High order volumes shouldn’t stress out fulfillment providers but delight them, as it’s the perfect opportunity to boost their profit margins. Using an AI-driven warehouse management system (WMS) or advanced fulfillment management system (FMS) alleviates peak season challenges substantially and puts 3PLs, B2B and DTC retailers on a profitable path.
This article explores how AI-powered WMS optimizes analytics, inventory accuracy, and picking/packing efficiency to streamline peak-season logistics.
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The role of AI in enhancing inventory accuracy
High order volumes during peak season stretch inventory systems and add complexities. To fulfill your delivery promises to customers, these must be resolved promptly.
Some of the inventory challenges that peak season brings include:
- Overstocking: It happens when retailers overestimate customer demand and stock excess inventory that surpasses demand. Overstocking causes extra storage and handling costs, increases tied-up capital, and accelerates inventory shrinkage.
- Stockouts: This is when a warehouse runs out of inventory because of excess demand. Stockouts cost retailers money in terms of lost revenue.
- Extra inventory handling costs: Ecommerce stores incur additional labor costs to process extra orders. Hiring more warehouse workers and delivery personnel costs you more money.
With an AI-driven WMS you can analyze sales data from past peak seasons and correlate the data with current market trends to estimate how much inventory is needed for the peak season.
Real-time inventory tracking simplifies supply and inventory planning, solving common warehousing and fulfillment challenges. With Logiwa IO, you’ll get AI-powered inventory management, plus benefits like an easy-to-use interface, flexible headless architecture, and easy integrations through our app store.
Watch the video above to learn about one of Logiwa IO’s many features.
AI-driven demand forecasting
While a demand spike during peak season is to be expected, you need a guide or benchmark to plan stock appropriately. AI-driven inventory forecasting gives you a data-backed approach to predict peak season demand more accurately.
Smart demand forecasting employs predictive analytics to analyze historical sales data and create formulas that simulate future demand. Predictive analytics analyzes various data points to derive crucial insights that help them perform demand modeling more accurately.
Other than past sales data, some data sources AI algorithms evaluate include:
- Market research and documented expert opinion expounding on peak season demand. For instance, the National Retail Foundation usually performs detailed market research and releases sales forecast reports like the 2024 sales forecast. AI algorithms analyze such data and use the gleaned sentiments to forecast demand.
- Supply chain reports documenting the supply state of products. AI algorithms analyze such reports to understand a product’s projected or existing supply state before peak season.
The smart insights derived from predictive analytics help retailers make data-backed decisions when ordering stock for peak season sales. This way, ecommerce stores avoid understocking or carrying excess inventory.
Optimizing picking and packing processes with AI
Fulfilling high order volumes during peak season requires optimized picking and packing to beat the holiday rush and satisfy heightened delivery expectations. The standard manual picking process falls short with workers unable to complete workloads accurately. And that’s where picking and packing optimization through automation saves the day.
Automated warehouse picking employs robotics technology to automate the item-picking process, eliminating the need for warehouse workers to retrieve products manually. Standard robotics technologies employed in warehouse automation include autonomous mobile robots (AMRs), automated storage and retrieval systems (AS/RS), and conveyor systems or automated guided vehicles (AGVs).
For instance, AMRs retrieve items from storage racks and deliver them to packers who finish the order processing process. This makes warehouse workers more efficient and productive, as they can pack more orders rapidly without errors.
Warehouse managers can also use other types of automated picking systems, such as pick-to-light systems, voice-directed picking, and vision picking, to enhance picking and packing efficiency.
Ultimately, the benefits of automating warehouse picking and packing go beyond enhancing peak season logistics. It streamlines warehouse processes throughout all seasons. Warehouse managers should approach picking and packing optimization as a long-term investment for their ecommerce business.
AI and real-time adaptation
Typically, even during off-peak seasons, changes in fulfillment operations happen rapidly, and retailers must make swift adjustments to sustain operational efficiency. Fortunately, an AI-driven WMS delivers real-time data on relevant changes, such as sudden demand spikes or supply chain disruptions.
Such AI-based systems analyze fresh data in real-time and derive reliable insights that help when making quick decisions on the go and adapting to new changes. For instance, if inbound orders of a particular product exceed the inventory levels in a warehouse, an AI-driven WMS can send warehouse managers real-time alerts with reminders to stock up.
With real-time data at your fingertips, you can foresee challenges and find solutions in advance to avoid or mitigate their effects. AI is revolutionizing the way businesses manage fulfillment of both B2B and DTC orders.
AI-driven WMS prove key to successful peak season operations
Savvy ecommerce retailers optimize the peak season period to maximize sales and profit margins. Relying on an AI-powered WMS helps retailers manage peak season challenges such as overstocks and understocks, as well as logistics challenges that hamper peak season operations.
Adopting AI in warehouse management comes with long-term benefits beyond peak season. It improves customer satisfaction, expedites order fulfillment, saves inventory handling costs, and facilitates scaling operations. Investing in AI-driven WMS gives ecommerce retailers the much-needed competitive edge in the tech-driven fulfillment industry.
You can count on the fulfillment experts Logiowa to guide you in picking the ideal solution from the myriad available solutions on the market. Schedule a call today, and our fulfillment experts will walk you through how you can get the most out of the Logiwa IO fulfillment management system.
FAQs about AI-driven warehouse management
Can an AI-powered WMS impact peak season sales?
When is the peak season for ecommerce businesses?
For instance, if you sell flowers, Valentine’s Day, Memorial Day, Mother’s Day, Christmas, and Easter are your peak seasons. It comes down to the product types and the culture of the target market, meaning businesses have varying peak season dates as dictated by their individual market trends.
