SCB: You have described the supply chain as being in a new “digital lifecycle.” What do you mean by that?

Elliott: If you look at the supply chain of the future, the question we're asking ourselves these days is twofold. First, how do I move faster? Looking at the competitive landscape and market dynamics, the world is changing faster than it ever has. With competitive forces from Amazon, and catch-up work from Wal-Mart, we see innovations coming into the market at a pace that is unheard of — far beyond what we typically would expect in terms of supply chain innovation.

Second, if I need to move faster, how do I use digital capabilities to create the competitive space I'm looking for, to be as effective and as competitive as I can be? We call that the digital lifecycle because it not only requires adoption of new technology, but also a new way of thinking about how to incrementally improve the business. It’s a total approach to understanding what I want to do next, from cradle to grave, and managing that change process.

SCB: So where do simulation and design fit in?

Elliott: If the goal is to adopt a total digital lifecycle, you need is better tools at the very beginning of the process. Today, when we think about improving business processes, implementing new material handling, or creating new market offers, we start with a conceptual phase. We do that today through very analog means. We sit around and we talk about our business processes, outcomes and goals. We may use a whiteboard to try and understand what’s the next phase of innovation for our business.

But what if we could take technology and create a digital whiteboard, where we model our entire facility, workforce, material handling, automation and robotics capabilities, and understand how our supply chain is functioning in a digital space instead of a physical space? What power would that provide us to go and play, to ideate and create novel concepts about how we can improve our capabilities, without ever touching any of our physical constraints? It would allow us to do “what-if” scenarios in a digitally safe environment — to create the ideas that will drive our business forward, and play them out using simulation capabilities, to better understand and quantify what those ideas will achieve for us as a business.

SCB: That seems to be a natural fit for warehousing and logistics. Talk more about how you specifically apply the concept of simulation to that sector.

Elliott: In the warehousing and logistics space, simulation is not a new concept. When you engage with systems integrators today to think about a new facility or a retrofit of an existing facility, oftentimes they’re using simulation techniques to understand what type of automation would make sense there. How should I build the total box? What size do I need? They're asking you for your expectations on throughput, labor, and material makeup — the types of products that are going into and coming out of a facility.

The difference lies in putting that power into end users’ hands with modern techniques, such as artificial intelligence and machine learning, so that you don’t necessarily need a systems integrator or multi-year initiative. Instead it’s a more natural and integrated process, tied to the normal progression of your business day in and day out.

SCB: When I’m doing a simulation exercise, what am I seeing on the screen?

Elliott: The beauty of simulation is that it makes it very tactile. Instead of looking at an Excel spreadsheet, you’re seeing a two- or three-dimensional representation of your facility. It includes your workforce, material-handling equipment and the types of automation you're using. It creates a very intuitive way to build the model, which is all drag and drop, to help you understand how your business is operating today, and where are the constraints, hot spots and bottlenecks. On an executive level, it makes it very easy to explain and understand the commercial aspect of the innovations you want to apply.

SCB: So I can be looking at something and constantly be swapping out variables?

Elliott: That's exactly what you do. In a drag-and-drop experience, You’re looking at racking, forklifts, pit walls, robotics, how many workers you have, what your shift structure is. The system is not only modeled to help understand the physical layout of a facility, but also the operating characteristics of all those material-handling solutions. You can tell it how fast your conveyor moves and how much it can hold, and add additional data from your WMS to see what your throughput looks like. You create a simulation that explains where the constraints are in your facility. You can ask, what if I implemented a person-to-goods solution? Or a goods-to-person solution with movable racking?

SCB: What's going on behind the scenes in that black box is anything but simple. Is artificial intelligence essential to making this technology work?

Elliott: Yes, we need the horsepower. Its high mathematics, using very sophisticated algorithms for artificial intelligence and machine learning. You’re taking all of those constraints-based simulations, modeling them together and creating a very simplified output. What you’re focused on is how to be more nimble in a business environment that's increasingly demanding agility.