Inflated inventories, expedite charges, constant disruptions and uncertainty over delivery times are perennial worries for anyone who has to deliver raw materials to a production plant or finished goods to a retailer.
Supply chain planning and technology teams have engineered new ways for suppliers, manufacturers and retailers to collaborate, but the freight side of the puzzle has been lacking until recently. Now, as companies gain access to real-time supply chain visibility data and analytics, things are rapidly improving.
What initially started as “Where’s my truck?” with real-time visibility platforms, has magnified one of the underlying issues in global supply chain management: What is the impact on my supply and demand? Now those same companies are looking to leverage real-time transportation data to supply their forecasting and decision tools.
Because real-time supply chain visibility platforms provide one single source of the truth, vendors, partners and customers who proactively share their data have multiple opportunities to collaborate to improve operations. In this post, I’ll focus on how collaborative forecasting can be leveraged to better manage supply.
Mitigating Supply-Side Disruptions
Consider a hypothetical example of a manufacturer of pasta. This company continues to grapple daily with the constant changes of demand from customers. Our data shows how F&B volumes have seen significant growth and decline week to week since COVID. This isn’t isolated to F&B companies, either.
As demand spikes for finished goods, you need to either have stock safety stock or be ready to increase production, which requires raw materials. Now imagine that an additional problem arises: A hurricane hits the port that usually receives the packaging material, causing an estimated four-day delay in the original ETA.
These kinds of supply-side disruptions – whether COVID-related or otherwise – can be mitigated when all stakeholders across the supply chain collaborate based on accurate, real-time data. Because this hypothetical manufacturer is apprised of the disruptions and is armed with new ETAs, they can alert the production line as to the new schedules, and optimize staffing and production for different jobs.
Similarly, the retail customer can be apprised of the new delivery schedules for the finished product, and be kept informed as to whether the quantity matches their original order (sometimes disruptions cause a reduction in the volume and quantity of products that can be manufactured). All of this collaborative forecasting can make an appreciable, positive impact on OTIF performance and other key operational metrics.
Take another real-world example: A seasoned supply chain manager with a major beverage maker reports that since they’ve started collaborating with their suppliers and customers based on real-time supply chain visibility data, the company’s on-time and in-full record has improved dramatically. “It’s been game-changing to help us with OTIF,” the manager told me. “If your OTIF is not where it needs to be in the customer’s eyes, don’t even bother about asking about new items or running promotions. This technology has helped us get there.”
Better Inventory Management
Real-time supply chain data can also help companies better manage inventory. That’s because most older forecasting models assume fixed sourcing locations and fixed lead times. But if real-time visibility tells me that the planned transit time of three days is, in fact, really 16 hours, I have an opportunity to update my master data to reflect true transit time based on precise information. This allows companies to reduce inventory carrying costs, which leads to significant savings at scale.
In addition, if I can see in real-time any location that has that SKU on hand, I can identify alternate sourcing locations or excess stock in other markets that I can source from, rather than having to buy additional material. Given that most companies carry around 30 days of finished goods ready to ship, those savings add up quickly.
The Path to Greater Efficiencies
It’s been my observation that companies leveraging real-time visibility often progress along three stages.
- The first stage is typically focused on shippers and carriers working together to manage carrier performance for the freight that is managed by that shipper.
- The second stage expands to pre-paid inbound freight and outbound CPU visibility, which allows for total end-to-end visibility for any shipments into and out of a shippers warehousing network.
- The third stage expands to include the collaborative forecasting techniques I’ve discussed here, aimed to better manage lead times, production schedules and the like based on the reality on the ground.
By looking at the same data, together, all parties can work toward objective improvement plans that benefit all.
Real-time visibility platforms are no longer solely about where trucks are at any given time, and FourKites is changing the way companies operate with their supply chain partners. My next post will focus on additional ways to collaborate to optimize demand.