Robotics in Retail Distribution Centers

It’s no secret that the pandemic caused and accelerated significant challenges and changes across global supply chains. Simultaneously, consumers embraced e-commerce with a vigor that surprised even its most optimistic proponents.

Next-day delivery, made omnipresent by leaders like Amazon, grew to include same-day delivery in many markets. Consumers also showed an eagerness to capitalize on the convenience e-commerce offers in new sectors. The U.S. Department of Commerce’s latest survey estimates that e-commerce accounted for 14.5% of all retail sales in the fourth quarter of 2021 and that online purchases were $870.8 billion for the year, a 14.2% increase over 2020.

The takeaway is clear: The pandemic prompted people to shop online and many will continue to do so even after they return to brick-and-mortar stores. This is important for those who oversee retail distribution centers because successful e-commerce fulfillment now requires warehouses to achieve much faster throughput.

Robots Take Center Stage

The pandemic revealed how important automation is in today’s retail distribution centers. Advanced warehouse automation enables retailers to effectively respond to increased demand and is equally important when addressing the shortage of labor in many markets. As a result of the so-called “Great Resignation” many retailers continue to struggle in their efforts to fill positions in their warehouses and distribution centers.

This is one of the reasons there is such great interest in robotics across the retail industry and at industry events. For distribution center managers, the idea of deploying a team of robots to supplement overextended employees is very attractive, particularly when most are being asked to process an ever-increasing volume of orders in an exceptionally tight labor market.

So what should heads of supply chains and warehouse operations consider when appraising the potential use of robots in their facilities? What is their value today and how can they be used in the future?

Robots have Already Proven their Value in Warehouses

The use of robots in retail warehouses of course is not new. For example, many high-volume distribution centers already use palletizing robots. The very things that made palletizing a difficult activity for people – lifting heavy cases repeatedly in the same motion – made it perfect for robots.

Today, robots are poised to take on more complex tasks thanks to advancements such as the latest vision systems and machine learning applications. The impact on warehouses will be significant.

Item Handling Use Case for Robots

Retailers’ ability to successfully address the materials handling challenges that arose over the past two years validated the maturity of the automated systems now used by the most successful brands. There is however, a clear and significant business case for robotics: item handling, item picking, item sortation and decanting make up more than 70% of the workplaces in the typical retail warehouse. Automating these tasks reduces the dependency on manual labor significantly.

Compared to palletizing, item picking requires more advanced robotics technology. A retailer might have 100,000 distinct SKUs, all of different weights, sizes and shapes, that change over time. These items arrive at the workstation in random orientations. This high variability presents robotics engineers with a far more difficult challenge than palletizing, however AI-based vision technology allows robots to pick selected items quickly and reliably.

The market demand is there. Robots are already proven in many industrial applications and will be used for increasingly complex warehouse tasks going forward.

System Implications When Adopting Robots for Item Handling

While it’s tempting to view robots through a Hollywood lens where they complete numerous jobs with ease, the reality is different. Not all the items can be handled by a robot: some are too large, too heavy or can’t be effectively manipulated by a gripper. Sending these items to a robot station causes interruptions and interventions that slow warehouse processes.

Robots are also not as efficient as humans in tasks like packing where advanced Tetris skills are needed. While there is no question that the advancements being refined today will ultimately lead to their use in such applications, today’s robots are roughly 50% as efficient as people when it comes to such complex tasks.

Like all investments in technology, robots do not deliver a return on investment when they aren’t working. It’s important therefore that automated systems distinguish which items can effectively be picked by robots and only feed the work they can execute successfully.

Ultimately, the ratio of robots to people in most warehouses will depend to a great degree on the percentage of items and orders that the robot can effectively handle. Over time, advancements and refinements will enable robots to pick a larger percentage of the total product assortment. Ideally, systems being designed today will also include plans and the flexibility to replace more manual workstations with robots in the future.

There is no question that robots already reduce many facilities’ dependency on manual labor and will continue to offset additional demands for people to do highly repetitive and manual tasks in the future. Ultimately, we will see the true and full potential of robots when the additional integration complexity they require today is fully addressed in large scale materials handling systems.

Envision a Realistic and Measured Future

Vice presidents of supply chains or directors of distribution centers have good reasons to be excited by the futuristic robotics technology touted today. Robots, like all forms of automation, are designed to augment the efforts of people. The first step in their deployment should be to simplify warehouse processes to a level that enables robots to successfully execute them.

Over time, robots – like the many other forms of automation we increasingly take for granted – will enable retail distribution centers to be faster and even more effective. What’s important now is that we implement reliable robot workflows, learn from them and increase their applicability over time.

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