Javier Herrero

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…

Most systems don’t fail all at once. They slow down, back up, and quietly break when demand hits from every direction at once. What passed testing last week suddenly struggles under peak volume, overlapping processes, or hours of sustained use. This white paper challenges the idea that one type of performance test is enough. It shows how load, stress, and endurance testing work together to reveal what your system will actually do when it matters. Because confidence doesn’t come from passing a test. It comes from knowing how your system behaves under pressure. What You’ll Learn: Why performance issues slip through even when testing is in place What load testing really proves, and where it falls short How stress testing exposes breaking points before production does Why endurance testing uncovers slow failures most teams miss How to combine all three approaches into a practical, repeatable strategy What performance testing looks like across real ERP, WMS, and supply chain workflows How to move from one-time testing to continuous performance confidence If your systems only pass tests under ideal conditions, you’re still guessing. Download the white paper to see how a layered performance testing strategy helps you find issues early, fix them…