Epicor is a business software company based in Austin, Texas founded in 1972 with products aimed at the manufacturing, distribution, retail and services industries.
Your career includes time at Oracle, Harvard Business School, and a wealth of industry experience. What made you feel Epicor was the right opportunity, and why have you stayed in the CEO role for so long?
The higher up you go, the more critical fit becomes, and when I looked at Epicor eight years ago, I saw a strong alignment with my background and aspirations. Starting out as an engineer in a factory, I understood ERP systems from the ground up—the good, the bad, and the ugly. Epicor specializes in "make, move, and sell," focusing on manufacturing, warehouses, and logistics, which was a world I knew inside out. When considering my first CEO role, I wanted something where I could be successful, not just for myself but for the organization. The quality of Epicor's products and the clear journey to the cloud made it an exciting and fitting challenge.
Fast forward to today, and that journey has driven our success. Moving to the cloud was not just a technical shift; it positioned us to meet our customers’ evolving needs. I have stayed because the work remains deeply rewarding. The potential I saw for innovation and meaningful impact is even greater now, especially as we dive into AI, helping our customers navigate what is next in their industries.
Moving to the cloud seems to have set the stage for Epicor’s work in AI. How are you ensuring you remain a leader in this evolving space while addressing the challenges AI brings?
The biggest hurdle for our customers is ERP complexity. If you are not deeply familiar with these systems, they can be overwhelming. Our mission is to simplify that complexity using AI so that anyone can use the system effectively. For example, with what we call "Cognitive ERP" or "Ask ERP Anything," you can interact with the software in plain English. Imagine you are working on a car assembly line and need a report to make a quick decision. You do not need to be an engineer or programmer to get what you need—just ask, and the system delivers. This approach is transformative because it gives everyone—from factory workers to warehouse operators—access to critical insights in an intuitive way. We are turning everyday users into "super users," empowering them to make better decisions without technical barriers. That accessibility is what drives value and keeps us ahead of the curve.
With $1 billion in annual revenue and a series of acquisitions, Epicor is clearly growing fast. What does the next chapter look like for the company?
This year, we will hit about $1.4 billion in revenue, and over the next four years, we are aiming to double that. Growth will come from expanding our footprint internationally, especially in Western and Eastern Europe, while continuing to innovate for our customers. But revenue is not the only focus—it is also about empowering the people on the front lines. For me, it is personal. I started on the factory floor, and I know what it means to have opportunities to learn new skills or operate more efficiently. Whether it is through certifications, training, or better tools, we want to help workers advance in their careers. That is not just good for them—it is essential for competitiveness in industries facing rising challenges in productivity and global supply chains.
You have spoken about starting on the factory floor. How does the experience of someone in that role today compare to when you were in their shoes?
The difference is night and day. Thirty years ago, if you wanted to make a process more efficient, like improving warehouse stock movements, it could take months. I remember working on a project at Procter & Gamble to rewrite an inventory system. It took about three months to plan, test, and implement—and by then, the window of opportunity might have already shifted. Today, that same project could be done in days, not months. AI and modern ERP systems allow workers to propose and implement changes quickly. What is even more exciting is that they can be involved in the process, learning and contributing directly. It’s a collaborative dynamic now, where the people closest to the work have more agency. That’s the real power of today’s technology.
Epicor focuses on specific industries like manufacturing and logistics. How are you using AI, including models like LLMs, to create value for your customers?
For us, it is not about massive, general-purpose AI models—it is about precision. We work with medium-sized language models that are tailored to our specific use cases. For example, our primary software has around 70 million lines of code. Using Retrieval-Augmented Generation (RAG), we can narrow down to the exact parts of the system needed to provide actionable insights.
Picture a forklift operator asking the system to optimize a loading schedule for a specific dock. The system can process that request in plain language and return a solution—something that would have taken weeks of coding in the past. This is not just about AI for AI’s sake; it is about making everyday tasks smarter and faster, so our customers can spend less time on logistics and more time innovating.
Many industries you serve have traditionally been slow to adopt new technology. Are you seeing a shift in attitudes, especially around AI adoption?
Absolutely. A few years ago, moving to the cloud or using AI was seen as experimental in many of these industries. Today, it is becoming standard practice. Concerns about losing control—like not being able to manage software updates or ensure system reliability—have largely been addressed. Cloud adoption is now seen as a way to enhance flexibility, not limit it. When it comes to AI, the conversation has shifted from “Why?” to “How?” Customers want practical use cases that solve real problems. For example, they are leveraging AI to make data-driven decisions, identify inefficiencies, or improve employee productivity. While competition in the tech space is fierce, it is encouraging to see more companies recognize the tangible value these tools bring to their operations.
With all the excitement and competition around AI, what’s your biggest concern right now?
The toughest part is ensuring we get the use cases right. There is a lot of hype around AI, but if we pursue the wrong opportunities, it could waste resources and frustrate customers. That is why listening to our clients is so critical. We need to understand their needs and deliver high-value solutions that solve real problems—not just theoretical ones. There is also the pressure to move quickly because the pace of innovation is relentless. But for us, it is not just about speed—it is about precision and impact. If we do not get the use cases right, we risk falling behind. My job is to make sure we stay focused and adaptable, learning from our mistakes and doubling down on what works.
Looking into your crystal ball, what use cases do you think will define the future of Epicor’s solutions?
The big game-changer will be empowering frontline workers to access and act on high-level insights. Imagine a factory worker being able to identify and resolve defects before they escalate, or a warehouse team optimizing their workflows in real time—all without needing a technical expert to intervene. It is about turning good ideas into action at every level of the organization.
Even more exciting is the idea of workers using these tools to bring forward their own innovations. When the people doing the work can propose and implement ideas that improve efficiency or quality—and are rewarded for it—that is transformational. It is not just about technology; it is about creating a culture where everyone feels they can contribute. That is the kind of future we are building, and it is why I love what I do.
