Brian Pulfer is VARGO’s manager of solutions development & data analytics.
In the past, retail warehouses made decisions based on historical data. But to meet today’s customers’ demands for on-demand delivery, the industry, and its technology, must shift. Looking to the future and predicting shoppers’ needs means using significant amounts of data to determine the next optimal move in a fulfillment center. Artificial intelligence (AI) transforms an overwhelming amount of data into usable insights to assist retailers in a multitude of decisions in the fulfillment center. Additionally, the market for robotics in the warehouse has grown significantly to help retailers manage labor shortages and to shift repetitive tasks from humans to robots.
RIS’ recently published “The AI-Driven Supply Chain: Seamlessly Meeting Complex Demand” special report in order to explore how savvy retailers are turning to AI to help power their next-gen supply chains.
To uncover how retailers can best leverage the newest available AI technology, VARGO’s manager of solutions development & data analytics Brian Pulfer sat down with RIS for an exclusive Q&A on the topic.
RIS: What is a warehouse execution system and how does this solution keep orders flowing to expedite fulfillment?
Pulfer: Warehouse Execution Systems (WES) are used within distribution facilities to manage the elements that make up the outbound workflow. The WES synchronizes and sequences all work resources — space, equipment and personnel. In the past, these may have been managed by several different systems that didn’t know or weren’t concerned with what was occurring in other areas of the distribution center. But the WES keeps orders flowing by providing real-time visibility and controlling automation, labor and other elements. With this expanded level of control, the WES can dynamically adjust to the needs of the operation with regard to prioritizing orders and operational tasks, releasing work (waveless processing), increasing/decreasing demand, and ultimately optimizing the flow of the entire fulfillment operation.
RIS: What part can AI play in the warehouse segment of the supply chain to improve fulfillment and labor?
Pulfer: AI can greatly improve fulfillment and labor in the areas of robotics, machine learning and data analytics, and training and development. With robotics — whether it be automated guided vehicles (AGVs), collaborative robots (CoBots), drones, or articulating pick/pack arms (to name a few) — many applications are already integrated within warehousing to help retailers manage labor shortages and to shift mundane/repetitive tasks from humans to robots. Within the last four to five years, the market for robotics in the warehouse industry has grown significantly. In the area of machine learning and data analysis, robots are using significant amounts of data to determine the next optimal move in a fulfillment center. In the past, most warehouses made decisions based on historical data. We’re now shifting — looking to the future and predicting trends and needs being driven by the customers’ demands for quicker cycle time and on-demand delivery. In the area of training and development, we have seen virtual reality used to train associates on anything from picking to driving a forklift. These types of applications provide a controlled and stable environment for associates to learn quickly and to even cross-train.
RIS: Why is AI needed to develop a demand-driven supply chain and help retailers make smart allocation decisions?
Pulfer: There are overwhelming amounts of data being collected and analyzed monthly/weekly/daily/hourly by a multitude of customers across all industries. AI transforms this data into trends, predictive models, and other algorithms to assist retailers in a multitude of decisions in a fulfillment center. In today’s heavy omnichannel environment — where so many retailers are using one inventory to fulfill both retail and direct-to-customer orders — AI can make the difference in whether a retailer is able to fulfill a customer’s order.
RIS: What are some of the cutting-edge ways you’re seeing AI make an impact on the supply chain today?
Pulfer: In supply chains today, AI greatly impacts the dynamic nature of systems, particularly in the WES. New features are being developed every day and added to the “neural logic” that drives a WES to optimize and organize work while synchronizing and sequencing resources. These additions to the intelligent design of the WES are leading to shorter cycle times, improved productivity, improved visibility, and better utilization of resources. Specifically, we are working on labor management/movement, order batching, and dynamic slotting of inventory. These types of evolutions in supply chain or warehousing are far beyond the standard practices of the past and equip operations to handle the increasing dynamic nature of the industry today.