Record e-commerce spending has put an unbelievable amount of pressure on not just retailers’ fulfillment networks, but also the warehouses that support them. The 2020 holiday season showed that retailers must face the reality that smart warehousing investments must be a priority if they want to improve the efficiency and performance level of their distribution centers.
Gartner believes retailers are set to make a run at more “non-invasive” automation-driven technologies, especially as they continue to adapt to Covid-19. The business research and advisory firm anticipates that through 2023, demand for robotic goods-to-person (G2P) systems will quadruple to help enforce social distancing in warehouses. With G2P systems in place, robots can deliver the goods to a person who remains in one location instead of roaming a vast fulfillment center.
“Keeping people in place and using a virus-resistant robot to move goods around respects people’s privacy and keeps them safe at the same time,” Dwight Klappich, vice president analyst with the Gartner Supply Chain practice, said in a statement.
The firm also forecasts that through 2024, 50 percent of supply-chain organizations will invest in applications that support artificial intelligence (AI) and advanced analytics (AA) capabilities.
“The COVID-19 pandemic has amplified the need for supply chain organizations to seek tools that help them make better and more informed decisions faster,” said Andrew Stevens, senior director analyst with the Gartner Supply Chain practice. “Leading organizations use AI and AA to dig through the vast amounts of data they generate to understand what is happening in their business now and—more importantly—what is likely to happen in the future.”
Gartner predicts that companies will continue to invest in applications that embed, augment or apply AI and AA tools. This may be to address foundational areas such as data quality or connecting disparate silos, or strategic objectives such as migrating to more automated, resilient and smarter applications. “Supply chain leaders should adopt a broad and holistic perspective when it comes to AI and AA,” Stevens said.
“These technologies are increasingly ubiquitous, and there are many ways in which they can be applied, such as data mining for smart manufacturing, visibility tools and autonomous transportation, and to aid customer retention,” Stevens added.
Get “smart” with warehouse execution systems
One such supply-chain solutions provider, Softeon, is aiming to empower both automated and non-automated distribution centers with AI-based technologies that ultimately drive better decision making within warehouse execution.
“The challenge with warehouse management systems is that over time they have looked at specific process threads and done a fabulous job with the evolution of the products themselves, but they are fundamentally missing the feedback loop,” Dinesh Dongre, vice president of strategy at Softeon, said in a recent webinar. “This is the learning that comes out of reacting and recognizing signals in a feedback pattern. It is always in ‘progress forward’ mode saying ‘do this, do this, hand off,’ so to speak, but there is no feedback to actually initiate actions.”
Dan Gilmore, chief marketing officer of Softeon, highlighted insights from Gartner’s Klappich when pointing out that the new paradigm of the “smart warehouse” requires platforms like warehouse management systems (WMS) and warehouse execution systems (WES) to work as one, particularly since the former is often a more reactive technology.
While WMS handles people-managed inventory and transactional processes such as receiving goods, putting them away and picking, packing and shipping orders, Gilmore said that modern WES can actually serve as an extension of the legacy WMS so that it can be deployed as a standalone and work for automated, non-automated and hybrid distribution centers alike.
This new definition of WES leverages AI to provide new levels of visibility and optimize flow across the warehousing floor to better understand when picking and replenishment processes must take place. The idea is that the WES provides a layer of automated decision making that can coordinates the flow of goods across all warehouse systems so that they are not siloed, but managed in one single system, Gilmore said.
“Historically, when you look at a WMS or a labor management system, they all tended to address the needs of a specific scope of work or functional area,” Dongre said. “But WES is fundamentally set up to facilitate orchestration and collaboration so it is not set up for orders, inventory or people, it is set up for everything that needs to work together.”
The webinar highlighted questions that a WES can automatically answer in real time, including: “What orders to release to the floor next?”and “How many orders to release to the floor based on capacity?”
It can also handle queries like “What locations should be replenished and when based on status?” and “How to balance people resources based on demand?”
Dongre said that these AI-driven technologies are “always on,” meaning they are receptive to feedback at all times.
“When we look at the dashboards, yes there are planners, there are people who can sit there and monitor the data, make choices, reassign resources, but as with anything else, the amount of time a person can spend in looking for feedback and accepting feedback is constrained,” Dongre said. “The WES is always observing feedback and making choices on there so it is continuously doing this without any limitation. It doesn’t have the typical constraints that you anticipate with human intervention.”
