With a historically low number of shipping days between Thanksgiving and Christmas this year, shippers are dealing with the shortest annual peak holiday period since 2018. With a tighter timeline and global consumer e-commerce sales forecasted to reach over $6 trillion in 2024 and over $8 trillion in three years according to Shopify*, the pressure on supply chains during the holiday shipping season isn’t slowing down anytime soon.
Ask any supply chain veteran and they’ll tell you that demand during the peak holiday shopping season is uneven. From volume surging during the “Cyber Five” shipping days starting on Black Friday, fluctuating sharply in December, then tapering and leveling off in January, takes a lot of planning and coordination to deliver. So, how can technology help shippers succeed in balancing operational challenges as time and demand are constantly shifting?
Technology Transforming Supply Chains to Meet Holiday Demand
Stemming in part from the Covid-19 pandemic, the shipping industry was forced to accelerate its digital transformation, making the future of the supply chain more interconnected and warehouse operations more digitized. With a continued eye on innovation and a need to meet increasing consumer e-commerce demand – particularly during tighter timelines like this year’s holiday season – technology like AI can provide analytics and insights into consumer ordering behavior. This can be used to help e-tailers better manage their inventories and consolidate order picking. Tools like robotics can also provide necessary real-time visibility, operational efficiency, and resilience to shippers.
There’s no doubt that AI and automation’s adoption in mainstream business and culture has accelerated in the past few years and the world of logistics is no different. When considering adding AI into their technology stack, e-tailers need to consider the benefits of analytics and insights into consumer ordering behavior to better manage the inventories and consolidate order picking. 3PLs should be leveraging historical data and real-time market signals like weather, trends and economic factors to predict demand and adjust operations accordingly. This practice allows companies to optimize inventory levels, reduce stockouts, and avoid overstock situations. AI can also be used to address maintenance needs proactively, reducing downtime, extending asset lifecycles for equipment, and cutting down on maintenance costs.
Another consideration is how best to use collaborative robotics (or co-bots), which can have a large impact on supply chains during this busy time of year. Co-bots are becoming commonplace in warehouses – leveraging them to quickly pick, sort, and pack items with high precision and speed, significantly increasing efficiency.
For example, co-bots can augment the existing warehouse workforce as they use machine vision and AI to identify and handle products of different shapes, sizes, and weights with ease as well as more complex tasks like put away and inventory management. Leaning into robotics at this time of year is especially helpful as it can make the fluctuating workload of staff more manageable and allow employees to focus on more nuanced tasks that may arise, leaving routine and repetitive tasks to the co-bots.
A UPS Supply Chain Solutions customer leveraged this technology to meet fast-growing consumer demand, forcing the team to rethink their 3PL strategy. Following a hugely successful test-and-learn campaign, a co-bot integration quickly started to deliver results: the team was able to handle an enormous peak scale up, handling a 97% year-over-year increase in throughput. The technology was able to deliver strong results, increasing picked units per hour by 4x year-over-year, ensuring significant consumer demand spikes were met. But without visibility into operation details and key data points, the operation cannot reach its maximum potential.
While not new, the value of cloud-based tools that provide end-to-end visibility at every step across the supply chain function – from warehousing, inventory management, distribution, final mile, and even returns – cannot be missed as it allows shippers to learn from their operations. With robust visibility and access to large amounts of data, shippers can better optimize, and course correct, due to actionable insights at their fingertips. This ultimately provides them with the one thing they need this time of year – flexibility.
The Power in Scaling Down the Right Way
While many shippers pay close attention to scaling up for the busy holiday shopping season, scaling-down in the quarter following is equally as important as it gives shippers the ability to accurately prepare for demand in the year ahead (and the next holiday season).
Winding down operations typically involves a mix of reducing operational intensity, managing inventory, and preparing for the upcoming peak holiday season. Automation can play a significant role in making this transition smoother, efficient, and cost-effective, including being able to quickly and easily throttle down operations in the warehouses once the larger demand tapers off.
Automating processes like inventory management, order routing, and even workforce scheduling in Q1 can help shippers better match staffing needs to suit the lower volume and reduced demand in January and February.
Ultimately, by leveraging automation to wind down peak operations, shippers are building necessary flexibility into their business models to better navigate a predictably unpredictable time of year, no matter the kind of demand seen.
Handle Peak Holiday Demand with Greater Ease
Supply chain technologies are and will continue to transform how businesses meet peak demand, particularly during high-volume periods like the holiday season. With the integration of these technologies, operations will be more efficient, scalable, and responsive to growing e-commerce needs. Shippers will not only be better equipped to manage peak periods but succeed in delivering accurate and efficient service, which increases revenue and ultimately provides a competitive advantage during critical periods of seasonal demand.
