Georgia Tech Supply Chain and Logistics Institute

With FIFA World Cup matches now underway in Atlanta, attention has turned from preparation to how effectively the city performs under real-world conditions.

A recent article from Hypepotamus highlights how Toronto-based Geotab is leveraging real-world telematics data from millions of vehicles to help cities better understand and plan for traffic at scale—offering an “intelligence layer” for urban decision-making.

Their analysis suggests that Atlanta’s stadium-area traffic could face challenges during match days, particularly in terms of how quickly congestion dissipates across the broader metro.

What stands out is the growing role of data-driven mobility insights in shaping how cities prepare for global events.

This is where Atlanta—and Georgia Tech—have a unique opportunity.

From transportation systems research to supply chain and logistics innovation, Georgia Tech has long been at the intersection of data, infrastructure, and real-world application. As new datasets and platforms like Geotab’s Altitude emerge, the opportunity to translate raw mobility data into actionable strategy becomes even more critical.

Major global events like the World Cup aren’t just stress tests for infrastructure—they’re living labs for collaboration across academia, industry, and public sector leaders.

🔗 Read the full article: https://buff.ly/oLk8fFA

Last-mile logistics is one of the most consequential (and least well-supported) areas of supply chain practice.

The Last-Mile IQ platform is designed to change that: a community where practitioners, researchers, and operators can ask hard questions and get answers from people who've done the work.

It's currently in beta, and the team is looking for input from professionals who know the space.

If you or your colleagues work in last-mile, we'd encourage you to register, explore what's already there, and contribute your perspective. Early participants are shaping the platform before it goes public, including the questions that will anchor the community going forward.

A few things to know:
-> Registration is open — no invitation required
->Members can view, comment, and submit new questions
->If you're interested in serving as a subject matter expert, indicate that when you sign up
->Bug reports and suggestions go directly to the team

Register at the link below, and feel free to share with colleagues whose input would strengthen the community.

We’re excited to welcome Conrad Grajczak to the Georgia Tech Supply Chain and Logistics Institute Industry Advisory Board! Conrad brings nearly 15 years of deep expertise at the intersection of procurement, supply chain logistics, and private equity value creation to the role—offering valuable perspective to support SCL's mission and future direction.

Read more: https://buff.ly/Ton9joc

Resilient supply chains bounce back from disruption.
Antifragile ones get better because of it.

That distinction sounds like a buzzword upgrade. It is not. It is a fundamentally different design philosophy.

A resilient chain absorbs a shock and recovers. An antifragile chain absorbs a shock, learns from it, and restructures so the next one hits softer.

The difference shows up in how you measure performance. Leading organizations are now tracking two metrics that didn't exist in most operations dashboards five years ago: time-to-detect (how quickly a disruption is identified) and time-to-adjust (how fast corrective action is taken after detection).

This is not an IT problem. It is an ops leadership problem.

Most teams are still measuring cost per unit and inventory turns. Both matter. Neither tells you how fast your organization sees what is coming.

We have been through four major supply chain shocks in six years: COVID, the Red Sea attacks, the tariff war, and the Middle East conflict. Each one exposed the same structural gap. Supply chains built for cost optimization in a stable world.

That world is gone.

The practitioners building antifragile operations right now are not waiting for the next crisis to redesign. They are redesigning between crises, while they have time.
What does antifragility look like in your operation? Drop one concrete example below.

Automation is accelerating. So is the gap between what's promised and what's delivered.

Half of all logistics automation projects don't hit their business case.
Not off by a little. Off by a lot, missed throughput targets, bloated costs, and in some cases, full decommissions.

The technology isn't always the problem.

The assumptions are.

Systems sized on best-case data. Hidden dependencies that become single points of failure. Technology that performs beautifully in the demo — and struggles the moment real operating conditions show up.

GT SCL is bringing together industry practitioners who have lived this (successes and failures) to dig into the root causes and what actually builds more resilient operations.
Ahead of the Curve: Lunch & Learn

📌 Why Do So Many Automation Projects Fail?
Registration link in the first comment.

94% of supply chain companies plan to deploy AI for decision support.
Only 23% have a formal strategy for doing it.

That gap is not a technology problem. It is a leadership problem.

Teams are not failing at AI because the tools are bad. They are failing because no one has defined what problem AI is actually solving, who owns the output, or how you measure whether it is working.

Gartner found that only 23% of supply chain organizations have a formal AI strategy, even among those already deploying AI. Meaning: people are running pilots, buying software, and calling it progress. But the moment the pilot ends, nothing scales.

The supply chain leaders getting real ROI from AI right now are doing three things differently.

1) They started with a decision. Not a tool. What decision are we making faster, better, or more consistently with AI?
2)They defined who owns the output. AI recommendations without a clear human accountable for acting on them go nowhere.
3) They built measurement before deployment. Not after.

This is not anti-AI. It is pro-discipline.

The hype around AI in supply chain is real. So is the graveyard of pilots that never scaled.

Which of these three gaps shows up most in your org?

Georgia Center of Innovation for Logistics May 2026 Georgia Logistics Market Snapshot. Check out the COI newsletter w/banner link to the PDF report. https://bit.ly/43MDpNy

If you have ever watched a solid recommendation die in a meeting, this is your reminder.

This Thursday, June 4 at 12:00 PM ET we are hosting:
Ahead of the Curve: Turning Analysis Into Executable Decisions

This is for teams doing serious work (models, scenarios, optimization) who still run into:

Misaligned stakeholders
Assumptions that do not survive scrutiny
Business cases that fall apart under finance or ops questions
Recommendations that are technically sound but hard to implement

If you are joining live, bring one decision you are working on right now (network, capacity, automation, footprint). You will get more out of it.

Save your seat: https://buff.ly/lApUVbg

What is the last decision your team struggled to move from insight to action, and what stopped it?