Category Archives: Blog Post

Chaos, Capacity, and the Case for Automation: Pete Blair with Pickle Robot

At MODEX 2026 in Atlanta, the energy was unmistakable. With thousands of supply chain professionals gathered, one theme echoed across conversations: uncertainty is no longer episodic. It’s constant and seemingly endless. In a candid discussion with Scott Luton, Pete Blair, VP of Product & Marketing at Pickle Robot, unpacked how organizations are navigating volatility, workforce challenges, and the growing role of automation in keeping operations moving.

Critical Mass: Inside the Coalition Building America’s Circular Supply Chain

It started over drinks, 80s music, and a shared frustration that has probably launched more good organizations than any strategic planning process ever has.

Why Track and Trace Is Essential for Modern Supply Chains

Supply chains have never been more complex or more exposed to disruption. From geopolitical instability and extreme weather to labor shortages and shifting demand, organizations are operating in a constant state of uncertainty. In this environment, basic visibility is no longer enough. Companies need the ability to monitor products in motion, understand their history, and act quickly on reliable data. That is where track and trace becomes essential.

Why Your Supply Chain Team Spends More Time in Outlook Than Your ERP

There is a dirty secret in supply chain management: the most critical information about your orders, delays, and supplier commitments doesn’t live in your ERP. It lives in email.

Are You Sure Consumers Are the Unlock for Circularity?

One of the most repeated excuses in the circular economy space is that American consumers just do not care enough. They will not sort their waste. They will not pay a premium for sustainable products. They will not participate in take-back programs. Europe is different, the story goes. Americans are a lost cause.

The Connected TMS for Shippers: One Platform for Every Mode

Learn how a connected TMS helps shippers manage every transportation mode in one workflow, respond faster to disruptions, and improve service with exception‑ready intelligence.

The Geopolitics of Junk

Here is the situation. The United States imports 95% of its critical mineral supply. Lithium, cobalt, rare earth elements, the stuff inside every battery, every semiconductor, every electric motor. We do not make it, we do not mine much of it, and we do not control the supply chain that delivers it. That is not an energy policy problem. That is a national security problem.

Anything is Possible: Josh Gruenstein on AI Workers, Throughput Pressure, and the Next Revenue Lever in Supply Chain

At Manifest 2026, Scott Luton spent time with Josh Gruenstein, Co-Founder and CEO of Tutor Intelligence, to talk about a future that’s no longer theoretical: AI-powered robot workers operating inside America’s warehouses and factories. And this isn’t a science experiment. It’s already happening.

Adapt or Be Left Behind: Jorge Morales on Technology, Personal Growth and the Human Core of Supply Chain

At Manifest 2026, Scott Luton spent time with his friend, Jorge Morales, Global Chief Operating Officer of the International Supply Chain Education Alliance (ISCEA), for a conversation that centered not on hype, but on growth.

Key Demand Sensing and Forecasting Use Cases Across Industries

Demand sensing and demand forecasting are both crucial aspects of optimizing supply chains, but they do have slightly different functions in their approach and focus. Demand sensing uses real-time data and analytics to identify and respond to immediate demand fluctuations, while demand forecasting uses historical data to predict future demand over a longer period (months or years). Different methods, such as statistical modeling and machine learning, are used to enhance the accuracy and adaptability of these processes. Both areas are crucial for companies when it comes to projecting sales, managing inventory, and coordinating replenishment. In the end, the goal is to accurately predict customer demand by using predictive models to forecast future demand.
In a world defined by rapid market shifts, volatile supply chains, and unpredictable customer behavior, traditional forecasting methods often fall short. Relying primarily on historical data is no longer enough. To stay competitive, organizations are increasingly turning to demand sensing and forecasting, an approach that blends real-time data, advanced analytics, and AI to anticipate demand more accurately and respond faster to change.