrishna: ⁠https://www.linkedin.com/in/ganeshatalk/

Connect 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

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]⁠

In this podcast episode, Michael Watson & Vijay Mehrotra interviews Harley Davis, Founder and CEO of Athena Decision Systems. They discuss the rise of generative AI and its integration with business rules, emphasizing the importance of reliable decision-making in mission-critical applications. Harley explains the limitations of LLMs, referring to them as 'stochastic parrots,' and highlights the challenges of scaling these technologies while ensuring privacy and compliance. The conversation also covers the role of RAG in enhancing LLM performance and shares real-world use cases where AI can improve administrative processes.

Chapters

0:00 - Introduction & Preview

1:19 - Meet Harley Davis & Athena Decision Systems

4:30 - Business Rules in Mission-Critical Applications

9:23 - Understanding LLMs and Their Limitations

12:05 - Integrating LLMs with Business Rules

14:12 - Challenges in Scaling LLMs and Privacy Concerns

17:34 - The Role of RAG in Enhancing LLM Performance

20:15 - Deploying LLMs in Real-World Applications

24:24 - Improving Administrative Processes with AI

27:10 - Final Thoughts and 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

Harley Davis: ⁠https://www.linkedin.com/in/harleydavis/

Athena Decision Systems: https://athenadecisions.com/

Connect 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

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]⁠

We live in a world filled where our lives and livelihoods increasingly depend on complex systems.  In this episode, Professor Laura Albert from the University of Wisconsin discusses a recent paper on the “Grand Challenges in Industrial and Systems Engineering” and offers some suggestions on how educational programs must evolve in the age of Artificial Intelligence.

Timestamps

0:00 - Preview & Introduction

3:20 - Definition & Importance of Resiliency

5:38 - The Need for Big Thinking in the Field

6:45 - Significance of case studies in bridging academia and industry needs9:00 - Rethinking educational approaches in light of GenAI advancements

11:23 - The Threat of Irrelevance for Industrial & Systems Engineering

12:55 - Challenges of Teaching with GenAI

13:55 - Lessons from COVID-19: Supply Chain Resiliency

16:32 - AI in Decision-Making and Governance

18:15 - Identifying and managing trade-offs

21:24 - Barriers to Impact in Data Science and OR Fields

23:45 - Cybersecurity as an Opportunity for Industrial and Systems Engineering & Operational Research

26:10 - The 'Equifax Breach Story'

29:10 - Laura Albert’s blog

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

Laura Albert: https://www.linkedin.com/in/lauraalbertphd

Laura's Blog: https://punkrockor.com/

Connect 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

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:

Industrial Engineering, Grand Challenges, Resiliency, Education, AI, Cybersecurity, Supply Chain, Governance, Decision-Making, Operations Research, Industrial and Systems Engineering, Operations Research, Resiliency, Complex Systems, Cybersecurity, Supply Chain, Education, Case Studies, Artificial Intelligence, Generative AI (GenAI), AI Governance, Engineering Curriculum, AI Ethics, Human-AI Teaming, Systems Thinking, Optimality, AI Audits, Workforce Training, Trade-offs, Data Science Projects, Impact Measurement, Public Outreach, Software Supply Chains, Power Systems, Digital Transformation, Decision-Making, Risk Management, Academic Blogging

In this episode’ of the Decision Intelligence Lab podcast we have 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

In the first episode of the Decision Intelligence Lab podcast, hosts Vijay Mehrotra and Michael Watson interview Dr. Irv Lustig from Princeton Consultants about the Princeton 20, a framework for identifying and mitigating AI and Optimization project risks. This evaluation framework includes both business and technical factors, and is a valuable methodology for project discovery, effective selling, and building and maintaining trust with clients.

Chapters

00:00 - Preview, & Introductions

02:20 - The Princeton Twenty Framework Overview

3:24 - How the Princeton Twenty Is Used In Practice

7:10 - Client Perspectives on Risk Management

8:27 - Overselling in Optimization and AI Projects

11:11 - Understanding the Decision Scope (Environmental Factor 5)

16:43 - Exploring Value Proposition (Environmental Factor 7)

21:45 - Process Maturity (Technical Factor 10) and Ongoing Maintenance

25:00 - Last Mile Problems in Decision Making

30:33 - Broader Impact & Risk Tolerance

35:35 - Irv'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

Irv Lustig: https://www.linkedin.com/in/irv-lustig/

Princeton 20: https://princetonoptimization.com/ai-project-management/

Connect 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

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

Princeton 20, AI deployment, optimization, risk management, decision making, data science, consulting, project success, value proposition, process maturity, decision science, project management, technical factors, sales tool, client engagement, cost benefit analysis, value proposition, decision scope, process maturity, machine learning, change management, agile methodology, human-in-the-loop optimization, black box optimization, business problem framing, analytics framework, certified analytics professional, project delivery, solution deployment, operational scheduling, strategic consulting, informs analytics.

The Decision Intelligence Lab podcast explores the practical challenges of implementing data science, analytics, and AI projects, shining a light on many diverse links in the information value chain that transform raw data into real business outcomes. 

Each episode features conversations with leaders from technology firms, consultancies, enterprise data science teams, and academia.

Hosted by Professor Michael Watson (Northwestern University) and Professor Vijay Mehrotra (University of San Francisco) — both seasoned entrepreneurs, consultants, and researchers — this podcast delivers real-world insights for data professionals, business leaders, and anyone seeking to leverage data for smarter decision-making.

Subscribe and follow to join us as we uncover how decision intelligence is reshaping the future of business and technology. You can connect with us at  [email protected]

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