For the 36th year in a row, Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering (ISyE) has earned the No. 1 spot in the 2026 Best Engineering Schools ranking released by U.S. News & World Report.   

“My dissertation focused on maternal health in the U.S., particularly in Georgia,” Meredith said. “Women are experiencing maternal morbidity and mortality at much higher rates than in other high-income countries. There are also significant racial, ethnic, and rural-urban disparities. All of this points to systemic issues in how maternal healthcare is provided.”

Meredith’s research combined data analysis, modeling, and policy-focused tools to understand and improve access to obstetric care. A major focus was how access is measured and how to use existing resources more effectively.

“One widely used metric, ‘maternity care deserts,’ looks at access by county,” she explained. “But in Georgia, someone might be labeled as lacking care even if a hospital is just a mile across the county line. We realized that this metric was measuring the wrong thing in Georgia. Our work focuses on providing actionable insights to policymakers so they can ensure women have high-quality care nearby.”

Her research was motivated by the urgent need to address poor maternal outcomes in Georgia, which ranks among the worst states in the U.S. for both maternal mortality and racial disparities. “We see that half of women who die due to pregnancy-related causes die after delivery,” Meredith said. “Pregnancy is a critical opportunity to engage women in their healthcare, and it’s essential to focus on both maternal and fetal health.”

Meredith’s contributions aim to bridge the gap between complex operations research models and real-world healthcare decision making. “We want to take the guesswork out of policy decisions,” she said. “If a hospital closes or receives funding, our models can estimate the impact on care access and outcomes.”

Receiving the IISE award underscores the impact of Meredith’s research. “We were so focused on improving maternal health in Georgia,” she said. “This recognition shows that meaningful healthcare research can also advance the field of operations research and industrial engineering.”

Meredith credits much of her success to her advisor, Professor Lauren Steimle, who nominated her for the award and provided guidance throughout her PhD program, which she began during the height of the COVID-19 pandemic. “Her support was critical, especially during the first year and a half of online learning and isolation,” Meredith said. She also highlighted the importance of her women-led team of collaborators, including physicians and epidemiologists, working on this women-centered research.

Currently a postdoctoral researcher at NYU Langone Health, Meredith is applying her expertise to organ transplant policy, a field where operations research directly informs life-saving decisions. “Access, efficiency, and equity are still central themes,” she said. “The goal is to use powerful tools to improve care outcomes wherever they’re needed most.”

We recently wrapped our semi‑annual industry advisory board meeting, where a core element of the agenda is a set of "hot topics" sourced in advance from our member companies, curated, and facilitated to reflect what is most top of mind in the field. This cycle, one of those topics focused on the impact of AI on supply chain technology investment.

What began as a discussion on technology quickly surfaced a broader issue:

AI is not just changing supply chains—it is raising the standard for execution, and in doing so, redefining what it takes to sustain a brand.

When Capability Becomes Cheap

Within that discussion, a simple example sparked debate. Most of us would trust a platform like DocuSign without hesitation. It has earned that trust through reliability, security, and consistent performance.

But what if a new entrant—call it “FredSign”—offered similar functionality, powered by AI, at lower cost and with comparable features? Would you use it?

The room split. Some argued that established brands are durable because of the trust they have built over time. Others pushed back, suggesting that AI‑enabled challengers could close that gap faster than expected, making brand less relevant.

The discussion quickly moved beyond software to a broader question:

In a world where AI lowers the cost of building capability, does trust shift from brand to performance—or does brand become even more important?

Brand as a Promise

From a supply chain perspective, this is no longer theoretical. It is already happening.

At its core, a brand is a promise. For product companies, that promise is built on quality, consistency, and the experience of using the product over time. For supply chain technology and service providers, it is grounded in reliability, security, and confidence in execution.

Historically, brand has been reinforced by performance—but also protected by time, scale, and familiarity.

AI is changing that balance.

Lower Barriers, Higher Expectations

On one hand, AI lowers barriers to entry. New entrants can replicate functionality faster, improve user experiences, and target specific gaps in incumbent offerings.

In supply chain technology, this is particularly relevant. Many organizations have made significant, long‑term investments in systems that have not always delivered as expected. That creates an opening for AI‑enabled providers to enter through narrow use cases, solve specific problems better, and establish a foothold. Over time, they build credibility.

But there is a second dimension that is more immediate—and more consequential.

AI Raises the Execution Standard

One way to frame this is simple: data is a terrible thing to waste.

For years, supply chains have generated vast amounts of data across planning systems, transportation networks, warehouses, and customer interactions. Much of that data has been underutilized—captured, stored, but not fully leveraged to anticipate risk or improve outcomes.

That is changing.

The capability now exists—and is rapidly maturing—to sense, interpret, and act on that data in ways that were not previously practical. Risks can be identified earlier. Disruptions can be predicted. Corrective actions can be taken before the customer ever feels the impact.

From Disruption to Preventability

Over the past week, in the span of just six days and four unrelated conversations with members of my network, I heard a series of examples that all pointed to this shift.

• A global food company managing risk tied to a critical supplier whose quality issues could impact multiple major brands—raising the question of whether AI could have surfaced a near sole‑source dependency earlier.
• An e‑commerce retailer using machine learning to reduce theft and damage in its fulfillment network, improving the customer experience.
• An organization proactively shifting its fulfillment partner mix based on AI‑driven insights into which nodes can and cannot handle surge capacity.
• A high‑end clothing shipment arriving wet due to a fulfillment breakdown—where the loss was not just the product, but a time‑sensitive moment that could not be recovered.
• A consumer receiving an empty box after successfully purchasing a limited‑release product that could not be replaced.

These are not isolated anecdotes. The common thread is not disruption—it is preventability.

As AI enables earlier detection of risk, better prediction of disruptions, and faster response to exceptions, the tolerance for failure is declining. Companies are no longer judged simply on whether something went wrong. They are judged on whether it should have been avoided.

Brand Is the Delivered Experience

From a brand perspective, that is a fundamental shift.

A product brand may invest heavily in innovation and customer engagement. But if the product arrives damaged, late, or not at all, the customer does not distinguish between the brand owner and the supply chain behind it.

There is only one experience—and therefore only one brand.

In an AI‑enabled supply chain, failure is no longer just a risk—it is increasingly a choice.

The Weakest Node Defines the Brand

A brand is now only as strong as its weakest node.

That node may be a supplier, a logistics provider, a fulfillment partner, or a technology platform. Many sit outside the direct control of the brand owner, yet their performance is inseparable from the customer’s perception of the brand.

AI makes it possible to identify and address these weak points—but it also makes it more apparent when companies fail to do so.

Implications for the Supply Chain Ecosystem

This dynamic extends directly to platform and software providers. In an AI‑enabled environment, it is no longer sufficient for supply chain technology to be stable or functionally adequate. It must evolve—continuously—to sense risk earlier, enable better decisions, and improve execution outcomes. If it does not, its limitations will be exposed quickly, and alternatives will emerge.

Technology providers are not insulated by their brand; they are judged by the outcomes they enable. Their brand will strengthen if their platforms improve execution—and erode if they do not.

Product companies must use AI to protect the customer experience end‑to‑end. Logistics providers must adopt AI to remain credible partners. Technology providers must evolve their platforms to meet a higher execution standard.

If one part of the system advances while another does not, the gap will be visible—and acted upon quickly.

Winners and losers are being judged daily.

What This Means for Leaders

None of this suggests that brand is no longer important. In high‑trust, high‑risk environments—contracts, financial transactions, healthcare, and other sensitive use cases—brand remains critical.

Even in this environment, trust must be continuously reinforced through performance. Leaders must clearly understand what underpins their brand. Brand is not an asset to be protected; it is the result of consistently delivering on a promise. Any performance gaps must be addressed before others move in. AI‑enabled challengers will not challenge strengths—they will target weaknesses.

Finally, leaders must elevate their ecosystem. Brand performance is now inseparable from partner performance. That requires greater visibility, tighter integration, and higher expectations—not only internally, but across suppliers, logistics providers, and technology partners.

One Question to Answer Now

This execution dimension is only one part of how AI is reshaping brand—but it is already decisive.

A great product can still win. A strong brand can still endure. But in an AI‑driven world, where disruptions can be anticipated and failures mitigated, the margin for error is disappearing.

And in many cases—especially where the purchase is infrequent or the moment is critical—you only get one shot. At the conclusion of our discussion, one participant framed it simply:

What is our secret sauce—and what are we doing to build on it?

That is the question every supply chain leader should be answering now.

Because in an AI‑enabled world, your brand will be defined by what your system consistently delivers.

Xiaoming Huo, A. Russell Chandler III Professor in the H. Milton Stewart School of Industrial and Systems Engineering and Associate Director for Research in the Institute for Data Engineering and Science (IDEaS), served on the event’s organizing committee. He underscored the importance of collaboration in advancing responsible and effective AI tools for medicine.

“The forum provides an opportunity for collaboration and team forming. This is critical in developing AI tools for medical and health care research,” Huo said.

The keynote address was delivered by Hongtu Zhu of UNC, who presented his work on Causal Generalist Medical AI (GMAI). The model integrates multiple data sources to recommend treatments to physicians and incorporates causal reasoning to strengthen reliability. Zhu demonstrated that embedding causal elements into medical AI systems can improve generalizability by supporting evidence-based decision-making rather than relying solely on predictive outputs. He also outlined both growth opportunities and ongoing challenges that must be addressed before GMAI can serve as a robust clinical decision-support tool.

Additional presentations highlighted the range of AI applications in health care. Professor Omer Inan of Georgia Tech’s School of Electrical and Computer Engineering (ECE) shared research from his lab on AI-enabled wearable technology designed to detect heart conditions. The device he demonstrated uses a vibrometer to measure heart timing and subtle vibrations. AI algorithms then filter the signal to identify abnormalities that may indicate deeper cardiovascular concerns, signals that might otherwise go unnoticed.

Students also played a central role in the forum, presenting their research in a poster competition. One project detailed the development of a retrieval-augmented generation (RAG) model designed to answer questions about drug interactions and flag potential side effects when incompatible medications are combined. Researchers found that incorporating a RAG framework can reduce AI hallucinations, an especially critical concern in medical contexts.

Another student team explored how AI can identify candidate proteins that may aid in treating blood cancers. Using data from the Worldwide Protein Data Bank, the researchers trained AI models to predict which proteins could disrupt processes that limit the immune system’s ability to target cancer cells. Given the complexity of protein interactions, AI offers a powerful tool for identifying promising therapeutic pathways that would be difficult to isolate manually.

Across keynote talks and student presentations, BERD illustrated both the breadth and precision of AI applications in medicine. From at-home wearable diagnostics to advanced computational modeling for cancer research, presenters emphasized that AI is already delivering tangible value. At the same time, speakers noted that the field remains in its early stages, with continued collaboration and innovation essential to improving care delivery and advancing healthier outcomes.

Introduction

This year has felt like a lifetime in the Generative AI (GenAI) world. Tools, capabilities, and best practices are shifting monthly, sometimes weekly. For supply chain professionals, the message is clear: ongoing development is not optional. Like lean, analytics, or S&OP in prior decades, GenAI proficiency is quickly becoming a differentiator. The question is not if you’ll integrate GenAI into your workflow, but how quickly and effectively. 

The Evolution of GenAI in 2025

When we look back to January, it’s striking how much progress has been made in less than a year. Early in 2025, the conversation centered on agentic AI and larger models. GPT-5 and Claude 4 improved reasoning and context windows, while OpenAI introduced ChatGPT Agent in preview, able to carry out bounded multi-step tasks like retrieving files, browsing the web, and drafting structured outputs. In supply chain, this translated into early experiments with automating shipment steps or running contract reviews in a single query — tasks that were pilot-level at best in January.

By mid-year, multimodal capabilities and enterprise copilots began shifting from concept to daily use. Users could combine text, image, and voice inputs to detect defects or summarize complex documents, and copilots became embedded inside SAP, Oracle, Microsoft, and Google platforms. For the first time, GenAI wasn’t just a tool "off to the side" but something integrated directly into the systems supply chain professionals rely on.

In the second half of the year, new capabilities started layering on: memory, specialized small models, and synthetic data with digital twins. Memory allowed copilots to recall context from prior chats or S&OP cycles, reducing rework. Domain-tuned models made GenAI lighter, cheaper, and faster for logistics, procurement, and planning tasks. And digital twin integration allowed organizations to stress-test networks under disruption scenarios, from weather to labor shortages.

Enterprises also moved closer to operations with AI at the edge, using IoT data for predictive maintenance or real-time routing. At the same time, guardrails and compliance became a central topic, with more organizations creating clear "green/yellow/red" tiers for safe use. And in Q4, collaboration AI and hybrid architectures came to the forefront — copilots that can negotiate contracts in multiple languages, and architectures that blend closed and open-source models to balance sovereignty, cost, and security.

For mainstream individual users, the picture is simpler but still powerful. Anyone with ChatGPT Plus or Copilot today can take advantage of:

• Memory and custom instructions to save preferences and formats across sessions.
• Project-only memory (rolling out) to organize work by context.
• Agent previews like Operator to see how automation might work on bounded tasks.
• Connectors and file uploads to bring internal data into conversations. 

For leaders, the focus is on policy, safe pilots, and scaling. They are:

• Sponsoring agent experiments in low-risk domains (like supplier alerts).
• Embedding copilots in enterprise systems for daily planning and reporting.
• Formalizing AI use policies so employees know what’s encouraged, conditional, and off-limits.

The net result: what started in January as experimentation has, by October, become a layered landscape. Individual users now have practical tools to reclaim time, while leaders are piloting more ambitious integrations and building the governance to make adoption sustainable.

1. Action Planning is Critical

The pace of change makes a one-and-done training activity insufficient. Think of GenAI skills like fitness: it requires steady reps over time. Professionals who set quarterly development goals — experimenting with new tools, building prompt libraries, testing workflows — will not only stay current but pull ahead.

💡 Try This Quarter:

• Build a custom prompt library for routine tasks (e.g., supplier follow-ups, KPI summaries).
• Test one open-source tool such as LangChain or Haystack.
• Use AI to summarize two recent meetings and validate output with your notes. 

2. Prompt Maturity is the New Literacy

I’ve personally learned the most about prompting by asking ChatGPT to critique my style against a 12-step framework. The feedback gave me a process improvement plan I still use today. Prompt maturity isn’t abstract — it’s a measurable, improvable skill.

💡 Applied step: Rewrite one work prompt per week by climbing the ladder. 

3. Unlocking Personal Productivity

One of the fastest returns from GenAI comes from personal productivity. In our short courses this year, I’ve seen learners gain comfort and lower stress as they practice more with the tools. Many reclaimed time by using GenAI for emails, presentations, meeting notes, and data prep.

While the list of GenAI time-saving strategies is broad, some uses are already mainstream and validated by thousands of professionals. The table below organizes these strategies into categories, provides guidance on how to accomplish them, and highlights common watch-outs to ensure they deliver value without risk.

💡 Try this week: Track one workflow where AI saved time and estimate the hours reclaimed.

4. Critical Thinking: Ironically More Important than Ever

We wrote about critical thinking and added it to our curriculum after studies raised concerns about overreliance on AI. The smarter the tools become, the more important it is to validate their outputs.

💡 Applied step: Take one AI output this week and run it through the checklist — you’ll see both strengths and blind spots.

5. Advocating for Strategy and Guardrails

We’ve seen firsthand how AI policies can evolve. One major retailer shifted in less than a year from a rigid “only data scientists experiment” model to encouraging all employees to try safe versions of multiple LLMs. This shift shows why professionals should advocate for strategy and guardrails that evolve with the technology.

💡 Ask your manager: Which of our daily tasks fall into green, yellow, and red today? 

6. Agents: Early but Essential

Many industry partners are actively testing agents. Our software partners are hitting singles and doubles now, with bigger “home run” opportunities still developing. Agents aren’t fully reliable yet, but they are advancing quickly and will increasingly appear in ERP, TMS, and WMS platforms. 

In practice, most organizations today sit between Level 1 (Exploratory) and Level 2 (Task-Specific Agents), with early pilots pushing into Level 3 (Augmented Workflows). Tech-forward enterprises — particularly in retail, e-commerce, and global manufacturing — are building domain-specific agents for forecasting, procurement support, and transportation planning, often embedded inside ERP or planning platforms. These companies are experimenting with multi-agent coordination but keep humans firmly in the loop. By contrast, mainstream companies are still largely in the exploratory stage: individuals using general copilots for drafting documents or ad hoc analysis, without enterprise integration, security controls, or governance. The gap is widening — forward-leaning firms are developing playbooks for orchestrated workflows, while many organizations are just beginning to set policies and figure out where AI fits safely into their operations.

Looking ahead, Level 4 (Collaborative Automation) is where the near-term breakthroughs will happen. In the next 3–5 years, we can expect multi-agent orchestration to become a practical tool for managing recurring disruptions — think transportation rerouting during weather events or automated supplier alerts when delivery milestones are missed. Early adoption will occur in large, tech-forward enterprises with strong governance and secure infrastructure. Level 5 (Autonomous Resilience) remains aspirational: while the vision of end-to-end supply chain automation is compelling, regulatory hurdles, trust, and explainability challenges mean human oversight will remain essential. The more realistic trajectory is that enterprises will selectively automate narrow disruption scenarios while maintaining tight human control, with broader autonomy coming only as governance, standards, and trust mechanisms mature.

💡 Applied step: Identify one repetitive process in your work that could be a candidate for an agent. 

7. Human in the Loop: Non-Negotiable

Competition has improved model quality this year — but hallucinations and memory issues remain. That’s why “human in the loop” is not just a principle; it’s operational reality. AI is still an assistant, not a replacement.

💡 Applied step: Write down one checkpoint you always apply before sharing AI outputs.

Conclusion

These observations — from teaching courses, updating curriculum, and watching partners experiment — motivated this article. GenAI is evolving at extraordinary speed, and our profession must evolve with it. Build your plan, refine your prompts, reclaim time, apply critical thinking, advocate for strategy, explore agents, and always keep the human in the loop. Those who do will thrive in 2026 and beyond.

Entering 2026, one thing is clear: staying on the sidelines is no longer a viable option. We both agree that 2025 was the last year when being “behind” on AI adoption could be rationalized. In 2026, leaders cannot stay in the foxhole. They need to move forward, doing so in a way that reduces the risk of failure.

The past two years have been full of promise for AI in supply chain: we have seen impressive pilots, compelling research findings, and no shortage of claims about what agents and large language models can do. At the same time, many supply chain leaders are frustrated; there has been significant activity and investment in centralized capabilities without meaningful results in the supply chain. Too many efforts stall. Too many pilots never scale. Many organizations feel they have kissed a lot of frogs and are still waiting for something that works reliably.

The question for 2026 is no longer whether to engage with AI, but how to do so in a way that consistently delivers results. This is the year to put points on the board through disciplined, repeatable progress rather than moonshots.

Two Principles Separate Progress from Experimentation

Across our work and conversations with supply chain leaders, organizations that are driving tangible results tend to follow two principles, sometimes explicitly, sometimes intuitively:

1. Leverage GenAI Where It Adds Differential Value

Large language models are exceptionally strong at working with language. They summarize, explain, code, and translate intent into logic. This makes them powerful tools for accelerating development, analysis, and communication.

Much of supply chain execution, however, depends on precision. Planning rates, forecasts, production schedules, routing logic, and inventory policies rely on structured data, mathematical relationships, and deterministic logic. In these environments, hallucinations or probabilistic answers are not just inconvenient. They can be operationally disruptive.

Many early failures stem from applying LLMs where deterministic logic is required, rather than using them to support the creation, maintenance, and monitoring of that logic. In practice, GenAI is most effective upstream, helping teams build analytics faster, surface issues earlier, and lower the friction of development and maintenance.

2. Design with People in the Loop

This is not only a philosophical stance. It reflects technical reality. While recent research shows that collections of agents can outperform humans in controlled settings, production supply chains are not laboratories. They are complex, interconnected processes and organizations that operate in a dynamic, ever-changing environment. In contrast to AI that augments workers, fully autonomous systems introduce risks—technical, organizational, and reputational—that erode the incremental value relative to the increased costs to develop and maintain them.

Human-in-the-loop is not a concession. It is a design principle.

From Ideation to Error-Proofed Execution

Most supply chain organizations are not short on AI use cases. What they lack are clear, high‑probability paths to value creation.

A familiar pattern plays out: organizations rush into pilots without a clear view of where AI adds value. Results are mixed and hard to interpret. When early efforts disappoint, leaders become more cautious, not because they doubt AI’s potential, but because they are wary of repeating visible failures.

One executive described this dynamic as being "tired of kissing frogs." After aggressively leaning into new technologies early, the organization became skeptical, insisting on external proof and peer validation before investing further.

The more productive question is no longer "What is the most advanced thing we can try?" but instead: "What can we do today that has a high probability of working, scaling, and building our capabilities?"

How to Put Points on the Board in 2026

Across our experimentation and advisory work, two areas consistently emerge where GenAI is already delivering value.

Enterprise Productivity: The Safest On-Ramp

The most reliable progress comes from improving everyday productivity.

Most organizations take a restrictive approach, limiting AI access to a small group or tightly controlled pilots led by centralized technical teams, only to realize they were slowing learning and adoption across the enterprise. In one large retailer, leadership initially centralized AI use due to security and governance concerns. Over time, they shifted to enterprise licensing that centralized risk management while allowing broader employee access within guardrails.

The result was not chaos or "shadow IT." It was productivity: meeting summaries, analysis support, presentation development, and faster access to internal knowledge.

These gains may sound modest, but they matter. Giving people five to ten hours per week back changes how employees experience AI. It becomes a tool that helps them do their jobs better, not a signal that their jobs are being automated away.

For leaders, this means actively enabling access to approved tools, supporting skill development, and encouraging experimentation within clear boundaries. This is one of the most straightforward ways to quickly and visibly put points on the board.

Decision Intelligence: Rewiring the Operating Model

Advanced analytics, optimization, and planning systems predate GenAI. What is new is not the math, but rather the speed, accessibility, and maintainability of building and sustaining advanced analytics solutions.

GenAI acts as an accelerator. It reduces the friction of writing code, standing up, monitoring logic, and explaining results. It brings advanced capabilities closer to the business, rather than confining them to a small central team.

A concrete example comes from production planning. Planned production rates are often set during commissioning or early ramp up and then reused for long periods. Over time, changes in labor mix, maintenance practices, or product complexity cause actual throughput to drift. Plans continue to run, but they quietly degrade.

In effective implementations, GenAI does not update the planning system autonomously. Instead, it operates adjacent to it. It helps teams build monitoring logic that compares planned versus actual performance, surfaces statistically meaningful drift, and generates candidate adjustments with supporting context. Planners review and approve changes before they are re-ingested into the APS.

The system of record remains intact. Human accountability is preserved. What improves is the speed, frequency, and quality of assumption hygiene, enabling earlier detection of problems before they cascade into service, cost, or inventory issues.

Avoid Kissing Frogs: Technology and Organizational Choices

Many organizations “kiss frogs” not because the new technology is flawed, but because they are not ready to adopt it.

To avoid this fate, successful efforts often include the following elements:

1. Leverage existing, approved AI platforms rather than onboarding new technologies
   • Accelerates time to value
   • Helps define the true limitations of your current technology stack to guide future platform selection
2. Maximize the value of current systems (e.g., APS, production scheduling software) instead of chasing new applications
   • Existing, complex supply chain software often under-delivers on its promised value
   • AI agents and workflows are highly effective at improving master data quality and ensuring planning parameters are accurate
3. Foster ideation and solution development with internal teams, while using third parties to accelerate capability building—not to replace it
4. Make progress visible by sharing early wins, curating employee-driven experiments, and scaling what works

Change management is not an option; it must be designed into every aspect of an AI program from the start. When organizations invest heavily in advanced capabilities at the top while doing little to equip everyday employees, the message received is often, "This is happening to you, not for you." That perception creates resistance, fear, and organizational drag.

Effective leaders communicate a clear vision for how new capabilities will augment, not replace, their teams, so that scarce human intellect is applied where it adds the most value.

Key Actions to Win in 2026

The principles are clear. The opportunity is real. The question now is execution.

If 2026 is the year to put points on the board, supply chain leaders must move from experimentation to engineered progress. That begins with clarity.

1. Define a Multi-Year AI Value Vision

Develop a concrete view of how AI will create value in your organization over the next several years. Not a collection of pilots. Not a list of tools. A clear articulation of where and how AI will improve productivity, strengthen decision quality, and increase operational reliability.

That vision should:

• Clarify where AI will augment human decision-making versus automate tasks
• Identify the business outcomes you expect to improve (service, cost, inventory, resilience, productivity)
• Guide decisions on organizational design, platform selection, governance, and partnerships
• Establish sequencing - what you will enable now versus what must wait

Without a defined direction, AI efforts default to software deployment. With it, technology becomes a lever for measurable operational improvement.

2. Enable Broad, Responsible Access

Capability development accelerates when access is not unnecessarily constrained. Ensure that team members at every level - from executives to frontline planners - have access to approved enterprise AI tools and agent-building capabilities, along with practical training tied to real workflows.

Effective enablement includes:

• Enterprise licensing and governance that remove friction while protecting data
• Hands-on guidance tied directly to day-to-day supply chain work - reporting, master data cleanup, production monitoring, inventory analysis, schedule validation
• Clear operating guardrails that define appropriate data use and boundaries
• Leadership support for responsible experimentation

Restricting access may feel prudent. In practice, it slows learning and reinforces dependency on centralized teams. Broad enablement builds capability across the organization.

3. Create Local Ideation and Scaling Mechanisms

Durable progress does not originate only from centralized programs. It often begins at the front line.
Leaders should create simple, visible mechanisms for individuals and teams to experiment within defined guardrails and to share what they are building.

This includes:

• Recurring forums or showcases where teams present working solutions
• Curated libraries of effective prompts, workflows, and agents
• Clear channels for submitting ideas and documenting results

Most importantly, organizations must be able to move from local experimentation to scaled adoption. That requires:

• Identifying the strongest minimum viable solutions emerging from the field
• Refining and hardening them into repeatable workflows
• Productizing and scaling what demonstrably improves performance

The objective is not activity. It is building capability that compounds over time.

These steps are straightforward. They require intention and follow-through. That is what separates durable capability from scattered experimentation.

It is not too late to lead. The last several years have provided lessons - technical, organizational, and cultural. Leaders who absorb those lessons and design deliberately for scale will build AI capabilities that strengthen over time.

That kind of progress is not flashy. It does not depend on moonshots or fully autonomous systems operating in isolation. It depends on clarity, access, discipline, and accountability.

In 2026, novelty will attract attention. Durability will create an advantage.

The organizations that win will not be the ones with the most pilots. They will be the ones who consistently translate AI into measurable operational improvement.

This is the year to move from experimentation to engineered results.

Put points on the board.

Xie is one of 20 mid-career scientists, engineers, and medical professionals in the 2026–2028 cohort. Her research develops statistical and computational foundations for sequential inference, high-dimensional change-point detection, robust decision-making under uncertainty, and generative modeling for inference and decision-making, with applications in public safety, power grid resilience, and biomedical and health systems.

During her two-year term, Xie will have the opportunity to contribute to National Academies’ consensus studies and convening activities, collaborate on interdisciplinary projects, and engage with peers to address critical national and global challenges. Cohort members meet monthly in virtual sessions and gather twice annually for in-person meetings.

“I am honored to join the New Voices program and to contribute perspectives from statistics, data science, machine learning, and operations research to the National Academies’ work on AI and public decision-making,” said Xie. 

New Voices members are supported by National Academies staff and guided by an advisory committee of senior leaders. They include elected members of the National Academy of Sciences, National Academy of Engineering, and National Academy of Medicine, as well as program alumni.

With the addition of the 2026 cohort, the New Voices network now includes 80 members across four cohorts. Alumni of the program have gone on to serve on dozens of National Academies committees and to represent U.S. mid-career STEM perspectives at major national and international events.

Xie will be the third Georgia Tech faculty member to participate in New Voices. Lauren Stewart (School of Civil and Environmental Engineering) and Omar Asensio (School of Public Policy) served in previous cohorts.

“Now more than ever, we need to nurture the next generation of talented American researchers, who are the future leaders of the U.S. science and innovation enterprise,” said Marcia McNutt, president of the National Academy of Sciences.

Tech Square 3, officially named George Tower | Scheller Tower, will reach a major milestone on Monday, Jan. 12, offering the campus community access to the first three floors of the new facility.  

People often ask me a simple question: “You always recommend a good book to read; what have you read lately?”

I usually give them my version of a money-back guarantee. I haven’t had to pay up yet!

The Thinking Machine, Stephen Witt’s book on Jensen Huang and NVIDIA, is one of those recommendations.

It’s a fast, engaging read that packs a lot of insight into a book you can finish in just a couple of days. It’s also one of the most interesting books I’ve read this past year out of a stack of twenty or thirty. Most importantly for my world, it’s a book from which supply chain students, young professionals, and senior leaders can all take something different.

What many supply chain readers may not realize is that NVIDIA’s story is, at its core, a case study in supply chain design, constraint management, and long-horizon system building played out on a global stage.

This book matters to me because it pulls back the curtain on the largest technology shift impacting supply chains this century. It shows it not just as a technology story, but as a supply chain, leadership, and ethics story hiding in plain sight.

More Than a Tech Book

On the surface, this is a story about GPUs, artificial intelligence, and one of the most important technology companies in the world. But underneath, it’s really a story about context: how ideas evolve, how industries form, and how long-term decisions compound over decades.

You don’t need to be an engineer to enjoy it. By the time you’re done, you’ll have a much better grasp of:

• why chips matter,
• why AI depends on physical infrastructure,
• and why supply chains quietly shape what’s possible.

That combination makes the book especially relevant for anyone building a career in supply chain, operations, or industrial leadership.

The Immigrant Story — Still Worth Protecting

One of the most powerful threads running through the book is Jensen Huang’s immigrant story.

His family worked hard to come to the United States. He grew up in modest circumstances, and through persistence, opportunity, and relentless effort, he helped build a company with global impact.

For many of our ancestors, this story feels familiar. For many who come to the U.S. today, it still represents hope. The book serves as a quiet reminder that this pathway from modest beginnings to meaningful contribution is not accidental; it is something that needs to be protected.

The United States is far from perfect, but it remains a remarkable place to innovate and to start businesses. Supply chains are both a driver of that innovation and a beneficiary of the new ideas that emerge.

A Startup Story With Real Twists and Turns

The founding of NVIDIA is not a clean, linear success story.

The original big idea wasn’t necessarily the one that ultimately “won,” and the initial target market wasn’t always the right one. The company faced near-death moments, pivots, resets, and more than a few reasons to walk away.

For students and young professionals considering startups, whether founding one or joining one, this book offers a realistic picture of what that path looks like. It reinforces a few hard truths:

• the probability of failure is high,
• the work ethic required is enormous,
• and the rewards, if they come, often come much later.

I often describe this as a “one scoop now, two scoops later” dynamic. Early effort is rarely rewarded proportionally; patience matters more than hype.

Innovation Is a Team Sport

While Jensen Huang is clearly the centerpiece of the book, one of its strengths is that it avoids treating innovation as a solo act.

Many other players, sometimes knowingly and sometimes unwittingly, contributed research, ideas, and decisions that ultimately shaped where we sit today. The book does a good job showing how progress builds through layers of contribution, often across institutions and generations.

This matters, especially for students and early-career professionals. Breakthroughs rarely come from a single moment or a single person; they come from systems that allow ideas to accumulate and translate into real-world application.

From Basic Engineering to Neural Networks

Several chapters walk through the literal evolution of the technology, and this is where the book is both accessible and impressive.

Even if you can only “just barely hang on” technically, the narrative is clear: today’s AI capabilities are the result of layered progress. Hardware advances built on earlier hardware, software abstractions built on earlier software, and research findings translated into application over time.

Many of the contributors moved fluidly between academia and industry, reinforcing a core lesson: foundational science and engineering still matter. For those of us who remember an analog world, it’s fascinating to see how decades of incremental progress led to the current state and potential of AI.

A Supply Chain Story Hiding in Plain Sight

From a supply chain perspective, The Thinking Machine reads like a case study hiding in plain sight.

NVIDIA is an American innovation success story that is, at the same time, deeply dependent on global supply chains. Its relationship with TSMC in Taiwan, the scarcity of advanced manufacturing capacity, the national security implications of certain chips, and the need to serve global markets all create a complex and fragile operating reality.

One of the quieter but most powerful lessons in the book is how much supply chain design matters. Product success here isn’t just about better ideas; it’s about how effectively those ideas are translated into scalable, resilient, global systems.

AI may feel digital, but its limits are profoundly physical.

Leadership Results — and a Real Paradox

The book also forces an uncomfortable but important leadership conversation.

Jensen Huang is demanding, intense, and uncompromising. While the results are undeniable, I don’t advocate for many aspects of his leadership style. I believe similar outcomes could be achieved without subjecting employees to public humiliation.

Results matter, but how we get them matters too.

Reading this book reminded me that some of the most valuable leadership lessons I’ve learned came from watching both how to lead and how not to lead. I’ve had bosses who modeled the kind of leader I wanted to become, and a few who taught me just as much by showing me what I wanted to avoid. Both experiences have been valuable.

That tension is worth sitting with, especially for those mentoring the next generation of leaders.

Computer Vision, GPUs, and Adaptability

Computer vision plays a supporting role in the story: not the headline act, but an important early driver. Graphics and vision workloads helped shape GPU architectures long before today’s generative AI boom.

Over time, those architectures generalized to support a wide range of parallel computation, including neural networks. It’s a reminder that technologies often succeed not because of a single application, but because they are flexible enough to evolve.

Ethics, Uncertainty, and Responsibility

Finally, the book leaves us with unresolved questions, and that may be its most honest contribution.

AI is resource-intensive, it will reshape work and livelihoods, and it raises real ethical concerns. Opinions vary widely on whether this moment resembles past industrial revolutions or represents something fundamentally different.

I teach and advocate for the application of AI, but I personally struggle with these ethical dilemmas. Rather than avoid them, I try to address them head-on by highlighting the risks and encouraging students to stay informed so they can be voices for responsible, positive use.

In today’s global and regulatory environment, it’s unrealistic to expect a pause in research or application. Education, not avoidance, may be the most practical form of governance we have.

We can’t guarantee how this plays out over the next decade, but we can prepare.

Why I Keep Recommending This Book

If you’re a supply chain student looking for context, a young professional navigating career choices, or a senior leader trying to understand how AI, supply chains, leadership, and ethics intersect, this is a book worth your time.

It’s engaging, timely, and surprisingly human.

And when someone asks me, “What are you reading?”

This is the book I’ll keep recommending.

The Thinking Machine succeeds because it reminds us that behind AI are people, supply chains, and long-term decisions, all operating under real constraints. That’s a lesson worth revisiting as we set the pace for the months ahead.

A Closing Question

This book highlights traditional supply chain constraints that NVIDIA faced in its growth journey, such as single source supply, perceived lead times, capacity at key suppliers, demand volatility, and talent gaps. Where have you seen or faced these, and how have you and your company navigated them?

Introduction

The supply chain labor market has been through one of the most dramatic swings in modern history. During the COVID-19 era disruption, talent shortages were acute, and the pendulum swung decisively toward employees. Companies paid top dollar, offered unprecedented flexibility, and competed fiercely for planners, warehouse leaders, S&OP talent, logistics managers, strategic sourcing leaders, and procurement specialists.

But the pendulum swung back in the opposite direction, from whence it came: in favor of the employers.

The past 18–24 months have seen hiring across supply chain cooling. Many large companies are now signaling they intend to grow revenue without necessarily increasing headcount. At the same time, AI and automation have gotten to the point where employers can get more productivity from existing teams. The result is not necessarily indicative of a recessionary job market but a “Great Hiring Pause”: low hiring, low firing, and a clear tilt of bargaining power back toward employers.

The key question now is whether this moment represents a temporary pause or the new normal. Additionally, what does this mean for both hiring managers and early to mid-career supply chain professionals who want to stay competitive in the workplace?

We’ll explore what this means for all stakeholders as we wrap up the year, looking at how the supply chain job market evolved in 2025 and what we expect to see in 2026.

The Pendulum has Swung from Employee Power to Employer Advantage

If you had as little as 5 years of supply chain experience in late 2020–2022, you may have found yourself with competing job offers. Compensation packages offered were lucrative and filled with relocation fees or even 100% remote job offers.

Without a doubt, this shaped the next 2–3 years of the supply chain labor force. Office space sat empty. Employees moved out of the city into the suburbs. Work-life balance improved for everyone. Employers fretted over rents and mortgages on office space and whether their highly compensated employees were actually working. Threats of a pending recession loomed but never materialized. (fingers crossed, knock on wood). Employers ran a bit lean but then found themselves needing more people to keep up with demand.

In early 2025, we wrote about this swing and the influence AI and automation had on supply chain hiring. Companies seemed to be focusing more on how they could accelerate the performance of existing teams while navigating new cost influences and demand swings. Anxiety about the economy amid never-before-seen tariff whims made it increasingly difficult for employers to plan reliable growth strategies for 2026.

And now here we are. The prevailing mindset as we close out a volatile 2025, where AI and tariffs took center stage, is for growth without as much hiring. So what does that mean for 2026 for employers and employees, or aspiring employees?

Growth Without Hiring: Why Companies are Staying Lean Across Supply Chain and Logistics

Executives are treating hiring as a last resort and not a first resort. JP Morgan Chase’s CFO reportedly said the firm has a “strong bias” against reflexively hiring new people. Walmart, Inc. has signaled plans to grow revenue without increasing employee numbers, instead relying more on automation/AI and efficiency improvements.

As mentioned above, market indicators have become increasingly unreliable. Recent Black Friday consumer spending data indicate that people are financing their purchases on credit and using buy-now, pay-later plans. This means less cash injected into the economy in the short term, along with increased interest payments for 95% of the purchases made on Black Friday. Retailers rely heavily on consumer spending and demand, which dictate their growth or lack thereof.

Businesses have also decided to engage in what some are calling “The Great Freeze”, which is not to hire but also to not fire—holding steady on headcount until they can get a better feel for what 2026 will offer from a demand and affordability sense. High inflation affects everyone, which is why many employers are riding it out for a while.

The Risks of Going Too Lean: Burnout, Fragility, and a Shrinking Talent Pipeline

For supply chain organizations, running lean means pressure to improve throughput, reduce waste, and automate more tasks. While the rapid emergence of AI and automation has greatly improved efficiencies, you still need people to understand the best use cases for all of these tools. They can certainly be enhancements, but will backfire if they are seen to be wholesale replacements for full-time employees. This backlash is being felt and mentioned a lot more consistently. AI shouldn’t replace humans, but rather, make them superhuman.

Firms may invest in upskilling existing staff rather than hiring large numbers of junior or mid-level staff. This could help manage costs in a turbulent economy. This is a tricky game, though. Keeping headcount flat while demands increase can lead to burnout, skill gaps, or degraded service if not managed carefully. Productivity gains might be possible, but at what cost? Change management, culture shift, lack of future talent pipeline, and succession planning can place your supply chain at great risk. Think about it: What will you do about career progression, worker loyalty, and organizational capability in 5–10 years? Yes, AI and automation are force multipliers, but not force replacers.

The people who succeed are those who take a measured approach to talent decisions. It is a refrain that has been emphasized for years. Overly lean operations become fragile, just as banking talent balloons your costs. The goal is to strike a balance between the two.

Will the Pendulum Swing Again?

The short answer: not anytime soon. Today’s flat hiring environment is not just a reaction to inflation or a temporary post-COVID correction or regression to the mean. It is influenced by other structural forces like AI maturity, demographic shifts (including the aging of the workforce), productivity pressure, and a corporate mindset increasingly comfortable with “growth without headcount.”

So what now? Employees should pay attention to these moves and make themselves more valuable by staying proactive. Do not wait for a chance to improve your position. Seek it out.

Find collaborative opportunities with your peers outside of your specific silo. Cross-functional literacy takes center stage to increase one’s value. There has been career acceleration among mid-level supply chain professionals who can work across the organization and become proficient in a multitude of functions. Increase your functional knowledge base and increase your organizational value at the same time.

This is not the time to be complacent or average. Employers still need people with elite soft skills such as leadership, personnel management, communication, and initiative. Visible contributions are essential and will separate those who thrive from those who are content to endure.

There is also hope on the horizon. An elite supply chain institution recently reported that more than 85% of their spring graduates received high-level roles. Another hopeful metric is the rise in offers coming to every supply chain graduate. These numbers are all trending up, which means that the supply chain is strong and in need of a robust talent pipeline.

Employees must demonstrate they can become experienced—if not fluent—with AI tools that make individuals more productive. Use them to lift your value. Differentiation is the name of the game in a field where the top 10–15 percent of talent still commands a premium.

This was explored further in an article written for Georgia Tech this summer. AI is not the end, it is the beginning:

I firmly believe professionals—especially early in their careers—should spend 3 to 5 years in front-line roles. No AI tool can replicate the kind of intuition you build by seeing how things work, where they break, and how people respond in real time. That foundation lasts an entire career.

There will always be a place where the human edge is necessary. The goal is to find where you fit and how you can use AI to your advantage while honing and refining your soft skills. Do not be afraid to make mistakes, either. It is one of the best ways to learn.

Conclusion: Planning for Stability in an Unstable Market

The supply chain talent pendulum has clearly swung back toward employers, and the forces keeping it there are unlikely to fade any time soon. AI maturity, demographic stagnation, post-COVID overcorrections, and a corporate appetite for “growth without hiring” all point to a labor market that may remain employer-favored through 2027 or 2028. But the story does not end there. The pendulum can shift again, and it will if several conditions align: steady consumer demand, renewed business investment, lower interest rates, stable inflation, and a labor market that stays tight enough to force companies to compete for talent rather than squeeze more productivity out of smaller teams.

For employees, waiting for that moment is a recipe for disaster and is not a strategy for success. This is the time to skill up, stand out, and become visibly indispensable. Become more proficient with AI tools, expand your cross-functional range, and build the soft skills that technology cannot replace. Your competition now becomes yourself. There is no better time to be a “self-starter” than now.

For employers, running lean perpetually will not provide a bulletproof bottom line. There is risk to succession planning and employee morale through burnout and stagnation. Continue strategically building internal pipelines. The job market has plenty of talent at a premium right now, so find people who can help you maintain operations and grow into more senior roles as the economy rebounds. Workforce resilience cannot be built overnight, and organizations that fail to adequately invest now will struggle later.

“Steady-Eddie” remains the preferred path. Do not overhire or overfire. Aim for a sweet spot that maintains growth, protects margins, and creates a small cushion of resilience for the labor pool. The companies that invest smartly and the employees who stay adaptable, proactive, and highly visible have the chance to define the next era of supply chain leadership, no matter where the pendulum lands.

Call to Action: What This Means for You—and What to Do Next

If these dynamics feel familiar—or unsettling—you are not alone. Moments like this are precisely when intentional investment in skills, talent pipelines, and professional networks matters most.

For students and early-career professionals

This is the time to differentiate, not wait. Employers are hiring selectively, and they are looking for candidates who combine foundational supply chain experience with strong communication, cross-functional literacy, and practical fluency with analytics and AI-enabled tools. Georgia Tech’s Supply Chain and Logistics Institute (SCL) offers professional education courses designed to build exactly these capabilities—grounded in real-world application, not theory alone.

For working professionals

If you are navigating growth-without-hiring realities, reskilling and upskilling are no longer optional. SCL programs help professionals sharpen decision-making, leadership, and applied technical skills that increase both individual and organizational resilience—especially in environments where headcount is constrained but expectations are rising.

For hiring managers and employers

Even in a cautious hiring market, the competition for top-tier supply chain talent has not disappeared—it has become more targeted. Engaging early with Georgia Tech SCL allows you to connect with high-caliber students, support a durable talent pipeline, and partner on developing skills that align with where supply chains are headed, not where they have been.

Readers are also encouraged to explore SCM-focused podcasts and practitioner conversations—including leadership, career-path, and “day-in-the-life” perspectives—that help translate these labor market shifts into practical guidance. These voices complement formal education by offering lived experience and real-world context during periods of uncertainty.

For those wondering how to navigate what comes next, staying connected with Georgia Tech SCL can be valuable. In a January 2026 webinar, the team will preview an emerging trend expected to materially shape supply chain roles, workforce expectations, and talent strategies over the next 3–5 years—particularly at the intersection of AI enablement, front-line experience, and leadership readiness.

This moment favors those who engage early, build capability deliberately, and stay connected to credible institutions shaping the future of supply chain practice.

This content was developed in collaboration with SCM Talent Group, a supply chain recruiting and executive search firm.

Resources

• Associated Press — “US hiring stalls with employers reluctant to expand...” (reports just ~22,000 jobs in a month). AP News
• CBS News — Supporting story on same 22,000-job report / labor-market cooldown. CBS News
• PBS NewsHour — Analysis of U.S. hiring stall and its implications. PBS
• Business Insider — Coverage of weak August 2025 jobs report and growing caution in labor markets. Business Insider
• The Wall Street Journal — “Jobs Report Shows Hiring Slowed in August 2025” (subscription-gated). The Wall Street Journal
• Bloomberg — Reporting that job openings and hiring have decoupled despite rising corporate capital expenditures; signals firms are investing without matching headcount growth. Bloomberg
• Walmart / Newsweek — Recent article on Walmart celebrating automation and signaling flat headcount even as business grows. Newsweek

So, when he had the opportunity to learn more about it through the Medical Bioscience Academy at his high school, Ganesh Kumar enrolled immediately. The program exposed him to healthcare, patient systems, and the science behind clinical care. Becoming a physician seemed like the natural next step.

But by the end of his junior year, everything changed.

He had taken an AP Statistics class, and that opened his eyes to the ways data could spot patterns, strengthen decisions, and, ultimately, improve the ways that systems support people. It was a revelation — one that pushed him to think about industrial engineering, a field that merged his mathematical mindset with his determination to do something meaningful in healthcare and something that felt deeply human.

“What I love about IE is how it lets you take a systems approach to problems that affect people directly,” said Ganesh Kumar, now a fourth-year student in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE). “In healthcare, even small process improvements can make a real difference in someone’s care.” 

As he works toward that future of making a difference for people, he’s trying to make a positive impact on campus first. He’s found ways to connect his interests and his personal values: mentoring younger students, conducting research on using data to improve medical outcomes, and organizing events as president of the Georgia Tech chapter of the Institute of Industrial and Systems Engineers (IISE) professional organization.

Prior to joining One MHS, Scott was Director of Worldwide Design and Engineering for Retail Core Fulfillment/Transportation at Amazon, where he was responsible for the design and development of global supply chain capability to support business growth across Amazon's vast network. He led critical design reviews with senior executives, effectively communicating vision, technology development roadmaps, and solutions to make compelling business cases at the VP, SVP, and CEO levels. 

His expertise covers the full spectrum of Amazon's supply chain operations, including first mile facilities (transload facilities, import processing centers, and inbound cross docks), production on demand (books, disks, custom merchandise), fulfillment centers (both Amazon Robotics and traditional facilities supporting conveyable and non-conveyable products across diverse merchandise categories), air and ground transportation (ground hubs, sort centers, air hubs and air gateways), and seasonal/specialty operations (quick-deploy, returns processing, and reverse logistics). 

Since joining Amazon in 2015, Scott has been influential in technological breakthroughs in robotics and AI, enabling new opportunities to broaden the types of deployable systems by using computer vision and machine learning to unlock new capabilities. He leads the development of integrated systems-of-systems that balance process optimization and intentional automation to ensure humans and technology work together safely and efficiently. During his tenure Amazon has achieved the largest deployment of industrial robotics and mechatronics on earth.

Prior to Amazon, Scott served as Project Manager and Lead Engineer for Direct Fulfillment Supply Chain at The Home Depot from 2011 to 2014, where he developed comprehensive omni-channel supply chain architecture and was recognized as Supply Chain "Leader of the Month" for his work on e-commerce facility network design and  startup. Earlier in his career, he spent six years at Office Depot as Senior Manager for Engineering, Continuous Improvement, and Supply Chain, where he received the Global Innovation Award for implementing lean principles to achieve 57% cycle time reductions across the fulfillment network.

Scott holds both Bachelor's and Master's degrees from the Georgia Institute of Technology — a Bachelor of Science in Industrial Engineering (2004) and a Master of Science in Systems Engineering (2011). His graduate work included analyzing future cargo aircraft and automotive designs, supply chain network simulations, advanced supply chain robotics, and autonomous robotics integration with human systems.

As an Industrial and Systems Engineer with over 20 years of industry experience, Scott brings expertise in strategic business planning, logistics network analysis and design, automation and robotics, statistical modeling, continuous process improvement, and team leadership.

SCL appreciates Scott's participation and will leverage his extensive expertise in global supply chain design, automation, robotics, and systems engineering to help shape our strategic initiatives and provide valuable insights to our research and educational programs.
 

In today's supply chain environment, the pace and scale of change are no longer episodic — they are constant. Network redesigns, automation investments, digital transformation, new product and business models, shifting customer expectations, cost pressure, and talent dynamics all converge at once. 

Here is the most direct insight I can offer — and one I have come to believe deeply through experience:

“If you want your organization, automation, or Digital/AI investments to pay off, change management is not optional. It is the highest-leverage point of failure or success.”

Despite decades of innovation, the uncomfortable truth is that most large-scale supply chain transformations still fall short. According to a recent Bain survey, 70% of major transformations fail to meet their objectives — a number that has remained stubbornly consistent over time. The reasons vary, but the most common root cause is not the technology — it’s the people side of the change.

This is why change management must be treated as a leadership discipline at the center of supply chain excellence. And it is why this topic continues to rise in conversations I have with industry partners, consulting clients, and the students entering the field. 

Where I First Learned the Power of Change Leadership 

This isn’t an abstract subject for me — it is something I experienced in my career. When I worked at The Coca-Cola Company, the business went through multiple waves of transformation over a 10–15 year period: acquisitions and integrations, major information-system deployments, shifts in the beverage portfolio, and cultural changes as carbonated soft drink growth slowed.

As the company diversified into new beverage categories, the economics shifted and productivity expectations rose. The technical challenges were significant, but what stood out to me was this:

“The difference between transformations that succeeded and those that stalled was how effectively people were brought into the change — how well they understood it, aligned with it, and adapted to it.”

Strong technical designs struggled if people weren’t aligned. But “good enough” solutions thrived when the organization invested in communication, role clarity, and capability-building.

Later in my career, during my time as President of Coca-Cola Supply, we made one of the most durable leadership investments I’ve ever seen: certifying the entire organization in the Coca-Cola change model. Many of those leaders still apply the same principles today — 15 to 20 years later — because the skills became part of how they led, not something they had to remember.

That experience shaped how I see change leadership today.

What Today’s Supply Chain Landscape Is Telling Us

Across industries — and especially across complex supply chains — the same patterns repeat.

WMS and automation vendors now budget change management into implementation plans. They’ve learned that even well-designed systems fail if associates fear job loss or can’t visualize the “after” state of their work.

Consulting firms see adoption challenges as the biggest barrier to client success. A firm we taught recently added change management to their executive education curriculum because their teams saw change gaps in almost every engagement. Months later, that module remains the highest-value part of the course.

Network design firms observe cultural resistance across geographies. Even optimized solutions don’t transfer cleanly from one region to another. Culture, norms, and expectations matter — often more than the math.

Robotics and automation projects fail for people reasons, not engineering reasons. At the recent RoboGeorgia Forum, the keynote emphasized that a surprising percentage of large automation investments fail because of unclear roles, resistance, weak communication, and fear — not limitations in the technology.

AI adoption mirrors these challenges. According to a recent McKinsey Global AI survey, only one-third say they are scaling AI enterprise-wide, and just 39% report measurable EBIT impact. The survey reinforces that even when technology works, the real barrier is organizational readiness — leadership alignment, redesigned processes, clear governance, and a reskilled workforce — not model performance.

There is also strong evidence showing that when change leadership is done well, project outcomes dramatically improve. In a benchmarking study of more than 2,600 initiatives, Prosci found that 88% of projects with excellent change management met or exceeded their objectives, compared with only 13% of those with poor change management. Projects with excellent change management were also 5 times more likely to stay on or ahead of schedule and 1.5 times more likely to stay on or under budget. These findings reinforce a simple truth: effective change leadership is directly correlated with higher performance, better adoption, and faster time to value.

Put simply:

“Technical innovation moves faster than organizational adoption — and the gap costs time, money, and credibility.”

Why We Still Struggle With Change, Even Though We “Know Better”

Here's where a critical-thinking lens helps:

• We have 50 years of research on how change works.
• We have widely used models.
• We have entire consulting practices devoted to change.
• And most leaders have lived through multiple transformations.

So why does the gap persist?

Leaders confuse technical readiness with organizational readiness. A strong design doesn’t guarantee strong adoption.

Self-interest is underestimated. Logic rarely moves people. Personal impact does.

Urgency pressures force shortcuts. Go-live dates push leaders to cut corners on communication, training, and role clarity — the exact things that prevent failure.

Leaders assume operations teams “will adjust.” This is the most common miscalculation. Operational excellence does not automatically translate to change readiness.

These points explain the paradox: even experienced leaders underestimate the work of leading people through change. 

The Two Leading Change Management Models: Kotter and ADKAR

Dozens of frameworks exist, but two stand clearly above the rest in terms of use, validation, and practical effectiveness in modern supply chain and technology environments: Kotter’s 8-Step Process and the Prosci ADKAR model.

Frameworks like Kotter and ADKAR are powerful, but they don't replace judgment. Real change leadership requires applying these tools with situational awareness, not following them mechanically.

Kotter’s 8 Steps focus on organization-wide transformation:

1. Create a sense of urgency: Show why change is necessary and the potential consequences of not changing.
2. Build a guiding coalition: Assemble a team with enough power and influence to lead the change effort and encourage teamwork.
3. Form a strategic vision: Develop a clear vision for the future and strategies to achieve it, making it clear how things will be different.
4. Communicate the change vision: Widely and often communicate the vision to get buy-in and inspire action from others.
5. Empower broad-based action: Remove obstacles and barriers, such as outdated processes or resistant individuals, to enable employees to act on the vision.
6. Generate short-term wins: Plan for and celebrate early successes to build momentum and prove that progress is being made.
7. Consolidate gains and build on the change: Use the credibility from initial wins to tackle larger, more complex changes, and don't declare victory too early.
8. Anchor new approaches in the culture: Reinforce the new behaviors, processes, and practices until they become a permanent part of the organization's culture. 

ADKAR focuses on individual adoption:

• Awareness  – Of the need for change
• Desire – To Participate and support the change
• Knowledge  – On how to change
• Ability  – To implement required skills and behaviors
• Reinforcement – To sustain the change

The synthesis: 
Kotter shows leaders how to orchestrate change. 
ADKAR shows leaders how to scale it through people. 
Supply chain leaders benefit from understanding both.

What Supply Chain Leaders Can Do on Monday

A practical call to action for building your own change leadership muscle:

1. Run a 15-minute clarity check with your team.

Ask:

• What change is coming?
• Why is it happening?
• Who will feel it most?
• What might they fear losing?

2. Identify the two individuals most affected by the change.

Ask:

• What will their new day actually look like?
• What one action can support them?

3. Choose one communication habit and make it consistent.

Options include:

• A Friday “What’s coming next” email
• A weekly dashboard
• A Monday 10-minute huddle

4. Map one current project against Kotter or ADKAR.

• Pick a project already underway.
• Identify the missing step.
• Strengthen it.

5. Model the behaviors you want to see.

• Be the first adopter.
• Be transparent.
• Be steady.

A Personal Reflection (Full Circle)

Looking back at my time at Coca-Cola Supply, the decision to certify the entire organization in change leadership stands out as one of the smartest investments we made. It gave us a shared language and a shared discipline for supporting people through transformation.

Fifteen to twenty years later, I still see those leaders applying those principles instinctively. That’s what happens when change management becomes part of a leadership culture — a natural reflex, not a task.

My hope is that every supply chain professional, whether student or senior leader, will build this capability. Because:

“Technology will keep evolving. People will remain the center of every transformation.”

Final Thought: “Says Easy, Does Hard” — But Always Worth It

Supply chains do not succeed because of perfect plans or flawless systems. They succeed because the people who operate them understand the change, believe in it, and are supported through it.

This is a muscle worth building. And it’s one that lasts.

If You Need Support — We’re Here to Help

If your organization is navigating a transformation and wants support building these capabilities, please reach out to us at the Georgia Tech Supply Chain and Logistics Institute (SCL). We are actively working with companies across Georgia and beyond, sharing what we’ve learned and offering short, practical workshops on change leadership for supply chain teams. We’re always happy to help organizations strengthen this essential muscle.

The Moment That Changed How I Listen 

When I chaired the National Product Supply Group at Coca-Cola, one of our most respected board members was Jeff Edwards. Jeff had decades of experience and commanded respect without ever seeking attention. In a four-hour meeting, Jeff might speak two or three times—never more. But when he did, everyone stopped to listen.

What made Jeff so impactful wasn’t the number of words he used—it was the care behind them. He listened intently, gathered information, built context, and added value only when his perspective would move the conversation forward. His real skill was not speaking—it was listening with purpose.

That experience stayed with me, especially because earlier in my own career, I had a very different experience. While working at AJC International, I attended a leadership program at the Center for Creative Leadership. Early in the program, a cohort of about twenty of us sat in a facilitated discussion. What we didn’t know was that we were being filmed.

Later that day, each of us reviewed our videos one-on-one with an instructor. Watching myself was humbling. I saw a young professional trying too hard to prove himself—talking far too much, jumping in before others, and dominating the conversation. It was uncomfortable to watch, but invaluable. It forced me to face how insecurity can manifest as over-talking and how much more powerful restraint and self-awareness can be. I’ve been on a "less is more" journey ever since.

Why Communication Is a Supply Chain Differentiator 

We often talk about supply chain as end-to-end, but that phrase means something deeper than process visibility—it implies constant collaboration. Supply chain professionals must connect with suppliers, customers, and internal stakeholders across every function. 

That means communication is the connective tissue of our profession.

• Upstream and downstream, we are translators—interpreting complex data, system logic, and network realities for people who make decisions.
• Inside organizations, we act as bridges between technical teams and commercial leaders.
• Across tiers, we negotiate, influence, and build trust with partners who don’t see what we see every day.

Even as automation expands, supply chains remain messy, human, and physical. Systems can handle the routine, but edge cases, disruptions, and exceptions still rely on judgment—and judgment relies on communication. The ability to see, listen, and convey context in real time is what keeps operations resilient when variability strikes.

In our earlier SCL articles, we wrote that skills that survive AI are the ones that emphasize human discernment—and that critical thinking is about interpreting and questioning rather than accepting data at face value. Communication is where these two intersect. It is how human understanding flows across the supply chain network.

When Communication Breaks Down

I once worked with a technically gifted colleague—let’s call him Forrest—who had deep analytical capability but struggled to speak up in group settings. His insights were sharp, but his inability to communicate them left him isolated. Eventually, he left the organization. It was a tough reminder that technical strength without communication is unrealized potential.

In a global supply chain, it’s not enough to know the answer. You have to make others understand why it’s the answer—and what to do with it. Communication is how insight becomes action. 

The Many Dimensions of Communication

We tend to equate communication with speaking, but it’s much broader. Great communicators master four dimensions:

1. Speaking – Conveying information clearly, concisely, and confidently.
2. Writing – Capturing ideas and decisions in a way that travels across teams and time zones.
3. Listening – Absorbing context before contributing, and letting others be heard.
4. Observing – Seeing what others miss and using that insight to guide action.

The fourth one—observing—is often overlooked.

Recently, while reading with my granddaughter, she picked out a children’s book titled Bud Finds Her Gift. It’s about discovering one's special ability, and Bud's gift turned out to be observation—simply noticing things others missed. Watching her read that story reminded me how powerful observation really is.

I thought of my former colleague, Tim Harville, with whom I worked at Coregistics. Tim often walked the warehouse with new supervisors, teaching them to "see the operation"—to notice what looks good, what's out of place, and where waste or opportunity hides in plain sight. His goal wasn't to test them—it was to train their eyes. Observation, in that sense, is a key communication skill. You can't describe, explain, or improve what you haven't first seen clearly. 

Can Communication Be Taught? Absolutely.

I’ve seen it done.

At Frito-Lay, we invested in communication training for new managers—everything from eliminating filler words to using purposeful body language and structuring messages with intent. At Coca-Cola, Toastmasters chapters gave leaders a safe space to practice public speaking, storytelling, and feedback.

And beyond formal training, there's practice in the everyday moments—taking notes in meetings, volunteering to summarize a discussion, representing a project team, or offering to speak at a class or event. Every repetition builds comfort and clarity.

My own Center for Creative Leadership experience was the beginning of that practice for me. Decades later, I still catch myself needing to slow down, listen, and wait for the right moment. The lesson never stops.

Painting the Picture: When It Works and When It’s Missing

When communication works, credibility follows. Jeff Edwards didn’t have to compete for airtime; his credibility made his words count. When it's missing, even talented people like Forrest can struggle to influence or grow.

Both extremes teach the same lesson: communication isn't about more or less—it's about meaning. It's knowing when to speak, what to say, and how to connect it to the needs of others. 

Practical Ways to Build Communication Strength

• Listen to learn. Take notes, paraphrase what you've heard, and confirm understanding
• Translate technical into practical. Explain what data means for the business, not just what it shows.
• Observe before you act. Practice "seeing" your operation or process with fresh eyes.
• Simplify your writing. Clarity beats cleverness every time.
• Seek feedback. Ask trusted peers to tell you how your communication lands.
• Prepare with intent. Know your audience, outcome, and key message before you speak. 

Reflection Questions

• Where in my current role does communication make or break outcomes?
• When was the last time I adjusted how I communicate to fit my audience?
• Do I listen more than I speak—and what might I learn if I did?
• How can I model communication that builds understanding rather than winning airtime? 

Closing Thought

Technical skills and analytics may earn you a seat at the table, but communication determines whether your ideas move the organization forward.

In a world of AI, automation, and constant change, the ability to listen, observe, and translate context into action remains our most human—and most valuable—differentiator.

Liu serves as the principal investigator (PI), joined by co-PIs from five universities: Hiba Baroud (Vanderbilt University), Linyin Cheng and Song Yang (University of Arkansas), Jennifer Pazour (Rensselaer Polytechnic Institute), Yisha Xiang (University of Houston), and Xiang Zhou (Harvard University). Together, they are launching Resilient-NET, a collaborative research team and network designed to connect U.S. and international research communities focused on the resilience of urban socio-technical systems.

The project takes a holistic approach to urban resilience, focusing on three interwoven dimensions:

• Technology (the “New Dimension”) – examining the integration of AI-enabled systems into infrastructure and mobility networks.
• People (the “Missing Puzzle”) – exploring the complex and evolving interactions between humans and technology.
• Environment (the “Uncertainty Accelerator”) – addressing the rising frequency of extreme natural events that disrupt urban systems, with the goal of improving predictive modeling, disaster preparedness, and the development of urban digital twins.

By combining these perspectives, the team aims to generate new insights into how technology, society, and climate intersect, and to chart pathways toward resilient, sustainable, and livable cities.

“Urban resilience is an interdisciplinary grand challenge,” Liu said. “It requires coordination of talents and resources to create transdisciplinary solutions. Through Resilient-NET, we hope to consolidate a roadmap for resilient urban ecosystems and nurture the next generation of leaders who will tackle these problems on a global scale.”

The project benefits from the support and collaboration from multiple research fields within ISyE such as System Informatics and Control, Energy and Sustainable Systems, Data Science and Statistics, and Supply Chain and Logistics Institute (SCL) and AI4OPT of Georgia Tech, domestic partners including the Weatherhead Center for International Affairs at Harvard, the Natural Hazards Center at the University of Colorado, IBM Research, the Taylor Geospatial Institute, and Argonne National Laboratory, as well as international partners, including the Singapore-ETH Center on Future Resilient Systems, Karlsruhe Institute of Technology in Germany, Global South partners such as Tecnológico de Monterrey and Universidad Panamericana Guadalajara, and the 4TU Centre for Resilience Engineering in the Netherlands.

Looking ahead, the researchers envision Resilient-NET as a long-term hub that not only advances scientific understanding but also equips students and early-career researchers with global leadership skills. At a time when artificial intelligence is rapidly reshaping infrastructure and mobility, Liu and his collaborators see this work as critical to ensuring that urban systems continue to function in the face of uncertainty.

Liu shares, “Our vision is that Resilient-NET will serve as a bridge, linking disciplines, institutions, and countries, to build cities that are not only technologically advanced, but also safe, welcoming, and adaptable for generations to come.”

Read the full story here. 

It means that our faculty community has specific rights and responsibilities that allow them to govern themselves and uphold high academic standards. The success of this model hinges on faculty contributions and voices.  

On a busy campus filled with enough buzz to keep schedules fully booked, Dima Nazzal, chair of the Faculty Executive Board, and Adam Steinberg, secretary of the faculty, explain why faculty governance is a commitment that matters.  

Q: Why do you think faculty governance matters, especially given everything else faculty juggle?

Nazzal: The faculty handbook says it’s both a right and a responsibility. Faculty are responsible for maintaining the highest standards for teaching, research, and resources. Many of us don’t think about how policies are made until we’re part of the process. Faculty governance gives us that voice.

Steinberg: For me, it’s about impact. I could publish a paper that gets cited hundreds of times over the years. But through governance, I can help make a decision that affects 50,000 students immediately. That’s powerful.

Q: What makes Georgia Tech’s governance structure unique compared with other universities?

Nazzal: One major difference is that half of our faculty are research faculty — many in GTRI. That’s unusual, and it shapes governance. We have both an Academic Faculty Senate and a Research Faculty Senate, with the Faculty Executive Board and Standing Committees of the Faculty bringing those together. Another unique element is that the president presides over the Senate, whereas at many universities it’s an elected faculty member.

Steinberg: Beyond structure, the culture matters. At Tech, governance is collaborative, not combative. Even when there’s tension, the spirit of the faculty community is aligned with our mission to support students.

Q: Why should students and staff care about faculty governance?

Steinberg: Students come here for the best education, and faculty governance is how we oversee, adapt, and advance the academic mission. Everything from degree programs to academic integrity policies to campus services passes through this system.

Nazzal: And it’s not just faculty voices. Students and staff serve as full members on many standing committees. Their input shapes outcomes, whether it’s curriculum, services, or even student fees.

Q: Could you share how you first became involved in faculty governance at Georgia Tech?

Nazzal: My first service involvement beyond my School came during the pandemic. As an industrial and systems engineer, I volunteered for the Covid-19 recovery task force. That experience showed me how Georgia Tech runs — how every person and unit is essential. After that experience, I decided to run for the Faculty Services Committee, then the Faculty Senate, then the Faculty Executive Board. Eventually, I was persuaded to run for vice chair and chair of the Faculty Executive Board.

Steinberg: I came to Tech as an associate professor and joined the Institute Undergraduate Curriculum Committee (IUCC). At first, I just observed. Later, I chaired a subcommittee during a major curriculum review, and that’s when I really engaged. From there, I became vice chair of IUCC, and then I was encouraged to run for secretary of the faculty.

Q: For faculty who are skeptical, what would you say about the impact they can have through governance?

Nazzal: Some impacts are easy to measure, like new degrees or policies approved through committees. But much of the work is behind the scenes — building trust, shaping resolutions, finding alignment, and preventing conflicts. It’s hard to see unless you’re inside, but it matters.

Steinberg: If governance stopped, you’d notice immediately. New programs wouldn’t move forward, and policies wouldn’t be adapted. The deeper you engage, the more you see how essential it is.

Q: If I’m a faculty member who has never been involved, what’s the best way to start?  

Nazzal: Many people start with service in their School or College committees, then move into Institute-level work. At the Institute level, you can run for one of the 15 standing committees, each with a clear focus — like benefits, accessibility, IT services, or curriculum.

Steinberg: Standing committees do the detailed work, while the Faculty Senate deliberates and acts on those recommendations. Both are good entry points, and temporary committees also provide opportunities to engage when new issues arise.

Q: What’s your elevator pitch for why faculty should participate?

Nazzal: Three things: You grow your network, you gain perspective on how Georgia Tech works, and most importantly, you get to influence how things get done here.

Steinberg: I’d add that it’s also leadership development. Many of Tech’s current academic leaders cut their teeth in faculty governance. It’s a way to make Tech better and grow professionally at the same time.

There are opportunities throughout the year to become involved in Faculty Governance at Georgia Tech. You can find out more about the various committees and branches where you can plug in via the Faculty Governance website.

For the 25th year in a row, Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering (ISyE) has been named the nation’s top undergraduate program in its field by U.S. News & World Report. The 2026 Best Colleges rankings, released September 23, 2025, reaffirm ISyE’s long-standing reputation for excellence in education and research. 

"While rankings are just one measure of our impact, they reflect the respect ISyE has earned among peer institutions and the broader academic community," said Pinar Keskinocak, professor and H. Milton and Carolyn J. Stewart Chair. "Most importantly, they also underscore our shared commitment to preparing the next generation of leaders in our field." 

Introduction

Artificial intelligence has entrenched itself in almost every aspect of the professional world. From copywriting tools to search engine optimization and image generation, professionals and laypeople alike use this new technology to streamline daily activities. But, before AI, there was high-level analytics and machine learning in supply chain. Analysts across the supply chain used machine learning to interpret high volumes of data and turn it into predictive algorithms for inventory planning, demand planning, and more. Now, AI is generating these analytics at a much faster, real-time pace.

This shift raises important questions. What does this mean for technology professionals in the supply chain world who once made a living doing these jobs? And what can we expect for aspiring supply chain pros or mid-career professionals who want to increase their value to the team in an age of accelerated technological advances? 

The fact of the matter is that AI is now everybody’s job. Standing still will ensure that you get left behind by your peers or the talent pipeline from colleges and universities. The question then becomes, how can I upskill and use what I already know to add value to my role and ensure that my AI competencies allow me to compete in today’s supply chain workforce?

We’ll look at the ladder as a series of increasing levels of complexity and AI activity—what we’ll call ‘maturity levels’: descriptive, diagnostic, predictive, prescriptive, cognitive/autonomous, and integrated enterprise.

Some things to bear in mind as we progress through this topic:

1. Everybody is somewhere on the ladder, so everyone has the opportunity to climb the ladder.
2. Analytics are no longer just for specialists. AI allows analytics to be an access point to the ladder. You no longer have to rely on someone else higher up on the ladder, and it’s in your best interest to climb higher, regardless of your job description.
3. There are lots of resources freely available to allow you to climb the ladder. But in most companies, you can find a mentor who is further along on a ladder, and perhaps they can help you up-skill your operational knowledge and help you advance your capabilities to ascend the ladder. 

We’re here to discuss to what degree you should so you can optimize your career opportunities and not be left behind. 

How Did We Get Here?

In the field of supply chain we’ve always been ahead of the curve when it comes to these types of innovations. Before AI, we were using machine learning and predictive analytics to enhance our understanding of real-time supply issues. We worked a lot on optimizations at Coke and started utilizing machine learning tactics almost 10 years ago. While I wasn’t the hands-on user of the technology, I took it upon myself to try and understand exactly what was happening and how it was working.

That was a large corporate machine–one of the biggest brands in the world–utilizing the latest in predictive analytics technology. And now we have a democratization of this technology being spread across industries. You no longer need to be part of such a high-powered team to make use of these tools. 

We have now entered into an era where artificial intelligence has become omnipresent across almost every supply chain practice and industry, or any other career discipline. The key is understanding best practices is making use of AI in your field, and how you can add value and incorporate it into your everyday work-life. 

Descriptive Level: From Rearview Mirror to Forward Thinking Decisions

“If you have some proficiency in Excel, then you’re on the ladder.” - Chris Gaffney

The lowest rung on the AI ladder is the descriptive level. Excel knowledge and experience resides here and can be the access point for most people. This level helps us describe what is happening with numbers and data. Reporting dashboards can be crafted here, and we can run trend analysis using basic inference to see what is happening and where to make adjustments, if necessary.

Excel tells us what did happen - not what could happen. These are important functions, to be sure. However, they only look behind us. They tell us what and why. Today’s supply chain landscape requires tools that allow us to make decisions based on what could happen in the future. We don’t have the power to make proactive decisions or to navigate uncertainty and factor in variables of change.

Our competitive edge is sharpened by having the capability to shape the future, not just explain the past. In order to do so, we need to move up into predictive and prescriptive AI territory.

Up until very recently, this descriptive capability was enough. Analysts, planners, and buyers were all able to produce data that helped others to understand what was happening. The data then required synthesis and analysis. The whys and so whats were human functions performed by different team members and used to measure the efficacy of various inputs and outputs throughout the supply chain. As one moves up the chain of command, so to speak, the ability to interpret the data and findings becomes even more important. However, the numbers crunching and analytics were more siloed.

And now, everyone has access to AI’s ability to synthesize and analyze raw data. But very few “off-the-shelf tools” can answer the why, let alone the ‘what should we do about it’ questions. Planners and managers need to upskill and ensure that they are up to speed on the capabilities and deficiencies of these platforms and insert themselves and their skillsets to close those gaps.

Roles at this level:

• Transportation analysts
• Warehouse supervisors reviewing daily throughput metrics
• Demand planners tracking forecast accuracy from the last quarter

Working in hindsight by monitoring and measuring data is important, albeit limiting. This looking backward in the world of supply chain decision making at a time when forward thinking is essential for future proofing your supply chain organization. Staying here too long limits your ability to prevent problems before they escalate.

What to do next?

• Learn Power BI or Tableau for interactive dashboards
• Get comfortable using large data sets from your ERP or WMS
• Start asking, “why” and “so what”

Diagnostic Level - Information into Insight

“This is where you start to become more valuable because now you can help the team avoid repeat issues.”

So you’ve now measured what happened. The next logical question is why?  Here’s where many companies fall short by relying on only internal historical data. The real learning happens when you bring in external variables like weather, economy, labor, or competitive actions. Diagnostics help uncover root causes and patterns across time and systems. What does this mean for you and the AI ladder?

This could mean combining two different datasets using SQL to pull deeper reports or identifying correlations between variables. You need to be able to get inside of your supply chain to see what’s really going on, much like a physician will draw blood or perform various scans to get a more vivid and comprehensive picture of what’s happening.

Examples from the field:

• A demand planner diagnosing why forecasts were consistently off by adding external factors outside your control.
• A transportation analyst finding route disruptions correlated with labor strikes and weather trends - kinda like WAZE.

What you can do

• Add layers of internal and external factors
• Use Power BI or Excel to show the impacts of external events
• Start to track leading indicators, not just lagging ones.

Predictive - Seeing What’s Coming

“Most of the tools we have heavily leverage your own history. But your ability to sell a product next year is different because you don’t control everything.”

Predictive analytics enables supply chain professionals to see trends, forecast disruptions and plan proactively.

As we mentioned earlier, most forecasting tools rely too much on internal history. Predictive power comes from adding things like economic trends, labor availability, weather, etc., to your forecasting models.

My first exposure to the broader umbrella of machine learning, falling under AI, was while working at Coke. Every night, our machines processed enormous volumes of data to track how much of each type—across countless product combinations—was being used. This data was being used to predict when the fountain machines would fail so that we could prepare a replacement without losing time or operational capacity. Basically, this meant we could allocate maintenance resources proactively instead of reactively.

This machine learning doesn’t have to be intimidating. In fact, machine learning was the #1 skill in supply chain job postings in 2024. Python and machine learning are much more accessible tools than they once were, and many professionals are teaching themselves the basics using online resources that are much more prevalent than they once were. Again, the democratization of AI tools means everyone can level up a lot faster.

Roles Seeing This Shift

• Demand planners and sourcing managers are combining historical sales information with things like inflation, trade wars, and taste evolutions.
• Transportation teams are integrating weather trends and traffic data to reroute loads

What Can You Do:

• Learn the basics of Python’s forecasting libraries
• Pull in a single external variable, like weather or labor availability, into your demand forecast.
• Track model accuracy over time to see where it succeeds and, most importantly, fails.

Prescriptive: Deciding What to Do About It

"We don’t want analytics experts. We want people who are applied analytics or applied AI experts.”

It’s not just identifying the risk. The key is choosing a more effective path forward. And this requires modeling scenarios in a way that lets you take action rather than just be an observer. 
A lot of companies stop at prediction. The ones that get ahead of the pack are those that are able to simulate outcomes and use this logic in daily decisions. Just remember that context is everything. Those with very impressive technical skills can sometimes miss the mark because they didn’t understand the business. There are also supply chain planners with moderate technical skills who can make major contributions because they knew what mattered and where to apply it.

The supply chain AI ladder is crucial, but only as effective as the depth of the supply chain knowledge base.

Cognitive and Integrated is When AI Starts to Work With You

This is the very top of the ladder or the tip of the AI ladder iceberg, if you will. This is the realm of AI agents that are learning and acting in an intelligent and sometimes autonomous manner. The cognitive tier blends into the integrated enterprise, where systems and data are connected. Warehouses talk to the forecast, which communicates with sourcing, which can adjust production. This is kind of futuristic, but based on how AI has evolved, it will likely be ubiquitous within a couple of years.

How to Apply Cognitive and Integrated AI:

• Learn how to build a basic GenAI or logic-based agent using online tutorials or sandbox tools
• Make sure the AI Agent’s work is sound before turning it loose on our business. The human element is still crucial in these cases.

Role of Leadership in Deploying the Supply Chain AI Ladder

“This can’t be a black box to you.”

Leaders need to know just enough about AI to advocate for it. If you’ve hired the right people, then you trust them to do the job that you hired them to do. If they’re telling you that AI tools will help them do their jobs better, then listen to them. Find out what your team needs and get them to explain to you how AI can unlock more benefits for your business.

Encourage them to pursue professional development courses and to experiment in a safe environment until they feel confident integrating the tools into regular operation.

Conclusion: Don’t Stand Still and Be Left Behind

The supply chain AI ladder is real, and it’s climbable. You are not too late to get on board and begin using AI to increase your personal value at your company. It doesn’t matter how old you are - whether you’re an entry-level professional with an MBA, a mid-career professional, or a seasoned C-suite executive. There is a place on the ladder for you.

The most valuable assets that employees can bring to bear right now in this tech immersion context. Those who have been in the workforce for a few years are able to mix their experiential knowledge with the tools and assets available through AI to translate technology into real-world wins for your supply chain teams. Your value increases significantly if you pair your knowledge with proactive learning tools.

Take the time to self-assess and figure out where you are on the ladder.

Don’t try to jump too high up on the level. Take it one rung at a time. Then reassess.

Commit to the 70/20/10 rule. 70% on-the-job learning, 20% learning from peers and mentors, and 10% formal training.

Apply what you’ve learned and stay curious. Just don’t get complacent. This is not the time to rest on your laurels because someone who is hungry for knowledge will be on your heels.

This content was developed in collaboration with SCM Talent Group, a supply chain recruiting and executive search firm.

Every few weeks these days, a new AI breakthrough makes headlines. Models get sharper and more capable. Language tools get more fluent. Claims of agent breakthroughs and embedded autonomy in tools are everywhere.

And each time, the question resurfaces: What’s left for people to do as this wave progresses?

It’s a fair question. But from what I’ve seen throughout my career—from managing logistics in a Frito-Lay regional DC to transportation and distribution operations at AJC International and Coca-Cola, and now through executive education, consulting, and applied research at Georgia Tech—I believe we’re asking the wrong question.

Instead of asking what AI can do, we should be asking: Where is the human edge—and how do we keep it sharp?

1. Collaboration Across Boundaries Still Wins the Day

Whether in manufacturing, logistics, commercial and customer teams, or strategy, success still hinges on people working together—often across silos, systems, or supply chains. At Coca-Cola, some of the most impactful progress we made didn’t come from technology upgrades. It came from aligning teams that didn’t naturally collaborate—finance with planning, supply chain with sales, bottlers with company.

From what I see in my advisory work and interviews with supply chain leaders, that hasn’t changed. AI can improve visibility. It can suggest decisions. But it doesn’t build consensus, resolve conflicts, or create shared understanding. That’s human work—and it often makes the difference between potential and progress.

2. When the Plan Breaks, People Step Up

During my time in global logistics at AJC International, unexpected events were the norm: shipping delays, capacity shortages, regulatory changes. AI may help flag risks, but when the plan breaks, it’s still people who step in, prioritize under pressure, and find creative solutions.

This same theme came up in a recent SCM Talent podcast conversation. When I asked a senior supply chain leader what traits define her most effective team members, she didn’t hesitate:

“A drive for results. Problem solving. The ability to work in teams. And the ability to influence others.”

Those aren’t going out of style. They’re still what carries teams forward when the data model breaks or the shipment gets stuck.

The professionals I see excelling—especially in moments of disruption—aren’t just technical experts. They’re problem solvers who own the outcome and stay focused when others get stuck.

Drive, persistence, and adaptability aren’t things you automate. They’re human qualities that remain essential.

3. Hands-On Context Isn’t a Field Trip—It’s a Foundation

At Frito-Lay, I worked in a regional distribution center and breakbulk operation managing warehouse activities and dispatching drivers. Later, I spent a full year as an operations manager at one of our plants, where I led drivers and worked with plant warehouse teams and schedulers to ensure load readiness and on-time dispatch to local DCs.

Those weren’t just jobs—they were formative experiences. They taught me how decisions affect execution in the real world, and how the rhythm of operations shapes everything else in the supply chain.

That’s why I firmly believe professionals—especially early in their careers—should spend 3 to 5 years in front-line roles. No AI tool can replicate the kind of intuition you build by seeing how things work, where they break, and how people respond in real time. That foundation lasts an entire career.

4. Communication and Leadership Will Always Matter

In every role I’ve had—from the plant floor to corporate teams to Georgia Tech—I’ve seen that clear communication and authentic leadership are force multipliers. They carry more weight now, not less.

AI might help with drafting, summarizing, or visualizing, but it doesn’t earn trust. It doesn’t mentor a new team member or guide a group through a difficult change. That takes listening, emotional intelligence, and personal credibility.

Those leading change in today’s organizations—whether rolling out a new system or rebuilding after disruption—are the ones who can communicate with clarity and lead with steadiness. That’s not something AI can learn.

5. The Edge Is Where Humans Live

There’s a space at the boundary of every operation—the “edge”—where plans meet real-world variability. And that’s where humans remain essential.

Whether it’s spotting an issue before it escalates, reading between the lines of a conversation, or connecting seemingly unrelated problems across functions, that kind of judgment is rooted in experience. It can’t be downloaded or inferred from data alone.

In my work at Georgia Tech, across executive education, consulting, and applied research, I regularly see the difference it makes when decision-makers bring not just technical knowledge, but lived context from the field. That human edge is where resilience is built—and where strategy becomes reality.

6. Humans and AI: Better Together

To be clear: this isn’t about rejecting AI. The smartest teams I work with aren’t afraid of it—they’re learning how to use it. AI tools can improve productivity, identify trends, and help people make better decisions. But they need to be paired with human insight.

AI suggests. People choose. AI speeds up planning. People keep it grounded. The professionals who combine digital fluency with interpersonal skill, operational awareness, and strategic judgment? Those are the ones who will lead in the next era.

So What Should You Do?

If you want to build a career that endures—and evolves—with AI, here are seven things I recommend:

1. Invest in the front line. Not just a tour. Spend 3–5 years in a real operations or customer-facing role. It will shape how you lead for decades.
2. Build bridges. Learn how sales thinks. Understand finance’s constraints. Connect systems, teams, and people.
3. Volunteer when the extra project comes up. These stretch roles are often tied to strategic initiatives and senior leadership. Saying yes can accelerate learning and visibility—especially when others hesitate.
4. Take roles at the intersections—not the cul-de-sacs. Look for positions that connect functions, partners, or ecosystems. Exposure to diverse perspectives sharpens insight and multiplies your value.
5. Sharpen your communication. Speak with intent. Write with clarity. Listen deeply. These skills amplify everything else.
6. Evolve with AI—or fall behind. You don’t need to code, but you do need to understand how AI is changing your domain. Through continuing education, hands-on learning, or professional development, stay curious and current.
7. Never stop learning. At Georgia Tech, I see firsthand how ongoing learning—through executive education, research engagement, or new assignments—helps professionals lead through change. Keep asking: what haven’t I seen yet? Who could I learn from?

Final Thoughts

The future of work isn’t about humans vs. machines. It’s about people who can lead, decide, and connect—with AI as their force multiplier.

We may automate tasks. But judgment, trust, and empathy? Those are human domains. And in times of uncertainty, it’s the people who can navigate complexity, rally teams, and adapt with integrity who make the difference.

So yes, learn the tools. Embrace the change. But never underestimate the power of experience, context, and connection.

That’s your edge. And that’s not going anywhere.

A Personal Wake-Up Call

I’ve always considered myself a reasonably strong critical thinker—someone who asks good questions, challenges assumptions, and doesn’t adopt a viewpoint just because it’s popular. But a recent experience humbled me. I took an open-source critical thinking test and didn’t do nearly as well as I expected.

This led me down a deeper path of inquiry. I was already concerned about how two decades of social media have shaped the way we consume and respond to information—short, sensational content delivered by algorithm. And now, with the rapid rise of generative AI, I worry we may be trading our thinking for speed and scale.

I use AI tools daily, and I advocate for their use—especially in supply chain applications. But I’ve also come to believe this: if we’re not careful, we risk outsourcing the very thinking that makes us human and effective decision-makers.

Why Critical Thinking Matters More Than Ever—Especially in Supply Chain

Critical thinking isn’t just a defense mechanism—it’s a differentiator. In a world where AI can generate answers instantly, the professionals who ask the right questions will stand out.

Supply chain professionals operate in environments where second and third-order consequences matter. We are called on to make decisions under uncertainty, weigh risks, balance competing priorities, and understand interdependencies.

Judgment—tempered by experience, structured analysis, and humility—is the edge. Tools can help you scale, but they cannot replace the human responsibility to challenge, reflect, and adjust.

What Is Critical Thinking?

Critical thinking is the ability to think clearly and rationally about what to do or believe. It involves:

• Questioning assumptions
• Evaluating evidence
• Recognizing biases (ours and others’)
• Drawing reasoned conclusions
• Reflecting on one’s own thought process

Said simply, it’s self-awareness of your thinking style—how you form your views, test them, and revise them when new evidence emerges.

It requires effort. It requires slowing down. It requires, at times, being wrong.

Facione, in his Delphi Report, defines it as "purposeful, self-regulatory judgment."

Kahneman reminds us that our brains are wired for shortcuts—“System 1” thinking is fast and efficient but often error-prone. True critical thinking requires “System 2” effort: slow, reflective, and disciplined.

Are We Losing It?

There’s growing evidence we are.

Social media echo chambers reduce exposure to opposing views. Short-form content conditions us to expect fast answers. And according to the MIT Media Lab (Kosmyna et al., 2024), students using ChatGPT retained less, showed reduced cognitive effort, and had lower originality.

“When ChatGPT was used, cognitive effort declined.”

And yet—this is not a moment for despair. It’s a call to discipline. Because critical thinking, practiced intentionally, can become a personal and professional superpower.

Applying Critical Thinking in Supply Chain Decisions

Supply chain professionals face complexity daily—inventory tradeoffs, supplier uncertainty, resource constraints, policy risk. Many of these decisions can’t be answered by tools alone—they require judgment. Critical thinking lives in that judgment.

Whether you're building a forecast, evaluating a supplier, responding to a disruption, or modeling risk exposure, structured thinking provides a path. The steps are familiar:

• Define the problem clearly
• Clarify what information is available—and what’s missing
• Analyze root causes or future implications
• Generate multiple options
• Establish decision criteria
• Choose a path—and test it before launch
• Monitor and adjust as feedback arrives

This process resembles A3 thinking or supply chain analytics. But what makes it powerful is doing it intentionally—even under pressure.

The best professionals I’ve worked with practice it on small decisions as well as large ones. They don’t confuse speed with clarity.

Practicing Critical Thinking When Using Generative AI

AI tools are powerful—but without deliberate use, they can dull our thinking. Here's how to make AI work with your brain—not instead of it:

• Document your assumptions before prompting
• Journal your intent: What are you trying to decide or explore?
• Ask AI to provide counterarguments or alternative views as well as sources for you to research and draw your own conclusions
• Look for what’s missing or oversimplified
• Summarize AI output in your own words
• Track and reflect on how AI influenced your decisions

Treat AI like a research assistant—not a strategist. Use it to extend your reach, not replace your reasoning.

Final Thought and Your Next Steps

Critical thinking is no longer optional. Not in business. Not in education. Not in leadership.

It is a skill. A discipline. And a mindset that pays dividends over a lifetime.

If you’ve read this far, take this challenge seriously:

1. Write out how you form your opinions—on paper.
2. Practice structured thinking on small problems weekly.
3. Use AI with intention—never outsource your judgment.
4. Teach someone else how you reached a conclusion.
5. Be humble. Ask yourself: what if I’m wrong?
6. Keep a thinking journal for 30 days.

The goal isn’t to be right all the time. It’s to be reflective, rigorous, open to challenge, and consistent over time. That’s what the world needs more of. That’s the edge AI can’t replicate.

So think before you automate.

And never stop questioning.

Ms. Ananthachary brings a wealth of experience in enterprise software and cloud technologies to the SCL Advisory Board. She has a proven track record of building and mentoring high-performing global engineering teams and driving large-scale strategic initiatives. Her leadership has played a key role in delivering transformative, cloud-based enterprise applications and advancing digital solutions in the supply chain space.

“I’m honored to join Georgia Tech’s SCL Industry Advisory Board,” said Ms. Ananthachary. “As someone deeply passionate about the future of supply chains, I’m inspired by the SCL team’s commitment to innovation, education, and impact. I look forward to learning, contributing, and collaborating with this exceptional community.”

Ms. Ananthachary holds an MBA from Georgia State University and a Bachelor of Science from the National Institute of Technology Jamshedpur. She brings both technical expertise and a strategic business perspective to her advisory role.
 

Below are the awardees: 

Graduate Awards

The program bestows multiple awards and fellowships to graduate students who have been recommended for quality and positive performance within the last year. 

1. Atlanta Air Cargo Association PhD Student Fellowship for Research Excellence
   1. Joseph Boone
2. Shabbir Ahmed PhD Student Fellowship for Research Excellence
   1. Neelkamal Bhuyan & Jingye Xu
3. Thos and Claire Muller PhD Student Fellowship for Research Excellence
   1. Yuming Sun
4. Anderson-Interface PhD Student Fellowship for Research Excellence
   1. Kevin Wu
5. Jerry and Harriett Thuesen PhD Student Fellowship for Research Excellence
   1. Diptangshu Sen
6. Robert Goodell Brown PhD Student Fellowship for Research Excellence
   1. Mengqi Lou
7. Ed Iacobucci PhD Student Fellowship for Research Excellence
   1. Yuhao Wang
8. Margaret and Stephen Kendrick PhD Student Fellowship for Research Excellence
   1. Alexander Bukharin
9. Angela P. and Reed J. Baker PhD Student Fellowship for Research Excellence
   1. Young In Kim
10. ISyE Outstanding Graduate Student Instructor of the Year Award
    1. Meen-Sung Kim
11. The Philip J. and Delores A. Scott Graduate Student Health and Wellness Award
    1. Sixtine Guerin
    2. Himadri Pandey
    3. Zihan Zhang
    4. Tanuj Deshmukh
    5. Thomas Cabe
    6. Sharay Gao
12. Alice & John Jarvis Best Paper Award - Winner
    1. Tianjiao Li
13. Alice & John Jarvis Best Paper Award - Honorable Mention
    1. Shaan Ul Haque
14. Alice & John Jarvis Best Paper Award - Honorable Mention
    1. Neelkamal Bhuyan

Undergraduate Awards

The undergraduate awards offer a number of scholarships and recognition to students each year, based on recommendations, past performance and the student's current resume. To learn more about each award, read here.

1. Institute of Industrial and Systems Engineers Excellence in Leadership Award
   1. Lucia Touma
2. The Evelyn Pennington Outstanding Service Award
   1. Aron Cheng
3. The Evelyn Pennington Student Health and Wellness Award
   1. Shirley Sharp
   2. Piya Khakharia
   3. Caroline Steiger
   4. Brennan Haynes
   5. Mohamad El Abou Khoudoud
   6. Shalini Mehra
4. ISyE Alpha Pi Mu Academic Excellence Award
   1. ZhiXian (Chris) Liding
5. Kurt Salmon & Associates Scholarship in Industrial and Systems Engineering
   1. Anna Park, Noreen Ali, Sristi Karamchandani
6. KS2 Technologies, Inc. Entrepreneurship Award
   1. Guy Mastrion
7. KS2 Technologies, Inc. Innovative Technology Award
   1. Sahana Yerneni
8. Nicholas & Aurora Suarez Condezo International Award
   1. Mariana Anargyrou
9. Institute of Industrial and Systems Engineers Outstanding Senior Award
   1. Sam Deckbar
10. Institute of Industrial and Systems Engineers Outstanding Freshman Award
    1. Mariana Anargyrou
11. Institute of Industrial and Systems Engineers Rising Star Award
    1. Aron Cheng
12. COE Honors Day Award
    1. Rohin Shah

The economic impact of Georgia’s transportation and logistics industry was $107 billion in 2023, according to an economic impact study by the University of Georgia’s Selig Center for Economic Growth. These industries supported more than 578,000 Georgia jobs, or one in nine jobs in the state. From 2010 to 2023, transportation and logistics jobs in Georgia grew by 68%, outpacing the national growth rate of 52%. Additionally, in 2023 and 2024 alone, new logistics and distribution sector investments, including cold storage and ecommerce fulfillment centers, totaled $3.8 billion and created over 9,000 new jobs.

“Georgia’s unmatched global connectivity is one of the driving forces behind our economic success. Decades of strategic investment in our logistics and supply chain infrastructure – from our ports and rail lines to our highways and air cargo capabilities – have led to record-breaking economic investments and trade,” said Georgia Department of Economic Development Commissioner Pat Wilson. “The Logistics Summit brings together private sector, government, and education leaders to learn from experts, exchange best practices, and explore opportunities in the rapidly evolving logistics landscape to maximize opportunities. Events like this strengthen collaboration and spark new ideas that keep Georgia businesses competitive on a global scale.”

Georgia Department of Transportation Commissioner Russell R. McMurry highlighted Georgia’s strategic investments and how the Georgia Department of Transportation (GDOT) is leveraging technology to improve freight flow. He cited the leadership of Governor Brian P. Kemp and support from the General Assembly to allocate $1 billion to the newly created Georgia Freight Program over the past two years. Additional investments in transportation infrastructure are advancing the timing for key planned transportation projects that will maintain and improve Georgia’s interstate highway system, roads, and bridges. Georgia’s multimodal transportation network carried nearly half a billion tons of freight in 2019, valued at $673 trillion. Projections show that freight volume is expected to nearly double to 900 million in tonnage and freight value to more than double today’s value by 2050. Working with partners that include the Center of Innovation and the Georgia Institute of Technology, GDOT is focusing on enhancing safety and efficiency, including projects to add 50% more truck parking and installing fiber internet on Georgia interstates.

Georgia Ports Authority Vice President of Operations Susan Gardner provided updates on strategic investments to expand capacity at the ports, and how Georgia Ports Authority (GPA) is leveraging live data to improve safety, track vessel productivity and containers, and eliminate congestion. Gardner emphasized building a technological culture and prioritizing hiring creative employees, as well as harnessing data insights to boost efficiency. GPA is investing in $4.5 billion in improvements over the next decade as part of its port master plan to expand cargo handling capabilities and support future supply chain requirements.

This year’s feature panel, “AI and Beyond: Embracing Digital Transformation in Logistics,” included leadership from The Home Depot, Havertys Furniture, and TOTO USA, as well as research perspectives from the Georgia Institute of Technology. Panelists highlighted the ways digital technologies are reshaping supply chains, including a three- to five-year outlook for the industry, and provided insights attendees can use to shape their strategies to move more efficiently as AI and automation transform the industry.

“Digital technologies are reshaping supply chains in various ways, and Georgia is working to stay ahead of the curve,” said Center of Innovation Executive Director David Nuckolls. “The Center of Innovation and our specialized logistics team work alongside this dynamic industry, helping to position businesses for growth. The annual Georgia Logistics Summit is a powerful opportunity to build connections and equip businesses with crucial knowledge and resources.”

Educating the needed talent was the focus of the event’s final panel, with University System of Georgia Chancellor Sonny Perdue and Technical College System of Georgia Commissioner Greg Dozier providing updates on how the state’s post-secondary institutions are developing a globally competitive workforce. Discussion focused on how these institutions are ensuring the skills they are teaching match the jobs logistics companies are looking for, including creative problem-solving and effective use of new AI and automation tools. The breadth of Georgia’s technical college programs was also discussed, including the High Demand Career Initiatives program and a pilot program called “Dual Achievement” that enrolls students who withdrew from high school in a technical college program, enabling them to earn a high school diploma alongside a technical college certificate, diploma, or degree. Panelists focused on the importance of helping students get where they want to go faster, upskilling the existing workforce, and how connections between industry leaders and educators can help foster greater outcomes.

The Center of Innovation’s Logistics Industry Advisory Board also recognized the winners of the inaugural Future Innovators in Supply Chain competition. The competition invited college students to create videos about supply chain careers, reflecting the Center’s commitment to developing future logistics leaders. Led by professor Parisa Pooyan, student team “The Masters of Logistinomics” from Kennesaw State University won first prize and a $3,000 grant for the university. Eli Hampton, Angeline Harris, Joe Johnson, and Dana Pazhouhesh created the winning video, which can be viewed here.

For additional information on the 2025 Georgia Logistics Summit and to stay up-to-date on next year’s plans, visit galogisticssummit.com.

Participants in the 2025 Georgia Logistics Summit also included leaders from S&P Global Market Intelligence, Boost Phase Ventures, and M.D. Livingstone Consulting.

About the Georgia Center of Innovation
Exclusive to Georgia, the Center of Innovation helps Georgia businesses of all types and sizes find inspired solutions to challenges and opportunities. The Center connects new and expanding businesses with a team of experts, external partners, and independent mentors to tap into the technical expertise and guidance they need. By encouraging collaboration across six key industries: Aerospace, AgTech, Energy Technology, Information Technology, Logistics, and Manufacturing, the Center helps Georgia prepare for growth in strategic industry ecosystems.

About GDEcD
The Georgia Department of Economic Development (GDEcD) is the state’s sales and marketing arm. It is Georgia’s lead agency for attracting new business investment, encouraging the expansion of existing industry and small businesses, and locating new markets for Georgia products. As the state’s official destination marketing organization, it drives traveler visitation and promotes the state as a location for film and digital entertainment projects. GDEcD is responsible for planning and mobilizing state resources for economic development, fostering innovation and the arts to drive opportunity from the mountains to the coast.

As part of their preparation for undergraduate education in the U.S., GTLI students enrolled in the Supply Chain Fundamentals course, a foundational element of our program, recently took their final exam in a truly innovative way.

The students, hailing from GTLI, are part of a program designed to equip international students with the skills they need to succeed in American universities.  Language Institute director, Katherine Samford, emphasizes, “Comprehensive preparation for undergraduate studies for our students means developing their English language skills, helping them build strong academic habits, and providing foundational exposure to content. 

Working with Georgia Tech’s Supply Chain and Logistics Institute is the perfect match for our program mission.”  Since many of these students have expressed a keen interest in pursuing a degree in Supply Chain Management, the Supply Chain Fundamentals course is a critical steppingstone toward their academic and professional goals.

What made this exam particularly unique was its delivery through our new Global Virtual Learning Environment (HITeC). HITeC, which we are also utilizing to modernize the content and pedagogy for our Master's in Supply Chain Engineering program, provided the perfect platform for these students to demonstrate their knowledge. 

The system was developed in collaboration with Dr. Frederick Benaben and our partners at IMT, offering a group-based, collaborative simulation that mirrored real-world supply chain scenarios.

The exam required students to work together to make strategic supply chain decisions using a virtual simulation that focused on the global supply chain for e-skateboards. This allowed the students to interact with suppliers and customers from around the world in a controlled, immersive environment. Students had the opportunity to learn about the complexities of managing a supply chain, the impact of their decisions, and how to improve decision quality in real-time.

Their journey began with the analog Beer Game, a classic exercise in supply chain dynamics. From there, they transitioned into the virtual world, taking on various roles such as ordering, assembly, and shipping, each critical to the successful management of a supply chain. Throughout the course, they played multiple rounds, gaining hands-on experience that culminated in this final immersive simulation.

This initiative marks the first time our students have taken a final exam using HITeC, and the results were impressive. The students successfully navigated the challenges of the virtual environment, supported by a dedicated development team, including virtual teaching assistants live from France.

Ghala Alhajri, Georgia Tech Language Institute student and SABIC Foundation Year Program participant reflects, "We got practical, hands-on experience that will help us in our future job roles at our company, SABIC (Saudi Arabian Basic Industries Corporation). The VR experience showed me how technology can impact our lives in a positive way, and I understood the importance of communication in the field of supply chain management."

Our collaboration with IMT and the work in the Physical Internet (PI) lab at Georgia Tech demonstrates the global reach and cutting-edge nature of the supply chain education we offer. The success of this pilot program highlights the value of blending technology with education to create meaningful, real-world learning experiences.

We are excited to continue modernizing our courses and leveraging platforms like HITeC to ensure that our students are not only prepared for the challenges of today’s supply chain but are also equipped to lead in the supply chain of the future.

Stay tuned for more updates on our educational innovations and how we continue to shape the next generation of supply chain leaders.

Why Organizations Choose Georgia Tech

Organizations turn to us for talent development solutions for several reasons:

A Balance of New and Experienced Professionals: Managing talent means addressing the needs of both emerging professionals who bring fresh energy and experienced workers who provide deep institutional knowledge. Our programs cater to this balance, offering foundational courses for newcomers and advanced training for seasoned leaders. 

A Competitive Edge in Attraction and Retention: Offering world-class development opportunities signals to current and prospective employees that your organization values growth. This commitment is especially critical in today’s job market, where career development ranks high on employees’ priorities. 

Practical, Immediately Applicable Training: Adult learners need training that works in tandem with their day-to-day responsibilities. Our modular programs are designed for immediate real-world application, ensuring learning outcomes translate directly into workplace improvements. 

Scalable Solutions for All Organizations: For growing companies, introducing structure and formal training is often the next step in their evolution. For larger enterprises, we complement internal training programs with flexible, impactful learning options that align with organizational goals.

What Makes Our Offerings Unique

We deliver training solutions tailored to the realities of today’s supply chain and logistics landscape, setting us apart in the industry. Here’s how: 

Flexible Delivery Options: From self-paced courses to live and virtual classes, public programs, and custom corporate training, we offer a variety of formats to meet your needs. For example, our hybrid Engineering the Warehouse course combines online lectures with in-person lab sessions to maximize convenience and impact. 

Bite-Sized, Modular Learning: Our modular approach allows professionals to access content in manageable segments, enabling learning alongside work demands. For instance, our series on supply chain analytics is broken into short, focused modules that let learners immediately apply concepts like inventory optimization and demand forecasting. 

Innovative and Relevant Content: We stay ahead of the curve by addressing emerging industry trends. Our new course on Generative AI in Supply Chain equips professionals to leverage advanced technologies for process optimization and strategic planning. 

Industry-Informed Solutions: Collaboration with industry leaders ensures our content addresses real-world challenges. For example, our program on Supply Chain Risk and Resilience integrates insights from Fortune 500 companies to help businesses mitigate disruptions effectively. 

Grounded in Research: Every program is informed by leading academic research and designed to reflect the best practices of adult learning, ensuring your team gains knowledge that is both current and actionable.

Preparing for 2025: A Competitive Advantage

As we approach 2025, talent development remains central to addressing the challenges of the supply chain industry. Large enterprises continue to seek solutions to skill gaps and organizational transformation, while small and mid-sized organizations increasingly recognize the need for formalized training. Georgia Tech’s offerings serve as a vital resource, ensuring professionals stay competitive, skilled, and current in an ever-evolving landscape.

Investing in your workforce today not only ensures your organization’s readiness for tomorrow’s challenges but also signals a commitment to your team’s growth and success. At Georgia Tech, we are proud to partner with companies of all sizes, providing a unique blend of flexibility, innovation, and industry relevance that drives results. 

Whether you need a program to supplement your internal training, build a comprehensive development strategy, or prepare your team for the future, we’re here to help. Contact us at info@scl.gatech.edu to learn more about how we can support your talent development needs. 

Let’s work together to ensure your supply chain workforce is ready to lead in 2025 and beyond.

As Managing Director of the Supply Chain and Logistics at Georgia Tech, I’ve seen firsthand how development planning can elevate individual careers, strengthen teams, and improve organizational resilience. However, the key to making it work lies in balancing the demands of day-to-day operations with actionable, targeted development efforts.

The Reality of Development Windows

The structure of the working calendar doesn’t make development planning easy. Between the end-of-year holiday season and summer vacation months, supply chain professionals face two primary windows for development:

• Spring (February through May): Coming off the end-of-year slowdown, spring provides the first extended opportunity to focus on growth.
• Fall (Mid-August through Mid-November): After summer, fall offers a second chance to refocus before the holiday rush begins.

For supply chain professionals, these windows represent critical periods to upskill and prepare for the evolving demands of the industry. The spring window is upon us, making now the perfect time to act with urgency and purpose.

The “Why” of Development Planning

In supply chain, the "why" behind development planning is straightforward: the industry is changing faster than ever. New technologies, shifting global trade patterns, and the increasing complexity of operations demand professionals who are both technically skilled and strategically agile.

The supply chain leaders of tomorrow must excel in areas like:

• Data and Analytics: Understanding data and leveraging it for decision-making is no longer optional.
• Automation and Technology: From warehouse robotics to AI-powered forecasting, supply chain professionals need to be tech-savvy to stay relevant.
• Resilience and Risk Management: Building robust supply chains capable of withstanding disruption is now a core competency.

The “What” of Development Planning: Key Focus Areas

Development can be broken into two primary areas:

1. Core Competencies (In-House):

• Communication: Clear, concise, and persuasive communication is critical for collaboration.
• Problem-Solving: Supply chains are inherently complex, and professionals must excel at diagnosing and resolving issues.
• Leadership and Teamwork: Even non-managers need strong leadership and collaboration skills to succeed in today’s cross-functional environments.

Here is a link to one of the best competency guides out there: FYI Resource Center

2. Technical and Operational Skills:

• Advanced Analytics and Visualization: Skills in tools like Power BI, Tableau, or Python are becoming industry standards.
• Supply Chain Systems and Automation: Understanding the functionality and implementation of WMS, TMS, and other critical systems is vital.
• Sustainability and Compliance: Professionals need to navigate increasingly complex sustainability requirements and global regulations.

Beyond these newer technical areas, there remain significant gaps in the application of many core supply chain processes—gaps that cannot be overlooked:

• Production and Inventory Planning: Effective planning processes are critical, yet many organizations struggle to optimize them to balance demand and capacity.
• Warehouse Operations and Optimization: Opportunities remain to improve material flow, labor efficiency, and space utilization in warehouse environments.
• Manufacturing Asset Reliability and Output: Ensuring consistent and reliable equipment performance is essential to maintaining throughput and meeting customer expectations.
• Tradeoff Analysis for Purchasing Decisions: Striking the right balance between low cost, resilience, and sustainability is an increasingly complex challenge, especially in the face of rising customer and consumer pressure for speed and service.

A Quick Action Plan Using the 70/20/10 Model

For supply chain professionals with limited time and access to leading practices, the 70/20/10 model offers a practical framework for development:

• 70% Experiential Learning: Apply learning directly in your work.
• 20% Social Learning: Learn from others in your network or organization.
• 10% Formal Learning: Invest in structured learning opportunities.

Please see attached figure 1 for Development Plan Example to improve Warehouse Operations Capability

Here is a link to a free Individual development GPT in Chat GPT: Individual Development Plan Builder

Call to Action: Take 30 Minutes to Plan Today

For busy professionals, the biggest hurdle to development planning is often finding the time. But a well-crafted development plan doesn’t have to take hours. Here's how you can get started in just 30 minutes:

1. Reflect on Your Growth Needs (10 Minutes): Where do I need to grow most?
2. Set Three Development Goals (10 Minutes): Identify experiential, social, and formal learning goals.
3. Identify Next Steps (10 Minutes): Write down one immediate action for each goal.
4. Schedule time with Manager to review proposed plan and schedule monthly check-ins

Development as a Competitive Advantage

The pace of change in supply chain operations is relentless, but professionals who make development a priority can turn that challenge into a competitive advantage. By leveraging the 70/20/10 model and focusing on intentional, actionable planning, you can position yourself—and your team—for success.

Don’t let this spring window pass without taking steps toward growth. Whether it’s mastering a new technology, improving core processes, or navigating tradeoff decisions, the time to act is now. If your growth plan includes professional education, consider how the Supply Chain and Logistics Institute and Georgia Tech Professional Education might benefit you!

AI Agents and Decision Intelligence

AI is moving beyond forecasting and analytics into autonomous decision-making. AI agents can rapidly process complex scenarios—such as supply disruptions—and generate optimal responses in real time. This shift reduces reliance on manual problem-solving and enables organizations to respond faster and with greater accuracy. These AI-driven systems also make insights more accessible, allowing non-technical professionals to interact with advanced analytics in natural language.

Georgia Tech’s Supply Chain and Logistics Institute is offering education in Generative AI for supply chain, helping professionals understand and apply these tools effectively. The key takeaway? AI isn’t just for data scientists—it’s becoming essential for all supply chain professionals. Investing in AI literacy and decision intelligence training will be critical to staying relevant in the field.

Physical Automation: AMRs Reshaping Warehouses

Automation in warehouses is no longer experimental—it’s here and delivering results. Autonomous mobile robots (AMRs) are replacing traditional automation solutions, offering greater flexibility and adaptability. Unlike AGVs, which rely on fixed paths, AMRs navigate dynamically using AI and real-time mapping, making them well-suited for evolving warehouse environments.

Companies deploying AMRs report increased throughput, reduced labor costs, and improved safety. These robots optimize workflows, assist human workers, and enable 24/7 operations. Georgia Tech researchers are developing human-collaborative robotics, reinforcing that the future is about augmenting—not replacing—workers. Supply chain professionals should focus on developing skills in automation management and AI-driven operations. Understanding how to integrate these technologies into workflows will be a key differentiator.

Data Management: The Foundation for AI and Automation

AI and automation depend on high-quality, well-integrated data, yet many organizations struggle with fragmented systems and poor data governance. Industry surveys consistently highlight that supply chain leaders cite data silos and quality issues as top barriers to digital transformation. Without a strong data foundation, even the best AI models and automation solutions will fail to deliver their full potential.

Modern supply chain visibility platforms and AI-powered analytics tools are helping companies consolidate data for better decision-making. Georgia Tech researchers are advancing digital twin models that simulate supply chain networks, but these rely on robust data integration. For professionals, this underscores the need to develop data literacy and analytical skills. Those who can navigate, interpret, and leverage data effectively will be indispensable in AI-powered supply chains.

Call to Action: Personal Development and Strategic Planning

Emerging technologies in supply chain—AI, automation, data analytics, and logistics AI—are no longer futuristic concepts. They are delivering tangible benefits now, and the gap between early adopters and laggards is widening. If these innovations are not on your radar, you need to take action.

Where to Start:

• Invest in Personal Development: AI, automation, and data skills are becoming core competencies. Take relevant courses, attend industry events, and seek practical experience.
• Assess Business Applications: Identify where these technologies can solve current challenges and improve efficiency in your supply chain.
• Build Data Competency: Understanding how to structure and leverage data is foundational for AI and automation success.
• Experiment with Emerging Tech: Pilot AI-driven decision tools, AMRs, or logistics optimization models to gain insights into their potential.

The future of supply chain management is being reshaped by these technologies, and those who prepare now will define the next era of supply chain excellence. The question is no longer if these tools will impact the industry—it’s how quickly you can learn to use them to your advantage.

The Core Challenge: Complexity Crowds Out Curiosity

In my time in industry, I’ve seen high-stakes decisions unfold under tight timelines. The rigor is there: financial models, market analysis, legal due diligence. But the same pressure that brings focus often narrows the field of vision. Once the strategic goal is clear, the push becomes “get the recommendation ready” or “get the deal done.” Often, the team disbands before the ripple effects have even begun to appear.

In fact, studies of managerial behavior find that decision-makers often prioritize short-term outcomes over long-term implications, making it easy to overlook those downstream impacts.

We rarely paused to ask:

• What happens to our partners, our systems, or our people two or three steps down the line?
• Are we shifting bottlenecks or creating future misalignments?
• Could this solution lock us into a path that becomes hard to reverse?
• Will we be happy with this decision in 5 years?

Not asking these questions isn’t negligence. It’s often a result of how we structure decision processes: focused, time-bound, and oriented toward closure.

When Good Decisions Still Cause Trouble

Let's make this real. I've seen:

• Procurement strategies that focused on driving down cost but over time forced suppliers to reduce investment in quality and continuous improvement resources—eventually leading to a significant quality issue for a key customer.
• Multiple outsourcing efforts that reduced future capital requirements but also reduced flexibility in scheduling and responsiveness to rapid demand shifts or new product innovation.
• Plant closures that optimized total network cost on paper but not in reality, because the remaining plants were not actually equipped to take on more volume and increased complexity.
• A new warehouse management system implementation that promised efficiency gains but created chaos in distribution—not because the software was flawed, but due to unforeseen complexities during implementation.

In each of these, the first-order decision was sound. But the downstream effects caught teams off guard, requiring backtracking, remediation, and even reputational repair.

Even recently, retailers trying to fix 2021 product shortages by ordering more stock found themselves “overwhelmed with inventory” in 2022 when demand eased—a textbook second-order surprise. Likewise, logistics executives admitted they “didn’t anticipate” that 2020’s e-commerce boom would spark a warehouse labor crunch—a side effect that underscores how easily ripple effects can catch us off guard.

Why This Matters—and Why It's Often Skipped

Let’s be honest. Most leaders are moving fast. The idea of adding more process—or imagining abstract future problems—can feel like a luxury. Typical objections sound like:

• "We don't have time for hypotheticals."
• "That's someone else's job—let's just move."
• "We'll deal with it if it becomes a problem."

But here’s the catch: in a complex system like a global supply chain or a tightly coupled stakeholder network, second-order effects are not edge cases—they're part of the landscape.

In fact, recent research in supply chain management finds that such second-order effects are likely ubiquitous and must be anticipated rather than ignored. Ignoring them doesn’t make them go away. It just delays the pain—and multiplies the cost.

Where This Applies in Supply Chain

These second-order thinking practices are especially useful in supply chain decisions where complexity and interdependencies are high. Think about:

• Network redesigns or footprint consolidation
• Sourcing shifts or dual sourcing strategies
• Technology implementations like a new TMS or WMS
• Inventory policy changes that affect fulfillment, customer service, or working capital
• Sustainability initiatives that touch suppliers, packaging, and compliance

Each of these decisions may seem straightforward at first glance, but often carry ripple effects that only surface months later—making this kind of foresight not just useful, but essential.

A Pragmatic Playbook: Small Steps, Big Impact

To embed this thinking into your organization’s DNA, you don’t need to launch a task force. You need lightweight, repeatable tools that shift how teams think. Here are a few that punch above their weight:

✅ Pre-Mortem Workshop

• Time: 60–90 minutes
• What It Is: Imagine the decision failed spectacularly. Ask: what went wrong?
• Value: Surfaces hidden risks early and creates a safe space for dissent.

"This is an insurance policy, not red tape.”


✅ Ripple Mapping

• Time: 1–2 hours
• What It Is: Visually chart the impact of a decision across systems, partners, and people.
• Value: Turns abstract consequences into visible risks and opportunities.

"Helps teams see around corners—and ask better questions.”


✅ Mini FMEA (Failure Modes and Effects Analysis)

• Time: 60 minutes
• What It Is: Identify how key decision elements could fail and what to do about it.
• Value: Helps prioritize monitoring and mitigation during rollout.

"Adapt it from engineering—it works just as well for strategic moves.”


✅ Early Warning Indicators

• Time: Minimal setup, integrated into standard dashboards
• What It Is: Define and track metrics tied to second-order risks (e.g., employee attrition, service delays).
• Value: Helps you course-correct before small issues become systemic.

"It's not just about making the right decision—but making the decision work.” 

Culture Shift: From Transaction to Trajectory

The real unlock comes when we shift the definition of a successful decision. It’s not just about getting a green light. It’s about ensuring the decision holds up over time—operationally, culturally, and reputationally.

To institutionalize this mindset:

• Add a "second-order checkpoint" to strategic review decks or governance templates
• Ask for a "consequence map" alongside the business case
• Celebrate teams who surface risks early, not just those who execute quickly
• Conduct post-mortems (not just pre-mortems) to harvest lessons

"Strategic foresight is not about predicting everything. It's about avoiding the predictable surprises.”
 

Backed by Big Thinkers

This isn't just operational wisdom—it's grounded in thoughtful literature:

• Peter Senge, in The Fifth Discipline, emphasizes how organizations struggle when they fail to see the system-wide consequences of localized actions.
• Nassim Nicholas Taleb, in Antifragile, argues that systems become more vulnerable when decisions are made without consideration for stress-testing and adaptive feedback loops.
• Cass Sunstein, writing on regulatory and policy decision-making, promotes the idea of "decision hygiene”—a systematic process to reduce bias and surface risk.
• Atul Gawande, in his book Better and in his commencement address at Stanford, shared how the habit of asking "just one more question" often uncovered crucial, overlooked insights—just like the disheveled detective Columbo. That final question, the one nobody else asks, frequently makes the difference between surface-level understanding and meaningful action.

Sometimes the last question is the best one. The more complex our systems become, the more important it is to keep asking until we find what we didn’t know we were missing.

Closing Thought: Be the Person Who Asks One More Question

As supply chains become more interconnected and policy environments more volatile, decision quality will increasingly depend on ripple-awareness. You don’t need perfect foresight. But you do need a culture that pauses—briefly—to ask: what might happen next?

Those few extra minutes may be the difference between a great decision—and a regrettable one.

Assessing Risk: The First Step

A critical starting point for risk management is assessing the risks specific to you or your business. For individuals and small businesses, this process doesn’t have to be exhaustive. Rapid risk assessments can identify the most significant vulnerabilities with minimal effort, like assessing how a hurricane or supply chain disruption might impact access to essentials such as power or food. Larger businesses or municipalities might benefit from more systematic assessments, which can be conducted as part of an annual review.

Appetite for Risk vs. Potential Impact

Once risks are identified, it's important to balance your appetite for risk with the potential impact. An individual might be able to weather a short-term power outage, but a logistics provider or hospital must maintain continuous operations. For businesses, supply chain vulnerabilities—especially single-source suppliers—present a significant risk. By understanding where dependencies lie and preparing contingency plans, businesses can significantly reduce potential disruptions.

Low or No-Regrets Actions

The next logical step is to focus on low or no-regrets actions. These are relatively simple actions that provide immediate benefits with little downside. For individuals and families, this can be as straightforward as ensuring access to working flashlights, batteries, and emergency staples like water, rice, and beans to last at least a week.  Developing communication plans with family or neighbors is another critical preparedness step that costs very little but can be lifesaving.

For businesses, conducting an annual risk review is a no-regrets action that can identify critical risks and supply chain weaknesses. For single source suppliers, it may not be easy or practical to find a second supplier.  If not, go deep on that supplier and understand their upstream risks and ensure they are focused on risk mitigation. Small businesses can often a risk review in just a few hours, while larger organizations may need a more comprehensive review. Understanding infrastructure risks—such as power, water, and data reliability—is essential for businesses of all sizes. With each major disruption, such as wildfires or hurricanes, we see large companies caught off guard, often due to inadequate preparation for these well-known risks.

Tools and Resources for Deeper Risk Management

1. Failure Modes and Effects Analysis (FMEA)

FMEA is a widely used tool that helps businesses identify where and how processes might fail. It evaluates the severity, likelihood, and detectability of different failure points, allowing businesses to prioritize actions. In supply chains, FMEA is invaluable for identifying single-source suppliers or fragile logistical routes that could break down under pressure.

2. Business Impact Analysis (BIA)

BIA assesses the potential effects of a disruption on business processes. By identifying critical functions that must continue during an emergency, BIA helps businesses prioritize resources and plan for worst-case scenarios. This is especially useful for small businesses with limited resources, as it pinpoints where to focus recovery efforts during a crisis.

3. Risk Heat Maps

A risk heat map offers a visual way to assess risk by plotting the likelihood and potential impact of various disruptions. By color-coding risks, businesses can quickly see which areas require immediate attention. These maps are especially useful when making quick decisions in the face of a crisis, such as prioritizing responses to supply chain issues or extreme weather events.

4. Scenario Planning

For businesses with complex supply chains or operations, scenario planning helps explore different risk scenarios and develop flexible response strategies. This approach allows businesses to stay agile, with contingency plans ready for natural disasters, industrial actions, or global supply chain disruptions.

Structured Actions: Resources and Support

For those looking to dive deeper into risk management, there are several resources and programs available:

Executive Education Programs: For supply chain professionals, attending executive education programs such as those offered by Georgia Tech’s Supply Chain & Logistics Institute can provide in-depth knowledge and strategies for managing risk. These programs often cover real-world case studies and actionable risk management strategies.

Federal and State Resources: Agencies like the CDC provide accessible resources for disaster preparedness, such as the Zombie Survival Guide, a lighthearted yet effective framework for emergency planning. FEMA also offers guides for Business Continuity Planning (BCP), helping organizations design robust continuity strategies.

State Economic Development Agencies: Many state agencies, chambers of commerce, or small business associations provide business continuity support tailored to specific regions. For example, states prone to hurricanes or wildfires often provide detailed guides on how to prepare for natural disasters and mitigate infrastructure risks.

Building a Resilient Future

The key takeaway for both individuals and businesses is that resilience starts with proactive action. For individuals, preparedness may be as simple as having an emergency kit and communication plan in place. For businesses, risk management should be part of a structured, ongoing process. Annual reviews, risk assessments, and low-regrets actions can protect against significant disruptions, ensuring continuity even in the face of unpredictable events. By incorporating readily available tools and resources, we can all build a more resilient future, whether in supply chain operations, daily life, or community preparedness.

 

The conference brings together researchers from across the southeast to present the best new health-related studies and build collaborative relationships. This year's conference celebrated the latest advancements in preclinical, clinical, implementation, and population-based research. 

Among the award winners at this year’s conference were ISyE PhD students Meghan Meredith and Jingyu Li, who each showcased their recent research.

Meghan Meredith earned the Outstanding Oral Presentation Award for her research titled "Identifying Regions that Are Vulnerable to Obstetric Unit Closures in Georgia Using Mathematical Optimization." Meghan’s study addressed the growing issue of rural hospital closures, particularly obstetric units, which make it harder for pregnant people in rural areas to access timely maternity care. 

By using mathematical optimization models, Meghan identified which hospital closures would have the largest impacts on travel distances for rural populations and proposed ways the government could allocate subsidies to keep them open. Her research is crucial for ensuring better access to high-quality obstetric care, especially for those living in rural Georgia. 

Meanwhile, Jingyu won 1st Place Poster in Public Health for her project titled "Examining Perinatal Regionalization in Practice: A Network Analysis of Maternal Transport in Georgia." Her work focused on how maternal transport is coordinated in Georgia, particularly for women in rural areas who need to be transferred to hospitals that can provide appropriate care. 

Jingyu analyzed birth records from 2017 to 2022 to map out transport routes between obstetric facilities and discovered that transport rates were highest in certain rural areas, indicating limited access to proper care in those regions. 

Her research also found that the state’s designated perinatal regions didn’t always align with how maternal transport actually occurs in practice. Jingyu suggested that redesigning these regions could improve access to the care pregnant people need.

Both students were praised for their recent research, which tackles real-world problems in maternal healthcare in the state of Georgia. Meghan and Jingyu’s research not only demonstrates their academic excellence but also their commitment to improving healthcare systems in Georgia. 

Their awards at the Southeast Regional Clinical and Translational Science Conference highlight how researchers in ISyE are innovating to improve healthcare systems.

Meghan and Jingyu are both advised by Dr. Lauren Steimle, who is the Harold R. and Mary Anne Nash Early Career Professor in ISyE.

The H. Milton Stewart School of Industrial and Systems Engineering (ISyE), in collaboration with the Center of Academic Success and Engagement (CASE), will be hosting a series of events recognizing alumni and their contributions to industrial engineering.  

This semester 17 ISyE senior design teams were showcased in the Capstone Design Expo, competing against over 100 teams.  

Join us in celebrating the incredible legacy of Professor Alexander Shapiro at ShapiroFest! 

One of these students, Yuming Sun, later joined the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) Ph.D. program, under the guidance of Professors Pinar Keskinocak and  Lauren Steimle. Sun embarked on a journey that would seamlessly blend academia and public health, leading to important contributions in the fight against polio. 

Yuming’s dedication and innovative approach, which has also been supported by key collaborators from the Centers for Disease Control and Prevention (CDC), earned him many recognitions for his research, including Honorable Mention as a Graduate presenter in the Medicine and Public Health category at the 2024 American Association for the Advancement of Science (AAAS) Annual Meeting. 

The AAAS supports the advancement of science, engineering, and innovation across the globe – while recognizing and fostering diverse research solutions for all.

Yuming’s research on “Modeling the Circulating Vaccine-Derived Poliovirus Outbreaks and Interventions” explores the complex dynamics of polio outbreaks and the effectiveness of various vaccination strategies, particularly in under-vaccinated communities.

Tackling Polio 

What began as a class project blossomed into a fully funded development, driven by the promising results of the team’s initial work. Later on, advanced by Sun, was an established detailed model of poliovirus transmission, sought to balance scientific rigor with practical applicability. 

The team looked at the widespread use of the oral polio vaccine (OPV) in outbreak response, which while effective, has unintended consequences in under-vaccinated communities. The live attenuated virus in OPV could revert to a form that acts and spreads like wild poliovirus. A new novel type vaccine was created which has less risk of reversion, but the role of this new vaccine in outbreak response, was unclear.

The model has several features capturing the complex dynamics of polio transmission, such as varying risk across subpopulations defined by age and geography, waning immunity - induced by prior infections or vaccinations - and virus reversion. 

They grouped regions based on geographic location, historical vaccination coverage, and accessibility, creating a nuanced framework to understand and predict polio outbreaks. 

The COVID-19 pandemic further compounded these issues by disrupting routine immunizations and delaying outbreak response campaigns, leaving many individuals unvaccinated and vulnerable.

The model also incorporated the decreased population mixing during COVID-19 lockdowns, reflecting the pandemic's profound impact on public health efforts. 

While the model is general and can be applied to any country or region, the team used data from northern Nigeria for model calibration, given the outbreaks in the region and under-vaccinated children in hard-to-reach areas. 

In an extensive computational study, the team evaluated various “intervention” scenarios, generating interesting results and insights. 

By collaborating closely with the CDC and leveraging real-world data, the team aimed to provide actionable insights that could guide strategies to eradicate polio in Nigeria and prevent its resurgence in neighboring countries.

“Our results emphasized the importance of novel OPV type 2 in reducing the size of outbreaks,” said Sun. The research also highlighted the need for “more rounds of outbreak supplemental immunization activities during outbreak response in under-vaccinated regions, which exhibit persistent transmission and delay the progress towards stopping outbreaks.” 

From a logistics perspective, “a quicker outbreak response would avert more paralytic cases and require fewer supplemental immunization rounds to stop the outbreaks,” added Sun.

Yuming’s journey from a classroom project to a pivotal public health initiative highlights the importance of hands-on learning activities, demonstrating the power of collaboration and the significant impact of advancing research to addressing real-world problems.

As the battle against polio continues, Yuming Sun and their team's work serves as a supportive contribution to the ongoing efforts led by the Global Polio Eradication Initiative (GPEI) of which CDC is a partner.

While their enthusiasm, innovation, and commitment to public health are commendable, they recognize that there is still much work to be done alongside long-standing collaborators in the fight against infectious diseases.

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Camille Carpenter, ISyE Communications Manager

Recently published in the INFORMS Journal Manufacturing & Service Operations Management, their research calls for transparency in the Medicare Advantage (MA) program. 

Their findings share that Medicare Advantage Plans adjust and reallocate funds inappropriately by implementing strategic cross-subsidization, which directly shifts the quality of care between high-risk and low-risk patients. 

With MA Plans supporting over $2 million enrollees, they’ve provided the first empirical evidence of strategic cross-subsidization happening within a large commercial insurance database. 

Ayer collaborated with faculty researchers, Zhaowei She (Singapore Management University), Bilal Gokpinar (University College London), and Danny Hughes (Arizona State University), to study and address the need for Medicare reform and regulating ongoing health equities.

"This study underscores the urgent need for enhanced transparency in Medicare Advantage. The practice of strategic cross-subsidization we've uncovered could exacerbate socio-economic inequalities in healthcare access and outcomes, highlighting the critical importance of rigorous oversight in capitation payment models."

Examples of this can be seen when individuals become ill or considered high-risk, however the healthcare plan may suggest spending less resources on the patient. These specific findings have the potential to alert policymakers and encourage enforcers to revisit the structure behind MA Plans. 

By revealing this unknown issue of resource misallocation, these types of solutions may have the ability to impact millions of beneficiaries across the entire Medicare Advantage system.

To learn more about their research and the full story, read here.

To read their published paper: https://pubsonline.informs.org/doi/10.1287/msom.2023.0637

About INFORMS and Manufacturing & Service Operations Management 

INFORMS is the leading international association for data and decision science professionals. Manufacturing & Service Operations Management, one of 17 journals published by INFORMS, is a premier academic journal that covers the production and operations management of goods and services including technology management, productivity and quality management, product development, cross-functional coordination, and practice-based research. More information is available at www.informs.org or @informs.

Turgay Ayer co-authored the study with his former PhD student, Zhaowei She (now on the faculty at Singapore Management University), as well as Bilal Gokpinar (University College London) and Danny Hughes (Arizona State University). 

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Camille Carpenter, Communications Manager

Keskinocak is the William W. George Chair and Professor and serves as ISyE’s associate chair for faculty development. 

She will be ISyE’s ninth permanent chair, leading a school renowned for its top-ranked graduate and undergraduate industrial engineering programs. U.S. News & World Report has consistently ranked ISyE as the nation's best since the mid-1990s.

“Pinar is a proven and respected leader both on campus and within her academic and research community,” said Raheem Beyah, dean of the College of Engineering and Southern Company Chair. “She is well-positioned to continue advancing ISyE’s national prominence and accelerate the School’s trajectory.” 

Read the full story here.

At this year’s annual Institute for Operations Research and the Management Sciences (INFORMS) conference, multiple Georgia Tech Industrial and Systems Engineering faculty and students were awarded and recognized for their contributions to the field. 

Faculty Awards

Pinar Keskinocak, William W. George Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) received both the prestigious INFORMS President’s Award and the George E. Kimball Medal. 

The INFORMS President's Award honors her exceptional contributions to the welfare of society and distinguished service to the organization and the broader profession.

The George E. Kimball Medal represents long, tireless and visionary contributions with distinguished service to society and the INFORMS community.  

The Frederick W. Lanchester Prize, awarded for the best recent contribution to operations research and management sciences published in English in the past five years, was presented to Professor Arkadi Nemirovski.

For his work on "Statistical Inference via Convex Optimization", Nemirovski provides a modern perspective on the connection between convext optimization and high-dimensional statistics, commonly used in machine learning.

In the Transportation Science and Logistics Section, the Best Paper Award went to Alexander M. Stroh, Alan L. Erera, and Alejandro Toriello for their exceptional research in transportation science.

After 20+ years in academia, Meller pivoted to industry and now stands as the Chief Scientist at FORTNA with over 10 years of experience overseeing researchers developing algorithms, analysts performing data analysis and design simulations, and solution architects designing distribution centers for some of the world’s largest brands.

At FORTNA, Russell Meller is at the cutting edge of complex distribution centers, employing automation, artificial intelligence, and advanced simulation and emulation technologies. This October, he will take the stage at H. Milton Stewart School of Industrial and Systems Engineering (ISyE), and dive into his experiences at the LeeAnn and Walter Muller Distinguished Lecture Series.

With great anticipation, From Academia to Industry: Observations of a Traveler, will share Meller’s unconventional career path, and the lessons learned along the way.

As technology continues to transform industries like supply chain and logistics, the need for professionals who can translate academic theory into practical solutions is more crucial now than ever.

Meller holds a B.S., M.S., and Ph.D. in Industrial and Operations Engineering from the University of Michigan. In addition, he was elected in 2020 to the National Academy of Engineering (NAE), in part for his leadership in scaling design methodologies for distribution centers at FORTNA.

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For more information: the lecture will be hosted on Tuesday, October 29 at 3:30pm in the Georgia Tech Marcus Nanotechnology Building, Room 1116-1118.

A reception will be held in the atrium, where all students, alumni, faculty and staff are all welcome to attend. 

RSVP here: https://eforms.isye.gatech.edu/2024-distinguished-lecture-series

Read abstract and speaker bio: https://www.isye.gatech.edu/events/calendar/day/2024/10/29/11728

Read the full story here.

Notably, the undergraduate program has been ranked best in the nation for 24 consecutive years and 34 years for the graduate program.

Since inception, ISyE's program achievements have not only propelled its own growth but have also laid the foundation for broader advancements within the College of Engineering (CoE). The college had an impressive overall ranking this year placed at No. 4 overall engineering, and No. 2 among public universities.

ISyE’s commitment to expanding the programs and workflow within systems has continued to be recognized on a national scale that reflects faculty advancement, student fellowships, and the growth for new building facilities. 

With the progression of ISyE’s next home at Tech Square Phase 3, and the school has positioned itself as a leader within the institution to further scale the growth and support of our students and programs. 

The ISyE undergraduate program prepares students with the necessary skills and mindset to take on big pharma, finance, logistics and global consulting. 

Nearly 76% of undergraduate students complete the program with an accepted job offer, starting at a median annual salary of $85K. 

For a detailed breakdown of the CoE rankings, read the full story here.

In this role, Nazzal will be a key member of the CHHS leadership team, co-leading efforts to fulfill the center’s vision of “transforming decision-making and enhancing the efficiency and effectiveness of health and humanitarian systems.” She will collaborate closely with CHHS faculty and partners to guide the development and implementation of strategic initiatives that advance the center's mission.

“We are thrilled to have Dr. Nazzal in this leadership role and are confident that her expertise will drive impactful initiatives that support the center’s mission to improve health and humanitarian systems worldwide” said Dr. Pinar Keskinocak, CHHS Director and William W. George Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech.

Nazzal's responsibilities will include:

• Co-leading CHHS’s strategic planning and management to execute its mission.
• Overseeing the Health and Humanitarian Supply Chain Management Professional Education Certificate program (HHSCM), ensuring its continued excellence and growth.
• Developing educational materials for undergraduate, graduate, and executive education programs, including case studies, course modules, and classroom games.
• Identifying collaborative research and education projects.
• Leading and participating in research initiatives focusing on health equity, process redesign, and improvement in health systems.
• Promoting the dissemination of research findings through academic publications, conference presentations, and reports.
• Advising and mentoring students and project teams on research and professional development.

Nazzal has been an active faculty member in ISyE and has had numerous affiliations with CHHS prior to this appointment. Her experience in healthcare and public health projects, combined with her passion for education and innovation, positions her perfectly to contribute to the center’s ongoing success.

Two teams completed senior design through the entrepreneurship-focused multi-disciplinary create-x capstone course. Teams explored and delivered solutions involving machine learning-based decision-support tools, system design, and predictive and prescriptive dashboards.” said Dima Nazzal, Director of Professional Practice and Senior Design coordinator and projects co-examiner.

“Every team delivered significant value to their client based on a thoroughly evaluated design solution. Much like every semester, narrowing down the top three is difficult,” said Leon McGinnis, Professor Emeritus and Senior Design projects co-examiner. “This is a testimony to the quality of the work our students produce, the strength of our curriculum, and the high standards we hold for ourselves and our students.” Nazzal and McGinnis added.

From the 24 ISyE teams that were judged at the Capstone Design Expo, three teams placed as finalists for the best of ISyE Senior Design teams: “Improving Coca-Cola's Concentrate Supply Chain”, “Georgia Power ‘Off the GRID’” and “Recruiting the Next.”   

Georgia Power’s “Off the GRID,” was the winner for the Spring 2024 Best of ISyE Senior Design.  

This team had a great challenge with their project, and they were able to methodically understand the system and provided a range of solutions, including redesigning system aspects.   

They were also outstanding in their professionalism and communication and had a strong endorsement from their client sponsor, Mr. Bill Harrop. Collectively, the group was awarded $1,500 with plaque recognition for the 2024 season. 

The second award category was Design with Implementation and Impact, sponsored by KS2 Technologies, featuring “Project Pelican Warehouse.” Finally, the third category featured ISyE Create-X project “PopUp Spaces”, which won Honorable Mention at the Capstone Design Expo.  

Senior Design Team, “Delta Tech Ops Pelican Warehouse” will receive $1,250 from the KS2 Technologies Design with Impact Award for their focus on implementable and piloted solutions with millions of dollars in value, at minimal investment. 

Category 1: Top 3 Finalists  

Client: Georgia Power 

Project Title: Georgia Power “Off the Grid” 

Team Members: Vaishnavi Duvvuri, Irene Feijoo, Annette Gisella, Shawna Kalladanthyil,  Ami Patel, Sreya Srinivas, Clara Wu, Shanru Xu 

Client Sponsor: Bill Harrop 

Advisor: Dr. He Wang 

 ISyE Senior Design team “Off the GRID” collaborated with the Georgia Power GRID Investment Program, a multi-year initiative aimed at enhancing service and reliability across Georgia’s energy grid. The team's mission was to implement a data-driven solution with both short and long-term strategies to reduce and prevent surplus inventory within the program. 

Grid Investment Program Overview: The initiative focused on improving the reliability of the worst-performing areas, with a goal of eliminating project risks and reducing existing surplus inventory. On average, 105 projects were completed per year, with 57% of the inventory value classified as surplus. 

System Dynamics: The team identified a cyclical process within the program: engineers estimated items for projects, procurement purchased with a buffer, construction-built projects, and the cycle repeated. 

Phase 1: Reducing Existing Surplus Inventory: The team developed an automated inventory cleanup tool with three recommended actions: clean, delete, and as is. By identifying surplus items and providing recommended actions, they targeted areas of opportunity such as item label discrepancies, existing buffer strategy inefficiencies, and communication gaps. 

Phase 2: Preventing Future Surplus Inventory: To prevent future surplus inventory, the team devised an improved buffer method aimed at increasing accuracy in estimating high-issue items. They also established a communication link between engineering and construction to streamline the process. 

Value Added: The team's efforts yielded significant results. Evaluation of recommended actions led to an $800k reduction in surplus inventory, while the cleanup tool identified $2M in disabled inventory. The improved buffer method had the potential to reduce surplus inventory by 75%, amounting to an overall impact of $43M identified as surplus.  

"Working across 3 different organizational units is a challenge,” Harrop said. Their circumspec analysis was impressive. They’ve created an invaluable tool to automate a previously manual process. This analysis will significantly improve our forcasting model.”  

Client: Coca-Cola 

Project Title: Improving Coca-Cola's Concentrate Supply Chain 

Team members: Sheza Chaudhry, Ayushee Kalura, Simran Kaur, Benjamin Liu, Mahzuza Rahaman, Michael Rizzo 

Client Contact: Saeed Siddiqi 

Advisor: Dr. Alex Shapiro 

“After seeing that Coca-Cola held the same safety stock across every type of inventory, we saw two opportunities: a SKU specific approach with the Kings Method Calculation, and a Multi-Echelon Network to guide a holistic creation of safety stock to mitigate risk and reduce cost.” shared Micheal Rizzo during their presentation.  

The applicability of this project to other parts of Coca-Cola that also use concentrate is noteworthy. 

“Concentrate is the most valuable part of our supply chain … but before this group arrived, we didn’t have the manpower for this high-stakes project,” Siddiqi said. “Impressed with this team – they were clearly articulate, took feedback well and communicated clearly both verbally and visually.” 

Client: Georgia Tech Football 

Project Title:  Recruiting The Next 

Team Members: Elijah Ballew, Isaac Barnett, Nathanael Barnett, Jihun Jeong, Sam Kent, Iris Kim, Amanda Lee, Cheuk Lo 

Client Contact: Pat Boyle 

Advisor: Dr. He Wang 

Client Pat Boyle emphasizes the project's significance, stating, "This is the future of college football and helps us with a dynamic world of recruiting."  

The core of the project lies in the development of two tree-based prediction models and Tableau dashboards, providing actionable insights for better player assessment. 

"These tools will lead to the evaluation of a larger and better fit candidate pool, allowing Georgia Tech to better predict and address roster overturn, ultimately leading to improved recruiting classes," Boyle explains. 

Category 2: Design with Implementation and Impact, sponsored by KS2 Technologies 

Client: Delta Airlines Tech Ops 

Project Title: Project Pelican Warehouse 

Team Members: Breanna Jones, Kelsey Marks, Kyle Parker, Esha Patra, Alex Pham, Melanie Webster, Anna Whitford, Megan Yi  

Client Contacts: Tyanna Pleasant, Aimee Smith 

Faculty Advisor: Dr. Nicoleta Serban 

Category 3: Featured ISyE Create-X project (Honorable Mention Winner at Capstone Expo) 

Project Title: PopUp Spaces 

Team Members: Kirti Bharadwaj (IE), Matthew Kaminsky (IE), Ayaan Momin (CompE), Garret Moore (IE), Bethanie Penna (IE), Keerthana Thotakura (CS), Kya Wiggins (IE)  

Faculty Advisor: Dr. Xin Chen   

We celebrate the remarkable achievements of these teams. Their innovative solutions not only showcased the transformative power of engineering but also underscored our commitment to shaping a brighter future through interdisciplinary collaboration and forward-thinking problem-solving. 

Nazzal's election follows years of service and leadership within the Georgia Tech community. A distinguished alumna, she earned her Ph.D. in Industrial Engineering from Georgia Tech in 2006. After Nazzal's return to campus as faculty, she quickly became known for her instructional excellence and received the Curriculum Innovation Award in 2021. In addition to her commitment to student success, Nazzal is known as an advocate for faculty, as demonstrated by her work as part of the campus Covid-19 Taskforce. As chair of the Faculty Executive Board, Nazzal leads the faculty in governance of itself, the curriculum, and Georgia Tech students. 

"Dima's election comes at a pivotal time for our academic community,” said Provost and Executive Vice President for Academic Affairs, Steve McLaughlin. “The charge of faculty governance is to represent the faculty’s interests and to work hand-in-hand with our administration to make Tech a better place for everyone. Her wealth of experience and commitment to faculty and academic success positions her well to lead the Faculty Executive Board as they seek to address the most pressing issues.”

Read the whole story here.

Yuming Sun, a Ph.D. student studying Operations Research at the H. Milton Stewart School of Industrial and Systems Engineering, has been honored with the 2023 Seth Bonder Scholarship for Applied Operations Research in Health Services.

The Seth Bonder scholarship is a prestigious student award in the INFORMS Health Applications Society, that promotes the development and application of process modeling and operations research analysis to healthcare design, delivery, and operations.

Officially unveiled on Sunday, October 15th at the INFORMS Annual Meeting Awards Banquet, Sun was recognized for his exceptional research addressing the urgent need to focus on the threats posed by “circulating vaccine-derived poliovirus” (cVDPV).

Pioneering Solutions in Polio Eradication

Sun’s research proposal emphasized the ongoing challenges in reducing polio transmission on a global scale and mitigating vaccine-derived poliovirus outbreaks -- offering hope for a polio-free world.

His work consists of modeling the spread of poliovirus in high-risk spaces, while investigating cost-effective options to stop, prevent, and end polio outbreaks.

“Vaccine-derived poliovirus outbreaks are a result of the live-attenuated viruses used in the oral polio vaccine (OPV) reverting to cVDPV in under-vaccinated communities. cVDPV leads to poliovirus transmission and potentially paralysis among infected individuals.”

A Visionary Collaboration

With his research advancement, Sun emerges as a trailblazer, potentially being the first ISyE student in over two decades to receive this revered award.

Under the guidance of his advisors, Pinar Keskinocak and Lauren Steimle, Sun has “closely collaborated with researchers in the Global Immunization Division at the CDC, and regularly incorporates their feedback into his models.”

The invaluable feedback from the CDC team has enriched the impact, positioning Yuming at the forefront of this critical research.

Aguirre’s primary interests revolve around tackling challenges in the domains of Causal Inference, Personalized Medicine, and Medical Decision-Making. He is grateful to be advised by Dr. Turgay Ayer and Dr. Gian-Gabriel Garcia, and his work aims to advance the field of machine learning in healthcare.

Joseph Boone, a recipient of the NSF Graduate Research Fellowship Program (GRFP) award, is interested in game theoretic optimization, logistics in contested environments, supply chain and infrastructure network resiliency, and applied statistics and simulation for risk-aware system design.

His primary research goals involve developing methods to solve complex, multilevel optimization problems that arise in optimizing supply chain and infrastructure networks against worst-case or adversarial disruptions. Joseph aspires to apply these methods in various fields, including military logistics, equity in healthcare, and disaster relief efforts.

Alina Gorbunova, a recipient of the NSF GRFP, focuses her research on systems monitoring, diagnostics, and prognostics using high-dimensional and high-variety data with machine learning and data analytics techniques.

Her research interests lie in creating a scalable causation-based quality improvement framework. This framework aims to monitor, diagnose, and control multistage manufacturing systems by leveraging high-dimensional and high-variety data. Gorbunova's work contributes to advancing the field of quality improvement in manufacturing systems through the application of machine learning and data analytics.

Engineers who are performing exceptional research and technical work in a variety of disciplines will come together for the two-and-a-half-day event. The participants — from the industry, academia, and government — were nominated by fellow engineers or organizations.  

Ayer also serves as the research director for healthcare analytics and business intelligence in the Center for Health & Humanitarian Systems at Georgia Tech and holds a courtesy appointment at Emory Medical School. 

Ayer's contributions to the field have also led to his role as a senior advisor to the Centers for Disease Control and Prevention (CDC), as well as his position as an associate editor for Operations Research, Management Science, and MSOM. Additionally, he has served as the past president of the INFORMS Health Application Society. 

His research focuses on healthcare analytics and socially responsible business analytics with a particular emphasis on practice-focused research. His research papers have been published in top tier management, engineering, and medical journals; along with being covered by popular media outlets, including the Wall Street Journal, Washington Post, U.S. News, and NPR. 

The symposium will be hosted by the University of Colorado, Boulder, September 10-13, 2023, and will explore four themes: 

•     Engineered Quantum Systems 

•     Mining and Mineral Resource Production 

•     Resilience and Security in the Information Ecosystem 

•     Complex Systems in the Context of Health Care 

Since the program’s inception in 1995, more than 5,000 early-career engineers have participated in previous symposia, many of whom have gone on to become national leaders in the engineering community. Georgia Tech is proud to partner with organizations like The Grainger Foundation to promote a vibrant engineering profession and public appreciation of engineering. 

Read the article in its entirety within the Scientific American website.

Keskinocak has long served as a leader with the Institute for Operations Research and the Management Sciences (INFORMS). A fellow with the institute, she has served as president, vice president of membership and professional recognition, and is the co-founder and former president of the INFORMS Section on Public Programs, Service, and Needs, and the president of the INFORMS Health Applications Society.

At Georgia Tech she has also served as the College of Engineering Advance Professor for six years and was a leading voice over the past three years of the Covid-19 pandemic. In addition to working with the Georgia Department of Public Health, she served on the Institute’s Covid task force helping to establish an institutional approach to the pandemic.

“It’s an honor, first of all, to have had the opportunity to serve,” she said. “Our communities at Georgia Tech and beyond are wonderful, so to be recognized among all of these outstanding contributors is a great honor.”

Keskinocak’s research focuses on the application of operations research and management science with society impact, particularly regarding health and humanitarian applications, supply chain management, and logistics. She is the director of ISyE’s Center for Health and Humanitarian Systems. Recent work has focused on infectious disease modeling in response to Covid-19.

Read more about Keskinocak’s latest research here: New Study Shows Hybrid Learning Led to Significant Reduction in Covid-19 Spread

A new study published in BMC Public Health shows that hybrid learning utilizing alternating school days for children offers a significant reduction in community disease spread. Total closure in favor of remote learning, however, offers little additional advantage over that hybrid option.

This research will help decision-makers in the event of another Covid-19 outbreak or one from a similar infectious disease.

“Early in the pandemic when school closures were becoming the norm, many debated the pros and cons of this measure,” said Pinar Keskinocak, the William W. George Chair and Professor in ISyE and the principal investigator on the study. “Do we get enough benefit to offset the social costs and impacts on education? This research shows that there is a benefit in infection reduction, especially in the absence of effective pharmaceutical interventions, and most of the benefits can be attained with a hybrid approach.”

This study is particularly relevant for the early days of an infectious disease outbreak when policymakers face the difficult decision of enacting school closures in their respective districts. Using an agent-based simulation model of Covid-19 spread, researchers projected the impact of various school reopening strategies: complete closure, alternating school days where one cohort attended in person twice a week and another cohort on the opposite days, younger children only, and regular (i.e. all students return to in-person learning).

Results showed that compared to schools reopening with regular attendance, the percentage of the population infected reduced by 13, 11, 9, and 6 percent with each respective strategy. The conclusions were that some level of closure – younger children only, alternating days, and completely remote – offers significant reduction in community-wide infections. The benefit of complete closure over a hybrid approach, however, was minimal.

The assumption in all cases was that individuals who contracted the virus would remain at home.

“The additional benefit of complete school closure compared to hybrid was relatively small,” Keskinocak said. “The implementation of an alternating day model can be challenging but could have public health benefits early in the pandemic or during a new wave, providing social and learning benefits as well.”

Other challenges remain that were not investigated in this particular research – costs on families in the event of school closures, learning tradeoffs, properly equipping students for virtual learning, and others. This is just one element of many for policymakers to consider, Keskinocak said.

CITATION: Arden Baxter, Buse Eylul Oruc, John Asplund, Pinar Keskinocak, Nicoleta Serban. Evaluating Scenarios for School Reopening under Covid-19. BMC Public Health. March 14, 2022.  https://doi.org/10.1186/s12889-022-12910-w

In addition to participating in the honors and awards banquet, Nazzal’s award will be published in the ISE magazine, as well as be featured on the IISE website.

The award is for developing an early design course, titled Cornerstone Design, which focuses on “framing the problem” without solving it. 

“The course lays out the foundation for design thinking using a project‐based learning approach, interactive sessions with instructors, and a goldmine of past capstone senior design projects that ISyE has kept for years organized in a database,” Nazzal explained. “That includes all the relevant data files, original team notes, deliverables, and code.”

Design aims to address the engineering design skill gaps by offering a learning environment that utilizes multiple past capstone senior design projects complemented with lessons on key engineering design and industrial engineering principles, Nazzal said of the study.

“Through multiple diverse projects, students develop the skill to structure the way they approach complex undefined problems that are fraught with data gaps, uncertainty and ambiguity in objectives, and conflicting priorities,” she said. “Students learn how to communicate the motivation effectively and succinctly for solving a problem and the scientific evidence supporting their design solution hypothesis.”

Nazzal has additional research that focuses on the control of discrete event logistics systems such as distribution systems, healthcare delivery systems, and manufacturing systems.

Current Ph.D. students Arden Baxter and Daniel Kim join Akane Fujimoto and Melike Yildirim as admits to the ORISE Research Participation Program at the CDC, an educational and training program designed to provide college students, recent graduates, and university faculty opportunities to connect with the center’s unique resources.

“These are all such fantastic students,” said William W. George Chair and Professor Pinar Keskinocak, advisor to all four students. “It’s a competitive program and for all four to be recognized in consecutive years, it says a lot about their work.”

Baxter, who will graduate in the summer, plans to join the ORISE program immediately and work with the CDC for the next year. Her work has included Covid-19 disease modeling and evaluating intervention strategies, as well as modeling for decision-making in humanitarian systems such as emergency response for resource coordination.

Kim will take a year off for the fellowship before returning to finish his thesis. He, too, has recent work on Covid-19. Other work includes incentive mechanisms to increase post-disaster debris recycling and analysis of data on mental health medication prescribed to children.

Fujimoto will complete the ORISE program this summer and return to ISyE to finish her Ph.D., with research focusing on various topics in health systems, including pre-natal screening for Down syndrome and Covid-19 modeling and dashboards..

Yildirim finished her degree in Jan. 2021, took a postdoctoral position at Harvard, and then joined the ORISE program in Dec. 2021.

The awards are sponsored by both alumni and corporate partners, among others. To learn how to get involved, contact ISyE’s Senior Director of Development Nancy Sandlin at nancy.sandlin@isye.gatech.edu.

Explore all award winners below.

Graduate Awards for Excellence in Research

The Shabbir Ahmed Research Excellence Award

Jiaming Liang (Optimization)

Sebastian Perez-Salazar (Optimization)

The Atlanta Air Cargo Association Research Excellence Award

Jana Boerger (Supply Chain Engineering)

The Robert Goodell Brown Research Excellence Award

Liyan Xie (Data Science and Statistics)

The Anderson-Interface Research Excellence Award

Amin Gholami (Energy and Sustainable Systems)

The Thos and Clair Muller Research Excellence Award

Zhaowei She (Health Analytics and Health Systems)

The Angela P. and Reed J. Baker Research Excellence award

Jialei Chen (Advanced Manufacturing and SIAC)

The Margaret and Stephen Kendrick Research Excellence Award

Keyu Zhu (Analytics and Machine Learning)

The Ed Iacobucci Research Excellence Awarc

Daniela Hurtado-Lange (Applied Probability and Simulation)

Additional Graduate Awards

ISyE Outstanding Graduate Student Instructor of the Year Award

Shangcong Mou

Tyler Perini

ISyE Outstanding Graduate Teaching Assistant of the Year Award

Xinyu Liu

ISyE Outstanding Master’s Teaching Assistant of the Year Award

Lucienne Loo

The Phillip J. and Delores A. Scott Graduate Student Health and Wellness Award

Nidhima Grover

Miguel Campos Murcia

Katja Meuche

Vinaya Krishna

Ritesh Ojha

Yassin Watson

Undergraduate Awards

ISyE Outstanding Undergraduate Teaching Assistant of the Year Award

Pratyush Agrawal

Institute of Industrial and Systems Engineers Excellence in Leadership Award

Dany Shwayri

The Evelyn Pennington Outstanding Service Awards

Duncan Siebert

Hung Doan

The Evelyn Pennington Student Health and Wellness Award

Noah Mitchem

Christina Collins

Elizabeth Schupp

Quentin Mot

ISyE Alpha Pi Mu Academic Excellence Award

Oscar Aguilar

Xufei Liu

COE Honors Day Award

Zhiyi Li

COE Outstanding Undergraduate Research Award

Madeleine Pollack

Adam Profili

Kurt Salmon Associate Scholarship in Industrial and Systems Engineering

Maxim Geller

Michael Cho

Hope Williams

Fuad Hossain

KS2 Technologies, Inc. Entrepreneurship Award

Christophoros Kontomaris

Min Sol Lee

Nicolas & Aurora Suarez Condezo International Award

Dewang Agarwal

Li, also core faculty in the Center for Machine Learning at Georgia Tech, currently focuses on the developments of machine learning algorithms for precision medicine specifically with regards to the brain. She leverages collaborations with radiologists and neurologists to investigate brain diseases like cancer, Alzheimer’s, and post-traumatic headache after brain injury.

Today, technology advances have produced more data than ever before, imaging, genomics, mobile health data, etc., which allow researchers to develop more personalized algorithms for diagnosis and prognosis.

“What disease do they have? How severe is it? How will the disease change in the future? Are they on the track of recovery, or are they going to get worse,” Li said.

Using the available datasets from imaging, genomics, clinical records, and mobile apps & wearables, they are building personalized models for diagnosis and treatment in each of these areas that can lead to early detection and more effective outcomes.

Ayer, who also holds an appointment from Emory Medical School and serves as a senior advisor to CDC, focuses on health care analytics and socially responsible business analytics with an emphasis on practice-focused research. In recent work, he has attempted to build up more robust and effective virtual trials for medical screening, diagnosis and treatment using large-scale mathematical models.

If you look at the gold standard in medicine and clinical science – randomized control trials – it generally utilizes A/B testing strategies. But what if there are thousands of strategies to compare, not just Strategy A and Strategy B?

“In a recent study, we looked at multi-modality cancer screening strategies for cancer detection in gene mutation carriers,” Ayer said. “You ask questions like: Should you use ultrasound screening or MRI screening? How about mammography screening? Or maybe mammography plus ultrasound screening? At what age should you start – 25 to 30? Or 35?

“At what age should you transfer from a less intensive screening to another? Is that cost effective? And what if we are solving this problem for the United States versus sub-Saharan Africa where resources are more limited? There are millions and billions of scenarios, and you can’t design a randomized control trial that would effectively compare those.”

Ayer’s work has spanned long-term chronic disease, both communicable and non-communicable – diseases like COVID-19 for the former and different cancers for the latter.

Both Li and Ayer said the chair appointment would assist in their work.

“It’s a great honor and recognition,” Li said. “I think going forward this will help me to pursue bigger efforts and initiatives, engaging people with a variety of expertise. This research needs collaboration across different descriptions. ”

“It helps to bring more visibility to the work,” Ayer echoed. “This will also help us scale up the resources that we have within our communities and reach out to more collaborators.”

“It was wonderful to see the senior design students develop and present their projects in person. They endured another stressful semester, but remarkably balanced quality and rigor with health and wellbeing,” said Director of Professional Practice Dima Nazzal. “Kudos to them for overcoming the challenges and delivering excellent work for a wide range of clients including government agencies, small non-profits, and large corporations. Congratulations to the faculty advisors, who coached the teams and kept them motivated and focused. A special recognition and appreciation to our Director of Technical Communication, Brandy Blake, for teaching the students how to communicate their engineering designs clearly and succinctly”

Senior Design team “Provision with a Vision” won the Capstone Expo award for Best ISyE Project. They worked with the on-board services group at Delta Air Lines to develop a data-driven methodology that determines the optimal amount of beverage items to load on a flight. The project motivation came from unused items adding extra weight to the aircraft resulting in excess fuel costs and carbon emissions. The team delivered an optimization model that takes into consideration passenger demand as well as an impact analysis tool which allows Delta to visualize how small changes in beverage quantities can have significant economic and environmental impact across the system.

The team included Anneliese Conrad, Carolina Howell, Niral Jagtap, Ellie Johnson, Nico Knutzen, Sofia Laval, Brad Peterson, and Libbee Stallone. They were advised by Associate Professor Anton Kleywegt.

From among the ISyE teams, three were selected as finalists for the Best of ISyE Senior Design Competition, which was held on December 14, 2021. Team “Shoulda Put A R(INGO)n i(T)” was selected as the first-place winner.

Team “Shoulda Put A R(INGO)n i(T)” partnered with Novelis, an aluminum manufacturing company, to improve ingot availability in its Oswego, NY, facility. The goal of the project was to ensure that when a customer makes an order, Novelis could supply the right ingots at the right time on hand to immediately start production. The team’s solution was to build an ingot “supermarket” that would increase ingot availability from 50% to 90% and reduce overall lead time by up to 40%. To achieve this, the team created an optimization model that recommended the best replenishment strategy for each ingot SKU and used a simulation model to measure the impact of the supermarket on the production process. With this new tool, Novelis can dramatically increase their operational efficiency and save millions of dollars per year.

Team Members included Tobin Abraham, Joseph Abrokwa, Elvin Chirackal, Joseph Cochran, Lorenzo Guerrero, Grace Anne Muller, and Tim Ryan. They were advised by Part-Time Lecturer and Tennenbaum Institute Principal Research Engineer Douglas Bodner.

Finalist team “Can’t Stop, Won’t Stop, Bus Stop” worked with the Atlanta Department of Transportation (ATLDOT), a recently formed government entity tasked with promoting transportation infrastructure. The team worked to provide ATLDOT with a data-driven methodology to allocate funding to bus stop improvements and a platform for closer collaboration with MARTA. Only 7% of bus stops (out of nearly 4,000) in Atlanta have shelters, which provide riders with proper seating, protection from weather, and ADA accessibility. The team’s solution combines process design with an interactive web tool and a greedy heuristic web app. Through the team’s solution, an additional 1.5 million trips per year will now originate at a sheltered stop. The City of Atlanta voted to back the project with a $3.4 million non-fungible funding source, and the team will present their design to the new mayor in January.

Team members included Soobin Baek, Aaron Brown, Ananya Ghose, Sanghwa Lee, Sung Kyu Lee, Alea Legg, Hetu Patel, Tejas Santanam. They were advised by ISyE Lecturer Gamze Tokol-Goldsman.

Finalist team “Keep it Simply” worked with The Coca-Cola Company to minimize the overall cost of the distribution network of two recently acquired dairy brands: Fairlife and Simply Oat & Almond. The team provided a data-driven method of formulating network expansion plans and determining safety stock levels by building and validating a mathematical optimization model that recommends not only the optimal distribution center (DC) opening location and timeline, but also the capacity expansion and safety stock level at each DC over a given horizon. This provided an annual value of several million dollars across the two dairy brands. To help Coca-Cola design the network expansion of any brand in the future, the team generalized the model to a standardized template wrapped within a user-friendly graphical user interface with three different model options.

Team Members included Joseph Chanin, Yizhi Huang, Minrui Liang, Yufei Liu, Naren Reddy, Xinran Yu, and Emily Zhang. They were advised by Leo and Louise Benatar Early Career Professor and Associate Professor Alejandro Toriello.

In addition, two teams received honorable mentions and were contenders for the Best of ISyE Senior Design.

Team “Panic! at the Cisco” worked with Cisco on its Printed Circuit Board Assembly Component Allocation. Team Members included Anjana Anandkumar, Udisha Bhattacharyya, Grace Gilpatric, Katie Landers, Kat Pospichel, Briana Sims, Tan Tanthien, and Anna (Tu) Vu. They were advised by William W. George Chair and Professor Pinar Keskinocak.

Team “The Bee’s Knees” worked with Smith + Nephew on its production planning. Team Members included Leon Breaux, Sara Costello, Emma Jones, James McGregor, Georgia Warnock, and Delaney Wastler. They were advised by ISyE Lecturer Ethan Lee.

“I am truly grateful and humbled for this huge honor,” said Keskinocak. “I am thankful to all my colleagues, students, friends, and family who have supported me and many others over the years, and it is the greatest gift for me to support others, even if only in a small way.”

Throughout her career, Keskinocak has been a leader in her field and has advocated for the advancement of women and minorities in engineering. She is an INFORMS Fellow, has served as president of INFORMS and the WORMS Forum, established the WORMS Award, and served as the co-founder and president of the INFORMS Junior Faculty Interest Group to help junior faculty develop their networks and grow professionally. During her term as INFORMS president, she helped further diversity, equity, and inclusion within the organization. She also spearheaded the establishment of a DEI Ambassadors Program to create a culture of inclusivity for all members within the INFORMS community.

At Georgia Tech, Keskinocak is the co-founder and director of the Center for Health and Humanitarian Systems, and she has served as a College of Engineering (COE) ADVANCE Professor and interim associate dean for faculty development and scholarship. She has also made significant contributions to numerous programs at COE and the Institute, which include the Demystifying Tech Series, Adaptive Leadership Workshop, and Diversity and Inclusion Fellows Program. In addition, she was instrumental in the establishment of the COE diversity and inclusion council, resume speed meeting workshops, and other initiatives focused on equity, diversity, and excellence.

Keskinocak has made a lasting impression on many of the people she has worked with.

“I don’t know how my career and life would have turned out had I not had the chance to meet and work with Dr. Keskinocak,” said one person in their nomination letter. “I do know how grateful I am I did have that chance. She is and always will be a role model for me in servant leadership, an extraordinary mentor, and an exceptional teacher.”

“I am just an example of all the lives and careers of women in OR/MS who Pinar has touched, as an advisor, as a professor, as a colleague, and as a leader and role model in OR/MS,” said another. “Pinar represents exactly what this award is about.”

Keskinocak’s research focuses on the applications of operations research and management science with societal impact, particularly health and humanitarian applications, supply chain management, and logistics/transportation. Her recent work has addressed infectious disease modeling — including significant work related to the Covid-19 pandemic — and evaluating intervention strategies and resource allocation; catch-up scheduling for vaccinations; hospital operations management; and disaster preparedness and response.

With innovative research projects in healthcare, it is no surprise Arden Baxter received a prestigious Graduate Research Fellowship from the National Science Foundation. Her work in humanitarian logistics explores how to allocate scarce resources to meet the most demand, specifically in disaster management scenarios where different resource types must work in coordination.

“In a hurricane setting, you could have flooding in an area but also people who are hurt and need EMS [emergency medical services], necessitating coordination between water rescue services and EMS to get those people out of their homes and treated,” Baxter explained.

She has also been involved in disease modeling for Covid-19, studying the benefits and consequences of nonpharmaceutical interventions, such as voluntary quarantine and school closure, and how they affected the people who were homebound.

“I knew that I wanted to do something where I felt like I was making a difference,” said Baxter. “I've always had this passion for service, and operations research is a great way to combine math and service into one.”

HENRY YUCHI // Ph.D. student, Machine Learning

After studying at the University of Cambridge to earn his undergraduate and master’s degrees in engineering, Henry Yuchi was drawn to Georgia Tech by the diversity of ISyE research and his interest in the interface of engineering, data science, and statistics.

“Across the country, and Europe as well, it is very rare to find a data science or machine learning program in the engineering department,” said Yuchi.

He is studying low-rank matrix completion as well as computer experiments with multiple mesh density variables — work that earned him a student paper award from the American Statistical Association. His research tackles the engineering problem of using computer simulation software to separate a very large model into mesh cells, or boxes, to make estimates of items such as flow speed and velocity.

“I’m trying to find a scheme where we can use different sizes of cells to run different experiments, then combine all the solutions together to improve the accuracy of the experiments, while using fewer computational resources,” Yuchi explained.

JIALEI CHEN // Ph.D. 2021, Industrial Engineering

Jialei Chen has been a research assistant at the Georgia Tech Manufacturing Institute, taking part in interdisciplinary research focused on data analytics and its applications to manufacturing and healthcare. One of his projects, a collaboration with Piedmont Heart Institute, proposes a surgical planning framework to treat aortic stenosis, a severe heart disease caused by the narrowing of the aortic valve. The current procedure, which involves inserting a stent, is a standardized treatment with limited customization.

“Our ambition is to personalize this surgery procedure for the specific patient,” said Chen. “We try to understand through computer simulations and 3D printing experiments which surgery procedure is the best for the patient.”

His work across multiple research areas has earned him the Ellis R. Ott Scholarship from the American Society for Quality, as well as many first-place awards at student paper competitions. Now that his Ph.D. is completed, he will continue his path in academia as an assistant professor in the department of statistics at the University of Georgia.

The dashboard was developed by a team from the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), including Pinar Keskinocak, William W. George Chair and professor, and Dima Nazzal, Director of Professional Practice. They worked alongside Ph.D. students Akane Fujimoto and Tyler Perini in collaboration with the Georgia Department of Public Health (DPH).

“There is a lot variability in different regions of the state, so we wanted to take a closer look from an equity perspective,” said Keskinocak in the article.

As of June 3, the dashboard indicated that vaccination rates among white residents are higher than those of Black residents in all large metro counties as well as around 70% of all Georgia counties. In addition, vaccination coverage among adults was lower among those living in counties with lower socioeconomic status and with higher percentages of households with children, single parents, and persons with disabilities.

You can read the entire article about their findings here.

The study was conducted collaboratively by researchers at the Georgia Institute of Technology, the University of North Carolina (UNC), and North Carolina State University (NCSU). This includes Pinar Keskinocak, William W. George Chair and professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), as well as Julie Swann, department head of North Carolina State University’s Fitts Department of Industrial and Systems Engineering.

Researchers evaluated how many Covid-19 cases could be avoided in North Carolina if more people get vaccinated and continue to follow mask and physical distancing guidelines. They used an agent-based model originally developed at Georgia Tech for pandemic flu that was later adapted to Covid-19 and modified to test additional scenarios.

“The main takeaway from the paper is that while the increasing vaccine coverage in the U.S. has a positive impact, we are not really there yet. We still need to follow preventive measures such as mask wearing,” said Keskinocak in the article.

Swann concurred, saying, “Current variants are more infectious, and there are still locations with less than 30% of the population vaccinated.”

You can read more about their findings here.

Turgay Ayer, George Family Foundation Early Career Professor in Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering (ISyE), is part of a research team that received funds from the first round of grants. The Foundation recognized the work of Ayer and ISyE Ph.D. student Jade Yingying Xiao, along with their partners from Harvard Medical School and Massachusetts General Hospital – led by Assistant Professor Jagpreet Chhatwal, and Boston Medical Center – led by Associate Professor Benjamin Linus.

Last spring as the Covid-19 pandemic was taking hold in the United States, this multi-institutional team devised the widely used Covid-19 Simulator, which helps inform public health responses to the pandemic on the state and local level. (The simulator website includes other tools created by the team, including an outbreak detection tool and an immunity detector, which shows the proportion of each state’s population with Covid-19 antibodies.)

With the Accelerator grant, Ayer’s team will broaden the Simulator’s impact to inform the timing of each state’s lifted restrictions and a gradual return to normal activities. The Simulator’s recommendations are based on Covid-19 vaccination rates, as well as the new Covid-19 variants that are cause for concern.

“The Covid-19 Simulator mimics current Covid-19 epidemiology and pharmaceutical and non-pharmaceutical interventions, including public health policies, at the state level,” said Ayer. “With the rapid uptake of vaccines in the United States, the estimations from Covid-19 Simulator show that we could go back to life on a near-normal basis by the end of 2021 or early 2022.”

Throughout his career, Ayer has worked on healthcare analytics, creating models to help slow the spread of various infectious diseases, including Hepatitis C. He also serves as the research director for healthcare analytics and business intelligence in the Center for Health and Humanitarian Systems at Georgia Tech and holds a courtesy appointment at Emory Medical School.

• Anne Schuchat, MD, RADM, USPHS, Principal Deputy Director, Centers for Disease Control & Prevention (CDC)
• Michelle Nunn, MPA, President and CEO, CARE USA
• Sanjay Gupta, MD, Chief Medical Correspondent, CNN; Staff Neurosuregon, Emory Clinic (to interview Michelle Nunn)

KEYNOTE BIOS

Dr. Anne Schuchat has spent almost 30 years in public health, in leadership roles at the CDC, the National Center for Infectious Diseases (NCID) and the Center for Global health. She will share her experience working across Africa on meningitis, pneumonia, Ebola vaccine trials, surveillance and prevention projects, as well as in China on Beijing's SARS emergency response, and the importance of collaboration in building strong supply chains and health systems around the world.

Michelle Nunn has spent 25 years in civic and public service, as a social entrepreneur, a nonprofit CEO and a candidate for U.S. Senate in Georgia. Michelle will share reflections on CARE’s work fighting global poverty and providing lifesaving assistance in emergencies such as the Syrian refugee crisis, and ongoing turmoil in Yemen and Sudan, as well as disaster response efforts in places affecting by natural disasters due to El Niño.

Dr. Sanjay Gupta is the multiple Emmy award winning chief medical correspondent for CNN. Gupta, a practicing neurosurgeon, plays an integral role in CNN's reporting on health and medical news for all of CNN's shows domestically and internationally, and contributes to CNN.com. His medical training and public health policy experience distinguishes his reporting from war zones and natural disasters, as well as on a range of medical and scientific topics, including the recent Ebola outbreak, brain injury, disaster recovery, health care reform, fitness, military medicine, and HIV/AIDS. Additionally, Dr. Gupta is the host of Vital Signs for CNN International and Accent Health for Turner Private Networks.

CONFERENCE OVERVIEW

The 2016 HHL Conference will feature plenary panels and interactive workshops on a variety of topics related to supply chain management and logistics in global health and humanitarian response and development, as well as a Technology Exhibit, poster sessions on innovative research, and ample opportunities for networking. Information on speakers, panel topics, health and humanitarian site visits will be available soon at: chhs.gatech.edu/conference/2016. You may register now for the conference at: chhs.gatech.edu/conference/registration/. *See note below on registration reimbursement

Plenary panel topics will focus on the below topics.

• Strengthening Public Health Systems
• Managing Complex Supply Chains in Refugee Crisis Response
• Matching Supply with Demand in Emergency Response

The 2016 conference is made possible by generous support from the UPS Foundation (now for the 8th year). TO SPONSOR THE 2016 CONFERENCE, please contact Meghan Smithgall at msmithgall@isye.gatech.edu. 

We hope you will join us in August!

*Note that the first two registrants from an NGO (for example, the first two employees from UNHCR (from any country) or other NGO) may apply for reimbursement of the registration fee following the conference. Only current degree students with accepted posters are eligible for limited financial assistance and registration reimbursement ($250 for travel within U.S. and $500 if traveling from outside of U.S. Click here for details). There is no other financial assistance or scholarship available for conference participants.

Director of Professional Practice Dima Nazzal is responsible for project-based learning in ISyE, including the Capstone Senior Design program. She has been awarded one of two Curriculum Innovation Awards, which recognizes faculty “who are improving the quality of education at Georgia Tech through pedagogical and curricular innovation.” Nazzal specifically received the award for her development of the ISyE Cornerstone Design course.

The Cornerstone Design class – first offered in the Fall 2018 semester – is an early design course focusing on framing a problem without solving it. The course lays the foundation for design thinking using a project-based learning approach, interactive problem-solving sessions, and the goldmine of past Senior Design Capstone projects from past years that ISyE has kept organized in a database.

Nazzal has explained that the goal of the class is for students to develop, through multiple diverse projects, key design skills, such as how to develop a solution hypothesis from a vague need by methodically dissecting the problem and analyzing relevant information. Students learn that there is not one way to solve a design problem because design generally involves tradeoffs between competing objectives under uncertainty. They work in teams with a rotating leadership role, so each student experiences the challenges and rewards of being a project leader. They learn how to effectively and succinctly communicate the motivation for solving a problem and the scientific evidence supporting their design solution hypothesis.

“We realized that we need to have a proactive approach to addressing the design skill gaps we see in our students during their Senior Design projects,” Nazzal said. “Some faculty have cynically said, ‘In Senior Design, we’re throwing the students into the water to learn how to swim.’ We introduced Cornerstone Design to teach our students to not only survive the deep waters of design problems but also to skillfully navigate the turbulence as well. Cornerstone Design has a set of simple and inexpensive features that have proven to be effective and replicable. I am honored to receive this recognition, and I look forward to continue working with my colleagues to improve and innovate."

“Being the No. 1-ranked industrial engineering program in the U.S. makes ISyE a leader in curriculum development. Cornerstone Design structure and content is readily available to any industrial engineering department that is looking to expand its curriculum – and consequently their student – development,” Nazzal added.

Previously, Nazzal received the 2015 Georgia Tech Women in Engineering Outstanding Teacher Award.

A. Russell Chandler III Chair and Professor Pascal Van Hentenryck received the 2021 Teaching Excellence Award for Online Teaching, which “recognizes a full-time faculty member for strong commitment to engaged online teaching and student success.”

When the Covid-19 pandemic caused Georgia Tech to move instruction online last March, Van Hentenryck successfully pivoted his courses to the changed format. This also included shifting the Seth Bonder Camp for Computational and Data Science, offered for middle and high school students, to a virtual configuration, which he was then able to offer twice last summer.

“We tried to make the courses entertaining and offer personalized attention to each and every student, knowing they would spend most of their days in front of a monitor,” Van Hentenryck said. “We learned so many things. Of course, I am more than delighted to receive this award: It is additional motivation to keep improving.”

In winning the Institute’s Teaching Excellence Award, Van Hentenryck will be this year’s Institute nominee for the Regents’ Teaching Excellence Award from the University System of Georgia. He has also been the recipient of numerous teaching honors, including the 2020 Student Recognition of Excellence in Teaching: Class of 1934 Award.

Nazzal and Van Hentenryck will be recognized at the April 15^th Faculty & Staff Honors Celebration, which will be virtual this year.

Keskinocak has focused her career on heath and humanitarian systems, including hospital operations management, infectious disease modeling, and evaluating the effectiveness of intervention strategies. Since the initial coronavirus outbreak, she has worked on developing a comprehensive agent-based disease spread model, in collaboration with ISyE Professor Nicoleta Serban and Ph.D. students Buse Eylul Oruc, Arden Baxter, and others. The model estimates the spread of the disease geographically and over time; resource needs such as hospital beds, ICU beds, and ventilators; and enables the team to evaluate the impact of various intervention scenarios to determine the best course of action.

In a recent CNN interview, Keskinocak discusses the impact of social distancing and current shelter in place orders. She cautions that a careful, gradual approach is needed as society plans to go back to work and social life, a balancing act between public health and the economy. She emphasizes the importance of the need to continue social distancing to slow down COVID-19 spread, flatten the curve, and save lives.

View the recording of “Analytics for Infectious Disease Control” via YouTube

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This was the fourth webinar of a series on the value of applying analytics to real-world problems. These webinars are an initiative of the INFORMS Practice Section, and you are welcomed to join here.

If you would like to present in this webinar series send your information to:

Dr. Patricia Neri (patricianerib@gmail.com) or Dr. Carrie Beam (carrie@carriebeamconsulting.com).

The Practice Section is currently working on the fifth webinar in the series.  Check back here for updates!

Now Keskinocak has been called on to lend her expertise to the Committee on Addressing Issues of Vaccine Distribution and Supply Chains to Advance Pandemic and Seasonal Influenza Preparedness and Response. This ad hoc committee formed by the National Academies of Sciences, Engineering, and Medicine will examine “supply chain and distribution challenges related to vaccines and vaccinations during the COVID-19 response and explore their implications for pandemic and seasonal influenza.” 

Among other responsibilities, the committee will review pandemic vaccine manufacturing during the H1N1, SARS, Ebola, and Covid-19 outbreaks; identify critical gaps in vaccine delivery on both a regional and global basis; and examine how Covid-19 vaccine manufacture and distribution may have important implications for the manufacture and distribution of flu vaccines.

Closer to home, Keskinocak serves on Georgia Tech President Ángel Cabrera’s Recovery Task Force, a group of leaders from across campus formed to help guide the Institute’s eventual return to normal – and safe – operations. The task force has been modeling different return scenarios using guidelines set forth by federal and state public health agencies, as well as the University System of Georgia. In March, Institute leadership announced plans for the Fall 2021 semester to see resumption of fully normal operations.

Keskinocak, who is also the co-founder and director of the Center for Health and Humanitarian Systems at Georgia Tech, has dedicated her career to the applications of operations research and management science with societal impact, particularly health and humanitarian applications and supply chain management. Most recently she has focused her efforts on vaccine distribution and infectious disease modelling during the Covid-19 pandemic.

“The pandemic highlighted the weaknesses in many of our ‘systems’ like never before. Its impact, similar to many other previous disasters, has been disproportionately high on vulnerable or underserved populations,” Keskinocak said in the article.

“When we prepare for or respond to a complex emergency, we need the public and the private sectors to speedily coordinate, with all players understanding what is needed from them, when, and where, so that we achieve synergies, providing resources and services that are the right place at the right time. This requires coordination on a national and sometimes global scale, which has been lacking in many of the complex emergencies in the past, including during the COVID-19 pandemic.” 

You can read the entire article about Keskinocak’s work here.

Using data from the state of Georgia, the study determined that a combination of non-pharmaceutical interventions, with various levels of compliance that change over time, could in some instances cut cumulative infections in half and reduce the peak number of infections to about a third of what could have been seen, “flattening the peak” to avoid overwhelming a state’s healthcare system. 

You can read a complete analysis of the ISyE team's findings here.