*This article was previously published on the Inbound Logistics website.
Timeliness is top of mind during the holiday season. As Santa prepares for his ride around the world to give every child a gift by Christmas morning, product companies and retailers are also busy planning to meet increasing customer delivery demands during the holidays. Santa has his magic and his elves, but product companies must find other ways to plan and proactively prepare their supply chains for optimal performance. Fortunately, advanced analytics technologies can help product companies and supply chain managers cope with large spikes and delivery demand this time of year.
The period between November 1 and December 1 can account for up to 50% of the revenue for certain industries such as toy manufacturers and shipping volumes increase accordingly. Data released by the National Retail Federation has already projected a 3.7% increase in retail sales in November and December to equal $630.5 billion. For product companies, delivery timeliness is critical. In the battle for shelf space, a late delivery to a retailer could cause them to lose high percentages of revenue. For instance, if a large shipment is scheduled to arrive at a retail facility before Christmas but doesn’t arrive until four days after Christmas, then not only do you lose shelf space, but you also have to discount post-holidays in order to sell the product. This means heavy revenue losses during a critical revenue-earning time of year.
A lot of product companies focus on using technology for demand forecasting, but there are many other areas that advanced analytics technologies can be just as valuable—such as the ability to track shipments and alert on disruptions in real-time to ensure optimal supply chain efficiency. This includes planning to overcome challenges around cross-docking, inventory management, and on-time delivery.
Through predictive analytics, product companies can uncover information to help make decisions for optimal supply chain planning, such as understanding which types of shipments to expedite, which carriers have capacity, which ports appear to be congested, what shipping routes are best for air, rail, and road, what time is best for clearing customs efficiently, etc. These advanced analytics solutions focus on correlating and analyzing historical data from transportation management systems, carriers, 3PLs, suppliers, ERP systems, etc. in order to drive smarter decisions and ensure that inventory arrives in time. Ultimately, this leads to better communications between product companies and those companies transporting their goods.
Optimizing cargo pick-up times can be just as important as accurate on-time delivery. Leveraging historical data, predictive analytics can also determine how long it took a specific carrier on a specific shipping route to get to a pick-up location. It also has the ability to track real-time shipment location data and adjust the anticipated arrival time by considering historical patterns of disruption caused by weather, port congestion, customs clearing time, etc. More so, by combing real-time location and ERP data, advanced analytics can provide visibility down to the SKU level.
Thanks to predictive analytics, product companies have the ability to outshine competitors and stay ahead of delivery demands this time of year.