The Decision Intelligence Lab

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

What happens when the optimization rules you learned no longer apply?

Dr. Tim Varelmann, Founder of Bluebird Optimization, an expert for mathematical modeling, algorithms and software development, joins Vijay Mehrotra and Michael Watson to unpack the real mechanics of combining machine learning with optimization. Not the textbook version. The practitioner version.

Dr. Tim breaks down how ML and optimization actually combine in practice — beyond just demand forecasting. Three integration patterns, the rise of primal solvers, why "start linear" is outdated advice, and a case study where simulation-based inventory optimization saved millions. Plus: maintainable optimization code, Pareto fronts for business stakeholders, and Warren Powell's policy framework.

Chapters

0:00 — Preview & Introduction

1:00 — Meet Tim Varelmann

2:50 — ML + optimization: general trends

3:50 — Three ways to combine ML and optimization

6:06 — Solver landscape evolution

9:45 — ML-optimization integration examples

13:35 — Maintainable optimization code principles

16:20 — ML integration challenges with algebraic modeling

17:30 — Downsides: nonlinearity and scaling issues

18:50 — Is "Start linear" advice still valid?

21:35 — Drift case study: inventory optimization

27:29 — Why closed-form inventory formulas fail

29:50 — Engineering the full solution, demand adjustments

32:00 — Future: Warren Powell framework, policy-based optimization

35:15 — Closing Remarks

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

Dr. Tim Varelmann: ⁠https://www.linkedin.com/in/timvarel/

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

In this episode, Vijay Mehrotra and Michael Watson sit down with Stephen Wunker, a strategy advisor for innovative leaders and Managing Director at New Markets Advisors, to explore transformative frameworks for navigating the AI era. Drawing from his book AI and the Octopus Organization—co-authored with Amazon futurist Jonathan Brill—Wunker shares actionable insights on how managers and executives can redesign their organizations for distributed decision-making, agile experimentation, and sustainable competitive advantage.

Chapters

0:00 - Preview & Introduction

1:05 - Meet Stephen Wunker

1:50 - AI and The Octopus Organization

8:21 - Centralize vs. Decentralize Decision Science

11:00 - The AI Magic Dust Problem

12:58 - Jobs-To-Be-Done Framework

16:30 - HelloFresh Case Study

20:40 - Skills for the Future

22:40 - When is Central Coordination Necessary

24:35 - Building an Experimental Muscle

26:55 - Governance & Metrics Alignment

30:05 - Figma Destroyed Adobe

31:35 - The VC Playbook

33:35 - What’s NOT Going to Happen

34:30 - Closing & Resources

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 Stephen

LinkedIn: ⁠https://www.linkedin.com/in/stephenwunker/

AI and the Octopus: https://www.newmarketsadvisors.com/books/ai-and-the-octopus-organization

Jobs to be Done: https://www.newmarketsadvisors.com/services/jobs-to-be-done-framework

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

This episode explores how organizations can successfully adopt generative AI by focusing less on tools and more on operating models, decision-making, and alignment.

Justin Trombold, President & Founder, Antesyn Advisors, shares his journey from academia to consulting and explains why most companies struggle with GenAI—not because of technology—but due to misaligned strategy, poor processes, and unrealistic expectations.

The conversation centers on a GenAI readiness framework with five dimensions:

- Strategic alignment

- Cross-functional collaboration

- End-user proficiency

- Scalability & adaptability

- Governance

Chapters

0:00 - Preview & Introduction

0:41 - Meet Justin Trombold

5:58 - Readiness Assessment Explained

7:51 - Strategic Alignment Deep Dive

10:06 - Leadership Blind Spots & Overestimating Alignment

12:49 - GenAI Strategy vs Reality

17:28 - Experimentation & Guardrails

21:00 - Real Risks (Hallucinations & Poor Inputs)

24:21 - Biggest Organizational Blind Spot

27:33 - GenAI as R&D, not IT

30:23 - Don’t Approach Vendors without Defined Problems

36:30 - Closing Thoughts

Are you ready to unlock the transformative potential of Generative AI (GenAI) for your organization? Test your organization’s GenAI Readiness at - https://www.antesynadvisors.com/blank-3

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 the guest

Justin Trombold: ⁠https://www.linkedin.com/in/trombold/

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

In this episode of the Decision Intelligence Lab Podcast, Vijay Mehrotra and Michael Watson sit down with Evan Shellshear, Principal at BCGX (BCG’s technology innovation arm) and co-author of Why Data Science Projects Fail.

Evan shares lessons from working on large-scale AI and optimization projects across industries like mining, supply chains, and retail, including a fascinating case study with Rio Tinto’s massive autonomous mining operation in Western Australia.

The conversation dives into why most AI and data science projects fail, the critical role of organizational change, and how companies can move beyond “pilot purgatory” to deliver real business value from AI.

Evan also explains BCG’s 70-20-10 rule for AI transformations, why executives should focus on value before technology, and how successful organizations redesign their operating models to fully leverage AI.

If you work in data science, AI, operations research, or digital transformation, this episode offers practical insights from real-world deployments at a global scale.

Chapters

0:00 - Preview & Introduction

0:48 - Meet Evan and BCGX's Overview

3:09 - The Scale of Rio Tinto’s Mining Operations

5:15 - Tackling Large-Scale Scheduling Problems

7:04 - The 70-20-10 Rule of AI Projects

11:30 - Combining Technical and Consulting Teams

14:28 - Proving Business Value Before Building Tools

17:36 - Escaping AI Pilot Purgatory

20:40 - Deploy, Reshape, and Invent Framework

22:45 - Balancing Speed and Transformation

25:35 - Maintaining AI Systems Long Term

28:48 - The Problem with Cheap Consulting

31:41 - Building Better Algorithms When Value Is Clear

33:44 - Retail Pricing Optimization Case Study

38:38 - Book Recommendations and Closing Thoughts

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 the guest

Evan Shellshear: ⁠https://www.linkedin.com/in/eshellshear/

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

In this episode of the Decision Intelligence Lab, hosts Vijay Mehrotra and Michael Watson sit down with Rich Savoie, CEO and co-founder of Adiona, to explore one of the toughest problems in modern logistics: last-mile delivery optimization.

Rich shares his unconventional journey from electrical engineering and medical devices to logistics technology. He discusses the intricate challenges of last-mile delivery, emphasizing how data science and AI are used to make supply chains more cost-effective and environmentally friendly. The conversation dives into the realities of building and commercializing enterprise software, navigating customer demands, and managing the trust gap with non-technical users in the logistics sector.

Beyond logistics, Rich reveals his journey from medical device engineering to startup founder, and the lessons he learned about sales, perception, cybersecurity, and enterprise-grade reliability.

Chapters

0:00 - Preview & Introduction

1:00 - Meet Rich Savoie

1:40 - Overview of Adiona

3:30 - Why the Last Mile Is So Hard

6:10 - The Optimization Stack: MIP, ML & Clustering

9:40 - Who Buys Optimization Software?

11:45 - Customer-Led Approach for Product Development

14:04 - The SaaS Dilemma of Modularization & Revenue Optimization

19:00 - Building Trust & Overcoming Resistance in Non-tech Operations Environments

21:41 - From Commute Optimization to Logistics AI

28:30 - Founder-Market Fit & Getting Real Data

34:10 - Lessons from the Medical Devices Industry

36:10 - Perception & Selling to Enterprise

38:15 - Tools, Books & Resources

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 the guest

Rich Savoie: ⁠https://www.linkedin.com/in/richsavoie/

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

In this episode of the Decision Intelligence Lab Podcast, hosts Michael Watson and Vijay welcome John Brandon Elam, Decision Systems Leader at Toyota and co-founder of Bit Bros. John shares deep, practical insights on why decision systems in large organizations often become “orphans,” how fragmented ownership across business, IT, and analytics creates risk, and what it takes to build scalable, repeatable decision-making systems. Drawing on experience at Toyota and AT&T (including work on FirstNet for first responders), the conversation explores decision ownership, incentives, change management, technical debt, and why simplicity must be earned.

This episode is a must-listen for leaders, product managers, data scientists, and anyone working at the intersection of analytics, technology, and real-world decision-making.

Chapters

0:00 - Preview

0:45 - Meet John Brandon Elam

1:55 - What are “orphaned” decision systems?

4:55 - Why decision ownership breaks down in large companies

7:28 - Who should own decision systems? The case for product ownership

10:21 - Preparing cross-functional leaders for analytics-driven decisions

15:20 - Lessons from AT&T’s FirstNet and mission-critical systems

20:05 - Adoption and change management at Toyota: “go and see”

25:01 - Trust, influence, and why being likable matters

27:01 - KISS 2.0: Keep it simple to start

30:02 - Rethinking technical debt

31:32 - Aligning incentives between operations and transformation teams

37:15 - From data to decisions: building a “Decision Factory”

39:29 - Bit Bros, books, and connect with John

40:42 - Closing remarks

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

John Brandon Elam: ⁠https://www.linkedin.com/in/johnbelam/

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at ⁠https://decisionintelligencelab.substack.com/⁠.

In this episode of the Decision Intelligence Lab podcast, hosts Vijay Mehrotra and Michael Watson welcome Linda Crowe and Benjamin Baer from DecideWise, a community focused on data, decision intelligence, and AI. The conversation explores the purpose of DecideWise and the importance of community in bridging gaps between vendors and buyers in the decision intelligence space. They discuss the challenges of implementing decision intelligence, the evolving landscape of vendors, and the significance of audibility and compliance in decision-making processes. The episode concludes with insights on the future of decision intelligence and the value of community engagement.

Chapters

0:00 - Preview & Introduction

0:46 - Meet Linda & Benjamin

3:50 - Understanding DecideWise

6:40 - Bridging Gaps in Decision Intelligence

9:49 - The Role of Community in Technology Marketing

15:25 - The Evolution of Decision Intelligence Across Industries

18:15 - Vendor Landscape & Categorization

21:56 - Common Implementation Mistakes

26:00 - Audibility, Traceability, and Risk

33:00 - Lessons Learned from Early Community Engagement

39:00 - Conclusion and Call to Action

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 the guest

Benjamin Baer: ⁠https://www.linkedin.com/in/benjaminbaer/

Linda Crowe: https://www.linkedin.com/in/llcrowe/

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]⁠

Make better business decisions with data and AI—subscribe to The Decision Intelligence Lab Newsletter at https://decisionintelligencelab.substack.com/.

In this episode, hosts Vijay Mehrotra and Michael Watson reflect on the first year of the Decision Intelligence podcast, discussing the evolution of the podcast, key themes from their guests, and insights into decision intelligence, data science, and AI. They explore the importance of trust and collaboration in decision-making processes, the role of data in shaping decisions, and the challenges of project management in data science. The conversation also touches on the future of decision intelligence and the impact of generative AI on business practices.

Chapters

0:00 Preview

Reflecting on the Journey of Decision Intelligence Podcast

3:09 The Birth of the Podcast: A Personal Story

5:52 Exploring Decision Intelligence: Insights from Guests

8:47 The Role of Data in Decision Making

11:58 Project Risks and Failures in Data Science

15:14 Testing and Implementation of Models

17:57 The Value Chain of Decision Intelligence

20:53 Innovations in AI and Decision Making

24:08 Looking Ahead: The Future of Decision Intelligence

27:03 The Importance of Trust in AI

29:57 The Role of Humans in Decision Processes

32:49 The Upcoming Book: Capturing Business Value from Decision 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 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

Mike's blog: https://miketalksai.substack.com/

Resources:

Advent of OR - https://adventofor.com

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, Dr. Lorien Pratt discusses the concept of Decision Intelligence (DI), its importance in bridging the gap between data and decision-making, and how it evolves from decision engineering. She emphasizes the need for stakeholder alignment, the role of data in decision-making, and the importance of understanding the context of decisions. The conversation also touches on the integration of various technologies and the future of DI in a rapidly changing world.

Chapters

0:00 - Preview

0:28 - Meet Dr. Lorien Pratt

1:43 - Defining Decision Intelligence

2:28 - The Gap Between Data and Decision-Making

5:05 - The Evolution from Decision Engineering to Decision Intelligence

9:28 - Integrating Operations Research with Decision Intelligence

14:14 - Pricing optimization, diffuse objectives & cross-silo interactions

16:44 - Two Meanings of “Decision”

18:55 - Incorporating Uncertainty in Decision-Making

20:54 - The Dangers of Over-Engineering Models

25:25 - Lack of a Shared Blueprint & The Need for Alignment

33:20 - Learn about Quantellia

33:55 - The Inflection Point

40:55 - Resources: DIHandbook.com & GettingStartedWithDI.com

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 the guest

Dr. Lorien Pratt: ⁠https://www.linkedin.com/in/lorienpratt/

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 special holiday episode of the Decision Intelligence Lab Podcast, Vijay welcomes back the show’s first-ever returning guests: Borja Menéndez, creator of Advent of OR, and Zohar Strinka, a lead contributor to the INFORMS Analytics Framework. Together, they explore two major initiatives released in 2024 that aim to reshape how the next generation of operations research (OR) and analytics professionals learn and practice.

Together, the guests and host dive deep into why OR is NOT just math, why curiosity is essential, how user engagement changes everything, and how practitioners learn to build systems that actually solve decision problems — not just elegant models.

Timestamps

0:00 - Preview & Intro

1:22 - What Is the Advent of OR?

3:45 - Introducing the INFORMS Analytics Framework

6:06 - OR isn't Just Math

10:10 - Skills Developed in the 2025 Advent of OR

12:10 - How Advent of OR Supports CAP Prep

14:21 - Why OR Must Teach Systems & Engineering

16:20 - The Consultant View: Building Real Systems

18:00 - Experiencing & Becoming a User Yourself

22:53 - Curiosity as a Core OR Skill

23:55 - How Borja Designs Advent of OR Challenges

26:00 - How to Learn More About the INFORMS Framework & CAP

27:22 - How to Join Advent of OR 2025

29:00 - Closing Thoughts

Follow the show

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

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

Resources Mentioned:

1. Advent of OR - Sign-up page for the annual 24-day challenge - https://adventofor.com

2. INFORMS Analytics Framework - https://www.informs.org/Professional-Development/Professional-Development-Classes/INFORMS-Analytics-Framework

3. Certified Analytics Professional (CAP) Certification - https://www.certifiedanalytics.org/

4. Decision Intelligence Lab Podcast (Substack) - https://decisionintelligencelab.substack.com

Connect with the guest

Borja Menéndez Moreno: ⁠https://www.linkedin.com/in/borjamenendezmoreno/

Zohar Strinka: https://www.linkedin.com/in/zohar-strinka/

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]⁠