Supply Chain - Unfiltered

How Procurement Teams Turn Data Into Value

24 min · 10 de jun de 2026
Portada del episodio How Procurement Teams Turn Data Into Value

Descripción

Data is quietly becoming the most negotiable asset in business and the easiest one to misuse. We sit down with Charlotte de Brabandt, Ph.D. [https://www.linkedin.com/in/dr-charlotte-anabelle-de-brabandt-digital-futurist-4492961b/], an expert in procurement, digital transformation, and AI-driven sustainability, to make sense of what it means to treat data like an economic engine rather than a pile of reports. We walk through Charlotte’s AI data economy model and the four forces it balances: 4G generative AI, 4E ethical AI, 4M monetization, and 4C democratization. From there, we get concrete about data monetization in two practical lanes. Direct monetization is selling or licensing data (often anonymized). Indirect monetization is using data to improve performance: tighter internal processes, smarter sourcing decisions, better customer experiences, and new products that are built on real behavior signals. AI is the accelerant and the risk. We dig into how AI raises data value through automation, predictive insights, and personalization, while also creating new problems like bias and unclear accountability. We also cover trends procurement and supply chain teams should watch right now, including data mesh and decentralization, AI-powered decision making, and sustainability in AI. Finally, we take on data privacy and consumer trust, the influence of GDPR and CCPA, and why transparency with vendors and stakeholders is becoming the new normal. If you want a clearer, more realistic playbook for competing in an AI-driven data economy, listen now, then subscribe, share the episode with a colleague, and leave a review.

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66 episodios

Portada del episodio How Procurement Teams Turn Data Into Value

How Procurement Teams Turn Data Into Value

Data is quietly becoming the most negotiable asset in business and the easiest one to misuse. We sit down with Charlotte de Brabandt, Ph.D. [https://www.linkedin.com/in/dr-charlotte-anabelle-de-brabandt-digital-futurist-4492961b/], an expert in procurement, digital transformation, and AI-driven sustainability, to make sense of what it means to treat data like an economic engine rather than a pile of reports. We walk through Charlotte’s AI data economy model and the four forces it balances: 4G generative AI, 4E ethical AI, 4M monetization, and 4C democratization. From there, we get concrete about data monetization in two practical lanes. Direct monetization is selling or licensing data (often anonymized). Indirect monetization is using data to improve performance: tighter internal processes, smarter sourcing decisions, better customer experiences, and new products that are built on real behavior signals. AI is the accelerant and the risk. We dig into how AI raises data value through automation, predictive insights, and personalization, while also creating new problems like bias and unclear accountability. We also cover trends procurement and supply chain teams should watch right now, including data mesh and decentralization, AI-powered decision making, and sustainability in AI. Finally, we take on data privacy and consumer trust, the influence of GDPR and CCPA, and why transparency with vendors and stakeholders is becoming the new normal. If you want a clearer, more realistic playbook for competing in an AI-driven data economy, listen now, then subscribe, share the episode with a colleague, and leave a review.

10 de jun de 202624 min
Portada del episodio Data Management Is a Dirty Job But Everyone Has to Do It

Data Management Is a Dirty Job But Everyone Has to Do It

76% of leaders say data-driven decision making is the goal, but most people still don’t trust the data they’re looking at. That contradiction is not just frustrating, it’s expensive. We talk with Susan Walsh [https://www.linkedin.com/in/susanewalsh/], founder of The Classification Guru [https://www.theclassificationguru.com/], about what actually breaks procurement data and supplier master data over time, and why “just add AI” won’t fix a messy foundation. We get practical about data quality in supply chain management: why cleaning and standardizing data gets treated like a side task, how the long tail of spend hides the biggest problems, and why tariffs and supply chain relocation make accurate, up-to-date data even more urgent for scenario modeling, forecasting, and real-time visibility. Susan also shares how to think about buying technology the smart way: start with your end goal, avoid paying for add-ons you don’t need, and choose tools that fit your specific use case instead of copying competitors. Then we dig into AI, gen AI, and agentic AI. Since every model learns from training data, bad inputs can create confident-looking misinformation and spread it across your systems. We also cover data governance basics that matter globally, like consistent units of measure, date formats, naming standards, and the people-side change management that keeps data clean after the project ends. If this conversation helps, subscribe, share it with someone wrestling with spend analytics or master data management, and leave a review so more supply chain teams can find it.

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Portada del episodio Hyper Agility

Hyper Agility

Disruption isn’t a phase you “get through” anymore. It’s the environment, and it’s forcing supply chains and organizations to evolve beyond classic agility into something bigger: hyper agility. We sit down with Dr. Charlotte de Brabandt [https://www.linkedin.com/in/dr-charlotte-anabelle-de-brabandt-digital-futurist-4492961b/] to unpack what hyper agility really means and why she sees it as a true superpower for teams that need to sense change early, respond fast, and still stay grounded in purpose.  We get specific about what makes hyper-agile organizations work: flexible structures that reconfigure around skills, communication that stays transparent across time zones, inclusive decision-making loops that move quickly without turning into bureaucracy, and rapid learning that favors short bursts of upskilling over slow programs. The thread running through it all is people. Charlotte explains why diversity isn’t optional in volatile conditions and how psychological safety turns diverse perspectives into better outcomes instead of silent disagreement.  We also explore how hyper agility reshapes talent management and workforce planning, from static roles to dynamic capability maps and from “perfect resumes” to learning agility, curiosity, and resilience. Then we connect hyper agility to innovation, technology, and measurement: empowering frontline microinnovation, using cloud tools, AI, and automation to enable collaboration, and updating KPIs to track outcomes like learning velocity, adaptability, inclusion metrics, and innovation flow. If you’re leading procurement, operations, or a cross-functional supply chain team, this conversation offers a practical way to move faster without creating chaos.  Subscribe for more, share this with a leader who needs it, and leave a review if the ideas help you rethink how your team can bend without breaking.

13 de may de 202628 min
Portada del episodio Keys to Quickturn Hiring Amid Global Supply Chain Chaos

Keys to Quickturn Hiring Amid Global Supply Chain Chaos

Scaling globally is exhilarating right up until the “how fast can we hire” question meets reality. A new client award or a winning bid can force a rapid ramp in a country where you have no entity, no local payroll, and no clear view of employment law. That’s when opportunity turns into internal panic, and the clock starts ticking on delivery dates, revenue, and credibility. We sit down with Rebecca Croucher [https://www.linkedin.com/in/rebeccacroucher/], Chief Growth Officer at Atlas, to map the real path from plan to headcount. We talk through what it takes to open a new country the traditional way, including legal entity setup timelines that can stretch from weeks to 12 to 18 months, plus the added layers of local contracts, statutory benefits, insurance requirements, pensions, and employer liability. Then we contrast that with the employer of record model and why companies use EOR services to hire quickly and stay compliant while they validate a market.  We also dig into the details that most global expansion plans miss: visa delays that can stall a build by six to nine months, cultural expectations that shape retention and day to day work, and the hard truth that there’s no single compliance tool that replaces local expertise. We close with practical planning guidance for near term market expansion, including role type, industry regulations, and how data protection typically works when teams operate inside your infrastructure.  If you found this helpful, subscribe, share the episode with a teammate planning global hiring, and leave us a review.

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Portada del episodio Future of Work and the Auspice of Emerging Markets

Future of Work and the Auspice of Emerging Markets

Trillions in new factories are coming, supply chains are shifting closer to home, and yet the biggest constraint is not equipment or real estate, it’s people. We sit down with Isaac Hagan [https://www.linkedin.com/in/isaachagen/], Senior VP of Emerging Verticals at ManpowerGroup, to unpack what “emerging talent markets” really mean right now and why they often look like familiar industries under extreme transformation: manufacturing, semiconductors, energy, automotive, and materials. We dig into industrial sovereignty, reshoring, and the new demand for predictability across both physical supply chains and talent supply chains. Isaac shares why the talent gap is becoming the defining risk for growth, what it means when millions of manufacturing roles could go unfilled, and why workforce planning has to start far earlier than most teams expect. We also talk about what actually scales: apprenticeships, skills-based hiring, reskilling in new geographies, and stronger partnerships between industry and government to build the volume of capability these investments require. Then we zoom in on AI and the future of work. Data analytics and AI fluency are rising fast, but the most in-demand skill remains collaboration and other human strengths like EQ and empathy. We also address the strain showing up in longer workdays and stressed middle managers, and why culture and development become the “trust currency” that helps organizations survive rapid change. If you work in supply chain management, procurement, manufacturing, or operations, this conversation is a practical map of where jobs are going, which skills travel, and how to stay relevant as the pace of change accelerates.  Subscribe, share this with a colleague, and leave a review with the skill you think will matter most over the next five years.

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