In this episode of Supply Chain Optimizers, host Diego Solorzano speaks with Maria Villablanca, transformation advisor, and three-time founder, HBR Advisory Council Member, and CEO of Villablanca Consulting Ltd,  about how trade policy, AI, and regional shifts are redefining competitive advantage in supply chains. Maria shares a powerful three-question framework for cutting through crisis noise, the mindset shift needed to thrive amid disruption, and why today’s supply chain leaders must think like economists, strategists, and geopoliticians to stay ahead.

Maria Villablanca is a three-time founder and transformation advisor with 29 years of experience in global supply chain strategy and operations. She specializes in turning complex transformation plans into actionable results. She advises Fortune 500 companies and FTSE 100 leaders on operationalizing change, aligning people, technology, and processes, and managing geopolitical risk. Recognized as a Top 100 Woman in Supply Chain, Maria is also a global keynote speaker and thought leader, partnering with organizations like the World Economic Forum, Gartner, and Reuters. She is also an Advisory Council Member for Harvard Business Review.

Maria Villablanca introduces a powerful decision-making framework to help supply chain leaders navigate constant disruption. When a crisis hits, ask three questions: Does this stop customer delivery? Does it materially change your cost base? Does it harm your reputation or compliance? If not, move on. This filter helps leaders prioritize effectively, avoiding panic-driven firefighting. By separating signal from noise, whether tariffs rise 35% or shipping delays stretch by 20%, leaders can focus on structural resilience instead of reactionary fixes. Strategic calm, not chaos, drives long-term competitiveness.

Maria exposes how organizations confuse complexity with sophistication, creating inefficiencies that erode value. She highlights a common trap: procurement chasing the cheapest unit cost while ignoring logistical bottlenecks, bulk handling, or warehousing costs. These disconnected decisions cripple agility and raise expenses downstream. The solution is system-wide thinking, walking the supply chain backward from the customer to identify where complexity destroys value. Amazon exemplifies intelligent simplicity by optimizing for the customer, not departmental metrics. For leaders, true sophistication means clarity, cohesion, and speed, not needless complication that stalls performance.

Maria explains that most AI failures in supply chains stem not from technology gaps but from leadership fear. Leaders hesitate due to cost anxiety, data distrust, and perfectionism, allowing competitors using generative AI to pull ahead. She reframes the question from “When should we start?” to “What are we afraid of?” Citing Unilever’s success with AI-driven forecasting, she shows that adopting AI is about courage and cultural shift, not software. Fear of imperfection stifles innovation; those who treat AI as a transformation, not IT, will define the future.

Maria challenges the obsession with perfect data and endless planning that paralyzes supply chain transformation. Her solution: pick one problem, one champion, and one measurable outcome for a 90-day prototype. This small, focused experiment builds momentum and credibility while reducing risk. She compares it to a “Couch to 5K” journey; you don’t wait for perfect conditions, you start moving. The key is learning fast, iterating, and proving results. For modern supply chains, motion beats mastery; inaction is the real risk in today’s volatile world.

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In this episode of Supply Chain Optimizers, host Diego Solorzano speaks with Ben Taylor,  Director for Logistics at Precision for Medicine, about navigating the hidden complexity of regulated international supply chains. Drawing on over 20 years in clinical trials, hazardous materials, and military logistics across 93 countries, Ben reveals how geography, geopolitics, and cultural nuance drive decisions that no optimization model can predict. Discover why Amazon's distribution model is fundamentally different from true logistics, how to build trust across global teams, and why forethought and humor matter more than technology.

Ben Taylor is Director of Global Logistics at LabConnect and an expert in clinical trial supply chains, hazardous materials compliance, and international operations. With over two decades of experience across pharmaceutical, clinical trial, and military logistics spanning 93 countries, Ben combines geographic expertise, systems thinking, and operational discipline to navigate complex global supply chains. He previously held senior roles at Eurofins Central Laboratory and holds certifications in hazardous materials handling (CFR-49, IATA, IDMG) from his service as an Aerialport/Certified Hazardous Materials Preparer in the Air National Guard. His unique perspective bridges highly regulated medical supply chains, international business complexity, and real-world military logistics.

 

Ben Taylor reveals how clinical trial logistics require far more specialized handling than traditional pharmaceutical distribution, with unique challenges around temperature control, chain of custody, and regulatory compliance. Managing clinical trials often involves shipping small, highly sensitive materials like blood samples or lab kits that have strict viability windows, sometimes as short as 24 hours. Countries like China have such strict regulations around genetic materials that many companies opt to build local labs rather than attempt cross-border shipping. The complexity extends beyond just medical materials - even common items like bandages with antibiotics may be classified as dangerous goods in certain regions. This deep understanding of product-specific requirements and regional regulations is critical for supply chain leaders managing clinical trial operations.

When establishing safety protocols, Taylor emphasizes starting with comprehensive preparation and treating compliance as a true partnership between providers and clients. Supply chain leaders must map out detailed requirements upfront, including specialized training for handling materials like dry ice, proper storage facilities, and documentation needs. Working closely with trade compliance teams and couriers helps identify potential issues before shipments begin. This proactive approach, combined with thorough documentation of lessons learned, creates a sustainable culture of safety without sacrificing efficiency.

Taylor describes how AI has revolutionized supply chain planning by identifying optimal shipping lanes and predicting potential disruptions before they occur. The technology helps analyze massive amounts of historical data to find patterns in shipping delays, customs issues, and route efficiency. Modern AI tools can even account for factors like upcoming elections or regional events that might impact shipping timelines. For supply chain leaders, this means being able to proactively adjust routes and methods to maintain delivery commitments while optimizing costs.

Taylor makes a crucial distinction between Amazon-style distribution and true global logistics, using the analogy of "spiderwebs in a forest" to illustrate the complexity. While distribution involves moving pre-positioned inventory from nearby warehouses, global logistics requires navigating an intricate web of regulations, customs requirements, and time-sensitive handling across borders. This understanding is essential for supply chain leaders dealing with international operations, as it frames the unique challenges and necessary capabilities for success. The real-time nature of global logistics, often dealing with urgent, one-off shipments, requires far more flexibility and problem-solving than standardized distribution models.

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Join host Diego Solorzano as he welcomes Jonathan Colehower, Managing Director of Global Supply Chain Practice at UST, to unpack the realities of navigating today’s volatile trade environment. From the strategic risks of the Strait of Hormuz to opportunities in Trans-Arctic shipping routes, Jonathan shares his decades of insights and strategies on scenario planning, private trading networks, and building supply chain resilience. Listeners will discover how leading companies can move beyond prediction and develop actionable playbooks that transform disruption into competitive advantage.

Here are some of the key topics that Jonathan and Diego discuss:

Jonathan Colehower is Managing Director of the Global Supply Chain Practice at UST, where he advises global enterprises on building resilience and driving operational excellence. With leadership experience at McKinsey, Accenture, Oracle, and Manhattan Associates, he has managed P&Ls exceeding $ 100 M and sustained multimillion-dollar revenue pipelines. An expert in digital transformation, lean manufacturing, and enterprise software integration, Jonathan brings a proven track record of delivering lasting impact. He holds an MBA in Marketing and Operations from Vanderbilt University.

Jonathan introduces a contrarian approach to supply chain risk management by focusing on potential damage magnitude rather than predictability. This strategy enables companies to identify and prepare for high-impact disruptions that could significantly impact their operations, even if they seem unlikely. Using the Strait of Hormuz as an example, he demonstrates how a single chokepoint disruption could impact global energy supply and cascade across all industries. Companies should map out their most devastating potential risks and build detailed response plans for each scenario. 

Supply chain leaders need to move beyond just having backup plans to actually practicing their response playbooks regularly. Organizations must first understand their specific risks and potential business impacts, and only then develop detailed alternative strategies for each major disruption scenario. The playbook should be treated like a sports team's strategy guide, practiced repeatedly until responses become automatic. Regular simulation of disruption scenarios helps teams build muscle memory and confidence in executing backup plans. 

Advanced computing power has transformed supply chain scenario planning from overnight batch processes to real-time simulation capabilities. Today's tools allow executives to run dynamic "what-if" analyses and test multiple alternatives in seconds, enabling more agile decision-making. The shift from seeking single optimized solutions to exploring multiple scenarios reflects a more sophisticated approach to supply chain planning. Companies can now rapidly model different network configurations and disruption responses to build resilience..

Supply chain simulation tools now enable companies to build comprehensive end-to-end network models and identify critical vulnerabilities. Rather than relying on past experiences or gut feelings, organizations can use data-driven analysis to architect alternative supply chains for different disruption scenarios. Open-source optimization tools make this capability accessible to more companies, allowing them to stress-test their networks against various risks. Using real examples like port strikes or infrastructure failures, companies can develop specific contingency plans with confidence. This systematic approach to network resilience helps organizations prepare for and quickly respond to supply chain disruptions.

Jonathan shares an interesting case study of managing complexity in agricultural seed production, where multiple variables from weather to market futures affect planning. The challenge involved coordinating production across different growing seasons while dealing with unpredictable factors like pest resistance and farmer preferences. By opening additional growing seasons in South America, the company created flexibility to respond to demand spikes for successful products. Instead of relying solely on expert opinions, they leveraged the "wisdom of crowds" by gathering insights from thousands of farmers. This innovative approach to agricultural supply chain management demonstrates how combining geographical diversification with collective intelligence can solve complex planning challenges.

 

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In this episode of Supply Chain Optimizers, host Diego Solorzano speaks with Ralph Asher, founder of Data Driven Supply Chain LLC and a former Marine Corps officer, about leveraging systems thinking, decision science, and advanced analytics to tackle complex supply chain challenges. They explore how to bridge the gap between being “data rich but insight poor,” how to optimize multi-echelon inventory, and implement AI-powered strategies while balancing real-world constraints. Practical case studies and actionable insights make this episode essential for leaders seeking high-performance, future-ready supply chains.

Ralph Asher is the founder of Data Driven Supply Chain LLC and an expert in network design, supply chain analytics, and decision science. With over a decade of experience across CPG, automotive, agricultural, and restaurant industries, he combines AI, optimization, and systems thinking to tackle complex supply chain challenges. A former Marine Corps officer and adjunct instructor at the University of Saint Thomas, Asher has held key roles at General Mills and Target, helping organizations transform operations through data-driven strategies and innovative supply chain solutions.

Ralph reveals how systems thinking transforms supply chain optimization by examining interconnected trade-offs between facility locations, inventory, and transportation costs. While adding distribution centers reduces last-mile delivery costs, it increases facility and inventory expenses in a non-linear relationship that requires holistic analysis. Optimization modeling helps quantify these complex trade-offs by considering millions of variables and constraints simultaneously. Organizations must move beyond siloed metrics to understand how decisions in one area impact overall supply chain performance. Companies like Target have successfully applied this systems approach to optimize their sortation center networks, balancing local inventory positioning with efficient last-mile delivery routes.

Companies are collecting unprecedented amounts of granular supply chain data but struggling to translate it into actionable insights. While most organizations focus on descriptive analytics through dashboards, they often lack the foundational data infrastructure needed for advanced decision-making. Supply chain leaders must prioritize data management as the essential "basement" that supports more sophisticated analytics capabilities. Effective optimization requires not only raw data but also the ability to forecast demand, understand cost structures, and model complex scenarios. 

A national auto parts distributor with 100 local DCs sought to optimize its network by establishing regional DCs for slow-moving SKUs. Rather than using a simple Pareto analysis, they developed a sophisticated model that incorporated lost sales risk, bulk purchase rebates, and facility constraints. The solution provided SKU-by-unit recommendations, balancing inventory consolidation benefits against service level impacts. This real-world application demonstrates how combining network design with inventory optimization can unlock significant value. 

Successful implementation of supply chain optimization projects requires early involvement from all stakeholders before modeling begins. Organizations need dedicated project management, finance, real estate, and other functional experts aligned from the start. Without proper planning and cross-functional coordination, even the best models risk becoming "nice PowerPoint presentations" without real impact. Supply chain leaders must focus as much on execution planning as on the technical solution development. This approach ensures optimization insights translate into operational improvements rather than theoretical exercises.

 

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Trade compliance is no longer just a regulatory hurdle; it’s becoming a driver of business growth. Host Diego Solorzano speaks with Diego Montemayor, Executive Director of Trade Compliance and Supply Chain Operations at Olympus Corporation of the Americas. Together, they explore how compliance can shift from a policing role to a strategic enabler by leveraging AI, automation, and robust program frameworks while adapting to global trade dynamics and emerging geopolitical shifts.

Diego Montemayor is Executive Director of Trade Compliance and Supply Chain Operations at Olympus Corporation of the Americas. With over a decade of experience spanning Thermo Fisher, CSL, and other global firms, he specialises in sanctions, customs, export controls, logistics, and supply chain design. Educated in foreign trade and customs in Mexico, Diego combines technical expertise with a passion for solving complex regulatory challenges, building resilient supply chains, and leveraging data-driven strategies to support sustainable business growth.

Diego shares how trade compliance has evolved from being seen as the corporate police to becoming a strategic business enabler. Instead of just saying "no" to opportunities, modern trade compliance teams help companies navigate complex regulations to unlock new markets, like finding compliant ways to operate in heavily sanctioned regions. This shift requires compliance professionals to deeply understand business objectives and proactively propose solutions rather than simply enforcing rules. By positioning compliance as an enabler rather than a barrier, teams can help companies expand into new frontiers while managing risks effectively. 

Trade compliance teams are chronically understaffed yet face increasingly complex regulations, making technology adoption crucial for scaling operations. Modern tools for HS code classification, sanctions screening, and origin determination have become essential for companies operating across multiple countries. While AI shows promise in areas like custom rulings and initial classifications, human oversight remains critical for final decisions, given the high stakes of compliance errors. 

Companies are adapting to a fundamental shift in global trade dynamics, moving from US-centric to multi-polar power structures. This has led some organizations to develop separate supply chain strategies for the US markets versus the rest of the world. The rise of nearshoring in regions like Mexico faces new complications from evolving trade agreements and increased scrutiny of Chinese investments. South Asian countries are emerging as important alternative sourcing hubs as companies seek to diversify beyond China. These changes require companies to maintain flexibility in their strategic planning while working closely with compliance teams to navigate an increasingly complex regulatory environment.

The most successful global companies integrate trade compliance considerations at the earliest stages of business planning rather than treating it as an afterthought. This proactive approach helps identify potential issues before significant resources are invested, whether in new market entry, supplier selection, or product development. For example, early compliance screening can reveal if potential business partners are sanctioned, preventing costly mistakes and legal issues. By making trade compliance a key stakeholder in strategic decisions, companies can better navigate regulatory complexities while maintaining business agility.

 Episode Resources:

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Host Diego Solorzano sits down with Kyle Peacock, Principal at Peacock Tariff Consulting, to unpack the complexities of tariffs, shifting regulations, and sourcing strategies. From leveraging AI and machine learning to understanding the rise of "micro-sourcing," Kyle reveals actionable strategies that help companies balance cost savings with resilience. He also explores how regional trade blocs and CUSMA certification are reshaping the future of North American manufacturing. Whether local or global, this conversation equips leaders to navigate international trade and sourcing with confidence.

Kyle Peacock is the Principal at Peacock Tariff Consulting, where he specializes in helping businesses navigate complex trade regulations and optimize their global supply chains. With over two decades of experience in international trade, including significant tenure at industry leaders like Nestlé and Wrigley's, he brings deep expertise in tariff optimization and trade compliance. His work focuses particularly on supporting small and medium-sized enterprises in managing international trade complexities and uncovering cost savings opportunities.

Kyle reveals how the biggest impact of recent trade policies has been the element of unpredictability, with tariffs now being implemented immediately versus the previous 6-8 month notice period. Companies are struggling to react strategically, often overreacting to tweets or following crowd behavior rather than analyzing their specific situation. This uncertainty has led many businesses to halt investments and stockpile cash while they wait for clarity. The solution lies in developing company-specific strategies rather than following one-size-fits-all approaches. Smart businesses are using this challenge to become more efficient and resilient by reviewing their entire operations.

Companies are being forced to make tough decisions between maintaining product variety and ensuring profitability under tariff pressures. A fascinating example is retailers reducing their SKU count, like going from 15 to 5 product variants to minimize changeover costs and maintain margins. The decision often comes down to company values: some prioritize customer choice even at lower profits, while others focus purely on profitability. This trend is particularly visible in holiday inventory planning, where retailers are carrying fewer variants but maintaining quick-response capabilities for popular items. 

AI and machine learning are becoming critical tools for companies navigating tariff complexities and capacity constraints. The technology allows businesses to analyze massive datasets to identify efficiency opportunities that humans might miss, from optimizing batch processes to improving shift scheduling. Virtual manufacturing simulations powered by AI help companies test different scenarios without real-world risks. The impact is particularly valuable for smaller companies expanding into new markets who need to quickly scale operations. Companies embracing these tools are seeing significantly faster improvements in cost reduction and output optimization.

A major shift is occurring from single-source strategies to "micro-sourcing" networks with multiple smaller suppliers across different regions. This approach allows companies to rapidly shift production between countries in response to tariffs, transportation issues, or geopolitical tensions. The strategy requires sophisticated coordination but provides much greater supply chain resilience. Companies can maintain production even when one region faces challenges by quickly scaling up alternate suppliers.

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Host Diego Solorzano sits down with Arthur L Valdez, Jr., EVP Global Supply Chain and Customer Solutions at Starbucks. Together, they trace the evolution of global retail logistics, from Amazon’s groundbreaking fulfillment and sortation systems to Target’s transformative “stores as hubs” model. Arthur reveals lessons on balancing culture with technology, the rising role of AI, and how convenience is shaping customer expectations. He also shares leadership insights on tackling complex problems, mentoring diverse talent, and preparing supply chains for a future defined by speed, efficiency, and customer-centricity.

Arthur L Valdez, Jr. is a veteran supply chain executive with over three decades of experience transforming global retail operations. As a former Vice President of Worldwide Operations at Amazon (1999-2015) and subsequent leadership roles at Target and Starbucks, he has pioneered innovative fulfillment strategies, including Amazon's international logistics expansion and Target's stores-as-hubs model. His expertise spans from scaling early-stage e-commerce operations to revolutionizing traditional retail distribution networks. 

Arthur reveals that sortation capabilities were the critical foundation that enabled Amazon's massive growth from processing individual orders to millions of daily shipments. By mastering the art of sorting products by size, location, and order composition, Amazon could dramatically cut throughput time while maintaining the accuracy of orders. This focus on sortation efficiency led directly to their current robotic fulfillment solutions, as human-only operations couldn't scale to handle millions of units per hour. The investment in advanced sortation technology helped Amazon evolve from 4-day processing times in 1999 to 30-minute deliveries today. 

Target's breakthrough stores-as-hubs model capitalizes on having 85% of the US population within 5 miles of a store to enable same-day delivery. This local fulfillment approach allows Target to split multi-item orders across nearby stores when needed, since the short delivery distances keep costs low. The model requires balancing predictive inventory placement with flexible logistics to ensure stores maintain the right stock levels. Success depends on investing in local sortation centers and delivery networks to make this distributed fulfillment approach work efficiently. 

Arthur highlights the fundamental difference between Amazon's "technology beats culture" philosophy and Target's "culture beats technology" mindset. This distinction has shaped how each company approaches innovation and customer experience, with Amazon heavily investing in automation while Target emphasizes human connection. However, the rise of AI and growing consumer demand for convenience is forcing traditionally culture-focused retailers to increase their technology investments. Companies that don't embrace both technological efficiency and cultural strengths risk falling behind as customer expectations for speed and service continue to rise. 

At Starbucks, Arthur tackled the challenge of long wait times caused by competing service priorities between in-store, drive-through, and digital customers. The solution involved creating algorithms to properly sequence and prioritize orders across channels while maintaining service promises. This required connecting point-of-sale systems with supply chain tools to ensure proper inventory levels matched service capabilities. The experience shows how applying technology to seemingly simple operational challenges can significantly improve customer satisfaction. 

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Host Diego Solorzano sits down with Jay Koganti, VP of Supply Chain Center of Excellence at The Estée Lauder Companies, to explore how foresight, AI, and structured planning can drive meaningful transformation. From implementing the three-horizon planning framework to using AI agents for ESG challenges like scope three emissions, Jay reveals why resilience starts with preparation over prediction and asking the right questions. Jay also unpacks his supply chain playbook that blends ancient Greek wisdom with modern supply chain design. The conversation provides a practical roadmap for leaders looking to balance short-term agility with long-term impact.

Jay Koganti is Vice President of the Supply Chain Center of Excellence at The Estée Lauder Companies. With over 24 years of experience in transforming global supply chains, he specializes in strategy, planning, distribution, and digital innovation. Jay has led major initiatives across Fortune 100 firms and tier-one consulting and is passionate about efficiency, sustainability, and equity. Jay blends technology with process excellence to create next-generation supply chains. Beyond work, he explores ancient wisdom, writes on spiritual themes, and practices yoga and meditation.

Jay introduces a powerful three-horizon framework for managing supply chain transformation, focusing on short-term operations, mid-range innovation, and long-term strategic goals. This approach helps organizations balance immediate challenges with future preparation, preventing the common trap of focusing solely on current quarter results. The framework divides responsibilities among different teams, with dedicated staff handling day-to-day operations while others focus exclusively on long-term strategic planning. At Estée Lauder, implementing this model proved especially valuable during COVID-19, enabling rapid response while maintaining strategic initiatives. 

Drawing from ancient Greek history, Koganti reveals three critical principles for effectively using AI in supply chain: the importance of asking the right questions, embracing multiple possible answers, and maintaining human wisdom in interpretation. Many organizations struggle with AI implementation because they focus on getting answers rather than formulating strategic questions. The approach emphasizes that while AI can provide powerful insights, human expertise remains crucial for contextualizing and applying those insights effectively. 

Jay explains how AI agents are transforming supply chain operations by combining the intelligence of large language models with specific, rule-based actions. Supply chain organizations are seeing particular success in procurement, where AI agents automate contract management and price negotiations with unprecedented efficiency. Unlike traditional automation, these agents can handle complex decisions while maintaining strict operational parameters. 

Jay outlines how AI technology is revolutionizing the tracking and management of scope 3 emissions and the challenging task of monitoring suppliers' emissions. Traditional methods of tracking these emissions are nearly impossible due to the vast network of suppliers and sub-suppliers involved. AI agents can now automate data collection and analysis across complex supply networks, making previously unmanageable tasks feasible. This technological approach enables organizations to meet ESG mandates while maintaining operational efficiency, marking a significant advancement in sustainable supply chain management.

Jay emphasizes four non-negotiable skills for aspiring supply chain leaders: maintaining curiosity about emerging technologies, developing an outside-in perspective, understanding commercial partners, and bridging the knowing-doing gap. Many practitioners limit themselves by focusing solely on their immediate operational environment without considering broader market dynamics. Success in supply chain leadership requires not just theoretical knowledge but practical application and results orientation. These skills form the foundation for effective supply chain transformational leadership in an increasingly complex environment.

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Host Diego Solorzano sits down with Chandan Trehan, Lead of Digital Transformation, Supply Chains and Sustainability at Bosch USA, to unpack how successful supply chain innovation starts with identifying real problems before jumping into solutions. From scaling tech pilots to orchestrating human-AI collaboration, Trehan shares how data sharing, AI literacy, and control tower evolution are reshaping logistics. Learn why transformation isn't just about adopting tools, but enabling meaningful outcomes through strategic alignment. This episode offers a grounded, insightful roadmap for navigating the next wave of supply chain disruption.

Chandan Trehan is a recognized global thought leader and Digital Transformation Leader at Bosch USA, driving innovation in supply chain sustainability and emerging technologies. Named a Top 50 Thought Leader by Thinkers360, he has over a decade of experience leading large-scale digital transformations across industries. Trehan specializes in AI, blockchain, IoT, and circular economy strategies. With deep expertise in supply chain analytics, design thinking, and change management, he helps organizations unlock growth, resilience, and long-term value through strategic innovation.

Chandan Trehan emphasizes that digital transformation must begin with thorough benchmarking analysis rather than jumping straight to solutions. Supply chain leaders often make the mistake of treating symptoms instead of underlying problems, like implementing AI chatbots without questioning why vendors need so many queries answered. The key is setting specific, measurable objectives based on data - for example, reducing scrap from X% to Y%, rather than vague goals about "improving efficiency." Only after establishing clear benchmarks should teams identify bottlenecks and potential solutions through targeted pilots. Real transformation happens when organizations take time to diagnose root causes rather than chasing the latest technology trends.

Rather than getting caught up in hype cycles, Chandan advocates for "realistic pragmatism" when evaluating emerging technologies like AI. The fundamental problems supply chains face haven't changed dramatically, companies still need visibility, efficiency, and reliability, but the tools to solve them have evolved from horses to mobile apps. Organizations should focus on existing challenges rather than inventing new problems to match available solutions. The key is understanding what's realistically possible with current technology while maintaining perspective on how it fits into broader business objectives. 

Warehouses currently spend 55-60% of their time on retrieval and storage systems, presenting a massive opportunity for AI optimization. Rather than simply adding more inventory, leading organizations are using AI to predict demand patterns and optimize layout and operations. The technology enables better planning of seasonal product placement, automated retrieval through AGVs/AMRs, and predictive upstream supply chain adjustments. However, the goal isn't "dark warehouses" with zero humans, but rather intelligent orchestration between automation and human workers. This hybrid approach allows automation to handle repetitive tasks while humans focus on creative problem-solving and continuous improvement.

The next generation of supply chain leaders will need to combine systems thinking with curiosity and creative problem-solving abilities. As AI agents take over routine tasks, the human value will increasingly come from understanding complex interconnections and questioning established processes. Supply chain professionals must develop both a strategic perspective to see the big picture and tactical abilities to solve operational issues. Rather than competing with other people, they'll need to learn to work alongside and manage AI systems while focusing on tasks that require human creativity and judgment.

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Host Diego Solorzano sits down with Christopher Mejia, Director and founder of MIT’s Food and Retail Operations Lab, to explore how 50 million nanostores in emerging markets could be the key to transforming global supply chains. Learn how Mejia and his team are combining mathematical optimization, AI, and social impact to redesign food distribution networks, balance nutrition goals with logistics efficiency, and cut costs by up to 20%. This episode provides a powerful glimpse into local commerce as a catalyst for significant change.

Christopher Mejia is the Director and founder of the MIT Food and Retail Operations Lab and a leading expert in supply chain optimization, with over 15 years of experience tackling logistics challenges in emerging markets. A passionate researcher, author of Reaching 50 Million Nanostores, and advocate for data-driven policy, Mejia focuses on reducing poverty, food insecurity, and inefficiencies through applied research. His work combines mathematical modeling and social impact to create sustainable, equitable strategies for improving food distribution and retail operations in underserved regions. 

Christopher Mejia reveals that nanostores are family-owned retailers constrained by limited space and budgets, but they serve as crucial community hubs in emerging markets. These small shops, despite handling most daily consumer purchases, operate with fragmented data systems, often just notebooks for inventory tracking. The risk-averse behavior of shopkeepers, combined with their reliance on CPG manufacturers, creates unique optimization challenges for supply chains. A major complexity comes from managing perishable goods alongside regular inventory, which requires sophisticated stochastic modeling approaches. The optimization solutions must balance commercial efficiency with social impact, particularly in improving nutritional access for vulnerable populations.

The integration of multi-compartment vehicles with compatibility constraints presents a fascinating optimization challenge in nanostore logistics. In emerging markets, delivery routes must serve up to 100 stops per route, compared to just 30 in developed countries, thereby dramatically increasing computational complexity. The solution requires sophisticated methods like adaptive large neighborhood search and evolutionary algorithms to handle various product types, including dry, chilled, frozen, and humidity-controlled items. The optimization must consider not just efficiency but also nutritional value delivery to communities. 

A major Latin American company achieved an 18-20% reduction in logistics costs through the implementation of combined operations research and AI approaches. The project involved optimizing cargo combinations, routing strategies, and fleet management across national distribution networks. The key success factor was building an analytics team that could leverage both traditional OR methods and machine learning capabilities. The company's transformation from pure data-driven decisions to incorporating operations research principles showcases the power of hybrid approaches. The project's most significant impact was enabling the company to handle stochastic elements independently, leading to sustained optimization improvements.

Christopher explains that companies beginning their optimization journey should start with simple combinatorial optimization. The approach emphasizes modular development, allowing gradual complexity increase while maintaining solution clarity. Stochastic programming becomes crucial for handling real-world uncertainties like tariffs and delivery variations. The focus should remain on creating understandable and  implementable solutions rather than unnecessarily complex models. This methodical approach helps companies build lasting optimization capabilities while avoiding the trap of overcomplicated solutions that practitioners won't use.

 

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Gabriella Runnels is a Principal Data Scientist and Senior Manager of Supply Chain Science at American Eagle Outfitters, where she specializes in building algorithms to solve complex supply chain challenges. With extensive experience in AI and supply chain optimization, she leads the development of innovative solutions, including forecasting, assortment planning, and dynamic inventory management applications. At American Eagle, she has helped reduce shipments per order from 1.2 to under 1.1 and decreased average package delivery distances by approximately 100 miles by implementing advanced analytics and AI solutions.

American Eagle's four-app system (forecasting, assortment, dynamic carton routing, and transfer) works together to optimize inventory across their network. The forecasting app predicts demand by location and SKU, while the assortment app determines optimal product placement to minimize delivery costs and prevent stockouts. For new products, they use clustering algorithms to associate them with similar historical items, enabling accurate forecasting from day one. This integrated approach has helped reduce shipments per order from 1.2 to 1.1, saving millions in delivery costs. 

American Eagle's assortment app analyzes product relationships to optimize inventory placement and reduce split shipments. The system identifies items frequently purchased together, such as bikini tops and bottoms, or jeans and shorts, ensuring complementary products are stocked in the same location. This approach has reduced average shipping distance by 100 miles per package and significantly improved delivery times. The technology considers both obvious and non-obvious product relationships to maximize efficiency.

Gabriella emphasizes the importance of humility and collaboration when implementing AI solutions in supply chain operations. Rather than positioning AI as a replacement for human workers, the focus should be on creating tools that empower employees to work more effectively. Success requires understanding existing processes and KPIs from those who know them best, while avoiding jumping to AI solutions without fully understanding the problem. Building trust and relationships proves more valuable than technical expertise alone.

The key to successful supply chain optimization lies in developing a robust data infrastructure before implementing advanced AI solutions. Organizations must focus on digitalizing manual processes and capturing institutional knowledge that often exists only in employees' heads or scattered across emails and spreadsheets. Clean, well-documented data enables more effective modeling and optimization strategies. While not glamorous, this foundational work is essential for any meaningful supply chain transformation.

Supply Chain Optimizers is handcrafted by our friends over at: fame.so 

Supply Chain Optimizers is handcrafted by our friends over at: fame.so 

Supply Chain Optimizers is handcrafted by our friends over at: fame.so 

Supply Chain Optimizers is handcrafted by our friends over at: fame.so 

Supply Chain Optimizers is handcrafted by our friends over at: fame.so