Mickey Horner

In a world of constant digital noise, marketing leaders need more than impressions—they need attention, trust, and measurable results. Supply chain podcasts have emerged as one of the most effective ways to achieve that, offering a platform to extend your reach to hard-to-access decision-makers, build authentic thought leadership, drive demand and generate qualified leads, and strengthen both brand recognition and visibility. Inside This White Paper, You’ll Learn: Why 80% of podcast listeners take action after hearing an ad—and how to leverage that to drive pipeline. How to usestorytelling to humanize your brandand create lasting audience loyalty. Proven ways podcasts canelevate brand awareness, support sales enablement, and accelerate deal cycles. Four key stepsto producing standout podcasts that deliver measurable ROI. Real-world success storiesfrom leading brands like Mattel, Colgate-Palmolive, Georgia-Pacific, and more. DOWNLOAD NOW

Special Guest Blog Post written by Matt McKinney, Co-Founder and CEO of Loop   I spend most of my time with supply chain and innovation leaders at major enterprises who are sitting on significant AI budgets but struggling to show measurable business impact in an increasingly complex and volatile supply chain environment.   These conversations have evolved dramatically. A year ago, executives were asking basic questions about AI feasibility. Today, the questions have shifted to strategic implementation at enterprise scale.   Based on hundreds of these discussions, three questions consistently emerge that separate companies making transformational progress from those stuck in pilot purgatory.   How do we move from AI experiments to enterprise-scale impact?   Most organizations have yet to see organization-wide, bottom-line impact from AI use. This is the strategic challenge keeping C-suite leaders awake at night.   The problem isn’t the technology. It’s the application of the technology. Too many enterprises are trying to treat AI like a magic wand they can bolt onto existing systems. But garbage in, garbage out. If your underlying data is fragmented and inconsistent, AI won’t solve your problems; in fact they’ll get worse.   At its core, anything automated is powered by…