Safety is usually treated as a lagging indicator where leaders only react after a claim is filed or an injury occurs. This reactive stance is a massive profit leak and an avoidable human cost that traditional safety walks can no longer manage in complex industrial environments. Vernon O'Donnell, CEO of Voxel, explains how computer vision and AI are flipping this script by identifying risks before the collision happens.

We sit down to discuss the practical application of visual AI in distribution centers and manufacturing plants across the globe. The conversation covers the reduction of workers' comp claims through ergonomic heat maps, the removal of "noise" from thousands of daily alerts, and the transition toward 90% true automation in safety monitoring. Vernon shares how Voxel identifies operational choke points—like poorly managed dock doors or incorrect forklift governors—to solve the root causes of near-misses.

The unglamorous truth of industrial technology is that many companies fear a multi-year IT nightmare that never delivers. This episode highlights a shift toward lightweight edge devices and software integrations that provide measurable value in days rather than months. You will walk away with a clear understanding of how to treat safety as a strategic lever that increases throughput and reduces employee attrition rather than just a cost center or a compliance checkbox.

Cold chain is one of those supply chain functions everyone relies on, yet few people really understand until something melts, spoils, or gets rejected at the dock. We sit down with Cindy Parker, Director of Operations at Americold, to unpack what modern cold chain logistics actually looks like and why it has shifted from “storage at temperature” into a true operations partner for food, grocery, export, and emerging pharmaceutical cold chain needs.

We get specific about what large retailers now care about most: on-time shipping, product quality, and cost discipline. Sandy explains where suppliers commonly stumble, from weak packaging that collapses over longer dwell times to late communication that forces expensive last-minute labor and space decisions. We also dig into why forecasting matters even before EDI kicks in, and why the best cold chain relationships feel like a third leg of a production facility rather than a disconnected warehouse.

From there we move into the realities of running temperature-controlled warehousing: labor and power costs, sustainability pressure to keep food out of landfill, and extreme seasonality like the holiday turkey rush that sites plan for all year. We also explore the tech wave hitting cold storage, including automated freezer facilities that keep people out of the cold, AI-supported labor planning, safety tools that flag risky lifting, and real-time inventory and temperature monitoring that customers increasingly expect. Finally, we talk traceability and FSMA 204, plus the unsexy spot where many temperature excursions happen: the trailer-to-dock transition.

If you work in supply chain, operations, retail, food safety, or logistics planning, you’ll walk away with practical ways to cut cold chain cost and reduce risk. Subscribe, share this with a teammate, and leave a review with your biggest cold chain challenge.

Retail doesn’t just use technology anymore, it runs on it, and that changes what leadership looks like at the highest level. We sit down with Vinod Bidarkoppa, Executive Vice President and Chief Technology Officer of Walmart International, to get a clear view of how modern omnichannel retail, supply chain systems, marketplace growth, and in-store operations connect through a single tech strategy.

We dig into the idea behind Walmart’s “people-led, tech-powered” purpose and what it means day to day: using technology to remove friction for customers and members while making associates’ work simpler. Vinod shares how he thinks about “invisible” tech, where the best systems fade into the background and give frontline teams the tools and confidence to serve people better.

From there, we get practical about global platform design. Vinod explains the “vehicle chassis” metaphor for building common global platforms once, then layering on what each country needs, from regulation and compliance to local customer behaviors like cash on delivery. We also talk about cross-cultural leadership, why the “what” can stay consistent while the “how” must adapt, and how Team of Teams principles like shared consciousness and empowered execution help distributed teams stay aligned across time zones.

Finally, we look at the speed of change in retail digital transformation, why transformation is intentional, and how AI in retail raises the bar on upscaling, curiosity, and learnability. If you lead teams, build products, or work anywhere in the retail value chain, you’ll walk away with frameworks you can actually use. Subscribe, share this with a colleague, and leave a review, then tell us: what’s the biggest friction point you want technology to remove next?

Supply chain leaders love to ask for “the model,” but the hardest part is figuring out what the real problem is in the first place. We sit down with Georgia Tech professor Benoit Montreuil, Executive Director of the Supply Chain and Logistics Institute, to unpack how his team works with major partners like Amazon, Home Depot, and UPS to tackle frontier logistics challenges with real data, real constraints, and real accountability. 

We walk through what deep industry-academic collaboration looks like when it’s built for long-term impact: fewer partners, stronger trust, and projects that evolve from listening and data analytics into simulation, optimization, and digital twins. Benoit explains how his lab avoids the classic trap of treating every issue like a single-method problem, why scientific rigor and publishing still matter, and how to train PhD students to operate in teams, under NDA, while delivering outcomes that decision-makers can actually use. 

We also get practical about AI in supply chain. Rather than chasing hype, we talk about generative AI as a tool for faster prototyping and experimentation, plus how to manage scope creep with an agile research program and steering committees that can pivot when mission-critical needs appear. Finally, Benoit breaks down the Physical Internet vision: hyperconnected logistics networks where warehouses and transportation capacity are shared like infrastructure, unlocking big gains in cost, resilience, service speed, and greenhouse gas emissions reduction. 

If you care about supply chain strategy, logistics innovation, sustainability, and what the next era of e-commerce fulfillment could look like, this one will stretch your thinking. Subscribe, share this with a colleague, and leave a review, then tell us: what’s the toughest supply chain question you’re facing right now?

Volatility isn’t a phase to ride out, it’s the operating system of modern logistics. We sit down with Michael Zimmerman, partner at Kearney and veteran of Fortune 500 supply chains, to unpack how structural shocks from trade policy, weather, and geopolitics have rewritten the rules of planning, sourcing, and execution. The throughline is clear: decision advantage beats tool accumulation.

We dig into layered planning that replaces single-point bets with capacity portfolios, flex clauses, and warehouse swing space. Michael shares how to define explicit triggers so teams can reconfigure within days, not weeks, and why the real breakdowns happen at cross-functional seams, order management to load planning, forecasting to capacity commitments. On the people side, we talk about preserving contextual experience, building durable playbooks, and resisting rotations that erase hard-won pattern recognition.

If you’re drowning in tech pitches, this conversation recenters the target: invest where most spend and resilience are decided, transportation sourcing, network design, capacity assurance, and supplier performance. We explore why big-bang transformations often fail and how to layer practical use cases on top of ERP, TMS, and WMS. On AI, Michael is blunt: real wins today live in decision compression, freight audit and pay, spend visibility, exception workflows, and sourcing support, while humans keep the negotiation and relationship work that sets advantage when markets tighten.

Walk away with a playbook to prepay for optionality, fix the seams, and focus your bets where they change outcomes. If you’re aiming to sense, decide, and reconfigure faster, without torching your budget, this is your roadmap to resilient, high-velocity logistics. Enjoy the episode, then subscribe, share with a colleague, and leave a quick review to help more leaders find the show.

What if your supply chain could answer hard questions in minutes instead of days? We sit down with Laurie Tuschen, Head of Customer Strategy at Optilogic, to explore how modern design stacks blend optimization, simulation, and AI to deliver faster, smarter decisions without adding new buildings or bloated spreadsheets. From the early days of mainframes to sensitivity-at-scale tools, Laurie shows how teams can test uncertainty directly and pinpoint when a decision breaks, where capacity buffers matter, and how mode shifts change the cost-to-service curve.

We walk through the practical power of a digital twin: a living model that captures facilities, flows, policies, and costs so leaders can run continuous what-ifs. When tariffs swing or lanes get disrupted, the twin helps reroute through existing assets, rebalance inventory, and protect service levels. Instead of periodic, months-long studies, cloud-native collaboration turns design into a weekly habit. Stakeholders enter data through intuitive apps, see clear scenario results, and build alignment around quantified risk, not gut feel.

AI is the accelerant, not the autopilot. Large language models make the twin queryable in plain English, while AI agents fill data gaps, profile quality, and automate scenario assembly. Humans stay firmly in the loop to judge tradeoffs and feasibility, but they spend their time on insight instead of grunt work. The payoff is real: flipping the old 80/20 so more energy goes to evaluating options, answering more project requests, and making resilient choices under cost volatility, labor constraints, and global shipping shocks.

If your team is ready to move beyond spreadsheets and embrace continuous design, this conversation maps the path; faster modeling, richer scenarios, and decisions that hold up when the world shifts. Listen, share with a colleague who owns network strategy, and leave a review with your toughest what-if we should tackle next.

Checkout isn’t a place anymore. It’s a strategy. We dive into how modern POS now spans mobile devices in the aisle, self-checkout, curbside pickup, and scan-and-go, and what that means for customer experience, associate workflows, and the bottom line. With guest Michael Leister, who helped deploy hundreds of thousands of devices across Walmart and Sam’s Club and later supported Amazon’s last mile, we unpack the operational playbook behind retail hardware and software that actually scales.

We start on the floor, not in a slide deck: observing shoppers, mapping associate tasks, and finding the gaps before drafting requirements. From there, we compare the strengths of enterprise vendors, NCR Voyix, Toshiba, Fujitsu, Diebold Nixdorf, HP, and the fresh pressure from Elo that’s pushed the market toward sleeker, modular, and configurable systems. Michael shares why mobile-first models like JCPenney’s ELO M60 transform a handheld into a dockable fixed lane, a line-busting tool, and an endless-aisle clienteling device that saves the sale when inventory is elsewhere.

ROI hides in serviceability. We break down how remote management, over-the-air updates, and AI-guided diagnostics (think on-screen self-checkout fixes and one-tap ticketing) cut downtime and truck rolls. We also look at NRF trends such as smart carts, computer vision, scan-to-add, and retrofits, along with the real hurdles of charging, shopper adoption, and defining where a transaction “closes.” Call 2025 a turning point: retailers need hardware and software that flex across kiosks, fixed lanes, mobile, and self-checkout without ripping and replacing every few years.

If you care about faster queues, higher conversion, and fewer abandoned baskets, this conversation gives you a clear path to modernize with less risk. Listen, share with your ops and tech teams, and subscribe for more pragmatic deep dives. Got a checkout pain point we should tackle next? Send it our way and leave a review to help others find the show.

What happens when a Navy nuclear power alum and finance PhD turns his focus to trucking? Sam Tibbs joins us to make a bold case: freight doesn’t have a tech problem, it has an incentive problem. He traces the unlikely route from teaching and data science to building the tools that exposed lane-level profit and drove the most-used variables in Sonar, then explains why today’s rate products miss the mark. If your pricing relies on paperwork extracted after delivery and guesses that fill in missing details, you’re driving with fogged windows.

We dig into the real bottleneck: timely, detailed data at the moment of booking. Sam argues that brokers create the signal, yet pay to buy back their own data days later, stripped of nuance like stops, hazmat, or lead time. His answer is refreshingly practical and familiar to anyone in finance: build a neutral, broker-owned data layer, much like how MasterCard aligned competing banks, where contributors are rewarded for high-quality inputs. With ownership and governance in place, the incentives flip, participation rises, and the rate product can finally show distributions that move with the market instead of stale averages.

Along the way, we contrast “great data plus a good model” with “good data plus a great model,” explore why LLMs can’t rescue missing truth, and outline where competitors should cooperate versus where they should battle. The near-term payoff is a cleaner rate signal and fewer pricing mismatches; the long-term vision is brokers turning a cost center into a profit center while shippers and carriers benefit from sharper, faster decisions. If you care about freight pricing, data quality, or building markets that actually work, this conversation maps a credible path forward.

If this resonates, follow the show, share it with a colleague, and leave a quick review so more folks in freight can find it. What's your take: should brokers own the data layer or keep buying it back?

Orders don’t move without clean data. We go deep with Jonathan Kish, SVP at Orderful, to reveal why EDI still runs global retail, where it quietly breaks omnichannel performance, and how modern teams can turn a tangle of maps and testing into a fast, reliable growth engine. From empty shelves to OTIF deductions, the symptoms are familiar; the root causes live in outdated mapping, slow retailer testing cycles, and inventory that never syncs across stores, marketplaces, and drop ship networks.

Jonathan explains how retailers standardize on EDI specs and why that foundation won’t vanish just because APIs are popular. He breaks down the documents that matter: 850s for POs, 856s for ASNs, 204/210 for freight, 810 for invoices, and 997 acknowledgments, and shows where small errors become big penalties. We explore the onboarding bottleneck that delays first purchase orders by months, plus the ripple effects on cash flow, vendor scorecards, and customer promise dates. Real case studies highlight how a single JSON-style integration and automated validations can migrate hundreds to thousands of partners in weeks, not quarters, without rewriting code per retailer.

We also look ahead. As agentic shopping grows and real-time inventory promises are made in chat, search, and social, the margin for data errors shrinks. Jonathan shares how AI-driven validation and captured testing “tribal knowledge” can compress EDI cycles from months to days, and eventually hours, while web-based EDI opens a simple path for smaller suppliers to trade without engineers or per-transaction fees. If you care about omnichannel reliability, faster vendor onboarding, and fewer chargebacks, this conversation is a practical blueprint for turning EDI from a drag into an advantage.

If this helped clarify your EDI strategy, follow the show, share it with your ops and IT teams, and leave a quick review so others can find it.

Ever wonder why a “standard” return policy can feel so unfair at the counter? We unpack the psychology and operations behind returns with Dr. Travis Tokar, Professor of Supply Chain Management at TCU, and explore how loss aversion, fairness, and frontline interactions shape customer reactions far more than a PDF policy ever will.

We walk through the five policy levers: money, exchange, time, scope, effort, and show which ones trigger loss perceptions that spark anger, and which ones customers accept when the rules are clearly justified. You’ll hear why framing a 15% fee as an “85% refund” doesn’t help, how justice theory explains real-world reactions, and why linking stricter terms to item-specific costs (like data wiping for electronics) earns legitimacy. We also compare mail-in versus store returns, highlighting where centralization saves money, when a fast shelf restock wins, and how to nudge shoppers to lower-cost channels with faster refunds, nearby drop-offs, or small incentives.

Beyond costs, we dig into what matters for loyalty: measuring more than return rates, using returnless returns strategically to boost goodwill, and training frontline teams to balance consistency with humane exceptions. Travis shares experiments, real policy patterns across retailers, and practical tests worth trying, like adaptive leniency for high-value customers and firm guardrails for serial returners. It’s a candid playbook for designing return policies that reduce friction, respect customers, and protect margins.

If this conversation gave you new ideas for your returns strategy, follow the show, share it with a teammate, and leave a quick review telling us which policy change you’ll test next.