Verusen is excited to welcome the newest member of its management team, Chief Technology Officer (CTO) Robert Sanders, who joined Verusen in June of this year. Robert is a self-described “Atlanta-based startup veteran,” having led DevOps teams in a variety of industries since 1994. He is a graduate of the Georgia Institute of Technology with degrees in Computer Science, Computer Engineering and Philosophy, but he’s been writing software since his first professional programming job during his junior year in high school. Here, we talk to Robert about Verusen’s AI and machine learning platform, his background and his interests.
What was it about the technology, culture and potential of Verusen that drove your interest to join?
My biggest career successes have occurred while working with leaders who had the vision to apply a transformative new technology within a well-established industry, and that’s what Verusen CEO Paul Noble has set out to do in applying artificial intelligence (AI) to supply chain and inventory management processes. The Verusen product is really exciting because it delivers such a clear ROI calculation. Using a company’s ERP data, we can quickly demonstrate how to save very significant amounts of money.
Company-wise, Verusen is small and its culture is continually evolving, which is another aspect I enjoy shaping. We’re scrappy, we’re innovative and there’s a very clear focus on solving real customer problems, while at the same time we’re building a company where we all love to work.
What sort of goals are you setting for your particular role at Verusen—both for right now and in the future?
Many companies have attempted to incorporate AI into products, but there have been challenges. At Verusen, innovating is the challenge we have to manage. As a startup company, we need to deliver a very focused, very effective application to our early customers, and then show results and continually refine the product until our customers are just absolutely ecstatic. Once we’ve done that, we can expand the application into more areas. For example, right now we’re looking primarily at inventory reduction for MRO, but there are huge opportunities outside that space.
Given your past experience growing companies, how are you going to achieve your stated goals at Verusen?
Maintaining clarity of vision and focus is absolutely the top priority. As a young company, you’re constantly squeezed between resources and sales demand and attractive opportunities. It takes a great deal of discipline and belief in your vision to stay focused in the face of all that. You have to keep an R&D pipeline going, but also guide those efforts toward very near-term deliverables in the product itself. Building the right team is a close second priority, because everything that this company will become rests on the talent foundation we’re building today.
Is there a particular skill set that you’re looking for in your team?
There are always the obvious questions about what programming languages a candidate knows, but I think what is more predictive of someone’s fit is adaptability, as well as the ability to be given a goal and creatively choose a solution that fits our environment here at Verusen. Much of what we’re doing is not a charted course, so everyone needs to be an independent thinker. As a team lead, I can point them in the right direction, but it’s really that self-guiding capability that is key to success.
You touched on the potential for AI in materials inventory management and beyond, and that the potential is definitely there to show ROI quickly. But what do you feel will be the barriers for adopting a technology like this?
I’ll start with AI’s potential, because that reveals some of the barriers. Inventory management is a mature discipline with a history of equations prescribing when to order, how much inventory to carry, and what the cost of doing so is. Then, there are systems, such as ERP systems, where those numbers reside for analysis. However, those general strategies don’t necessarily fit the realities of the business because they aren’t well tailored. So, you have local experts that have built an ad hoc knowledge base, who also tend to be conservative because there’s an insurance aspect of keeping extra materials around, even though it’s an error-prone strategy, it’s expensive and time consuming, and it’s not really systematized. AI allows us to capture that ad hoc knowledge and operational history and really tailor the models to each organization so we can cost-effectively attain their goals.
The challenge is that when AI gives you answers, it’s not always clear why. You have to be able to explain why you’re making a recommendation and you have to convince the local experts—the people who really have their jobs on the line—to trust that answer. It’s the AI-human feedback loop that’s so critical to success. Another challenge is that we have to interface with very complex ERP systems. We offer those systems the potential to enhance their platform, which can actually help us penetrate into the customer base.
What are some of your personal interests?
I spend most of my free time with my wife and two young boys, as well our old dog, Chomsky. When I do have free time, which startups don’t always allow, I like to cave dive, bike, read and travel as my schedule allows. Cave diving—although rightly perceived as carrying risk—is particularly interesting in that it’s all about having a plan and having the right skills. If you make the right plan, follow the rules, train well and don’t go beyond your limits, there is great joy in just having taken that little bit of risk. I guess you could say I enjoy the same in my career.
Readers can connect with Robert on LinkedIn.