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Excessive inventory, 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.
While the supply chain planning and technology teams have engineered new ways for suppliers, manufacturers and retailers to collaborate, the freight side of the puzzle has been lacking until recently. Now, as companies gain access to more data and analytics, things are rapidly improving.
And with insights comes the opportunity to tackle one of the underlying issues in global supply chain management: What is the impact of my transportation network on my supply and demand?
By having a single source of the truth, vendors, partners and customers who proactively share their data have multiple opportunities to collaborate to improve planning and forecasting for supply and demand.
Consider a hypothetical example of a pasta manufacturer. This company continues to grapple daily with the constant changes of demand from customers. As demand spikes for finished goods, you need to either have 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 of the new schedules, and optimize staffing and production for different jobs.
Similarly, the retailer 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 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.”
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.
It’s been my observation that companies leveraging real-time visibility often progress along three stages:
By looking at the same data, together, all parties can work toward objective improvement plans that benefit all.
On the other side of the supply chain coin, retailers, manufacturers and suppliers are always managing wild, unexpected swings in demand because forecasting is an estimate based on the known or planned factors. But long-term disruptions like COVID expose problems at a much broader level as leadership identifies gaps in knowledge. All of this has accelerated the demand for supply-chain visibility. So, how can you plan for the unplanned? Be agile.
Supply chain management systems have addressed demand planning for years and continue to advance in sophistication. And they’re great doing what they do: If demand for a product is going to increase five percent, the platforms will adjust accordingly. The foundation for many of these systems is the assumption that material is moving according to plan, and so they don’t tell you where bottlenecks are.
By contrast, let’s consider: What if the port of loading is backlogged and there is a five-day delay? What if the carrier breaks down, causing a seven-hour delay, but you need the product right away? It’s only when you add visibility into the mix that you can really get a handle on demand shocks, and where and how to best address any given scenario.
Best-in-class supply chain visibility requires greater transparency than many companies have been accustomed to. And while many have grown comfortable with transparency in pockets, those who deploy visibility at scale across inbound, inter-company and finished goods have an undeniable edge. By sharing data about the freight that all parties want to arrive on time, suppliers, shippers, carriers and receivers gain the power to do more work with less labor – both at the loading dock and the back office. The question is no longer just, “Where’s my truck?” It’s, “I know where my truck is and when it’s supposed to arrive, so now what?”
Here’s an example from one of our grocery retail customers. The company operates a network of more than 100 large grocery stores across the US, and they work with more than 100 carriers to get food to the stores on time. COVID made their workers’ lives harder; not only were customers buying things in a panic, but staffing had fallen, too, which made it even harder to keep up.
“Our stores were getting completely wiped out, and we were having to react almost every single day,” one manager told us. They faced shortages of all the things you might remember reading about: pasta, toilet paper, hand sanitizer. Fortunately, they had recently deployed a visibility system so they, their suppliers, receiving distribution centers and their carriers could all see where their shipments were at any given time.
The crush of consumer buying would normally have swamped their already thin staffing. This time was different. Because they’d urged their business partners to adopt visibility, the shippers, carriers and the grocery chain all rallied to keep up. Now they knew where almost every load was, when it would arrive and why delays were happening. Suddenly, all that understaffing and remote work became much more manageable. The transparency enabled by visibility prevented logistical chaos.
Meanwhile, the increased transparency for pre-paid inbound orders helped the retailer monitor how often they ordered from different vendors. Day-of-week data analysis revealed buying patterns they had not seen before. The company ultimately saved money by ordering more by the pallet instead of smaller quantities. Buyers learned that frequent ordering would no longer be required to buffer safety stock because visibility gave them confidence that loads would arrive on time and with the correct SKUs. Better still, logistics could detect incorrect lead times that had previously led them to think shipments were late before they’d had a chance to leave the shipping dock.
With this actionable intelligence at their fingertips, the retailer’s OTIF stats improved accordingly, and overall performance soared. “We thought we’d find a lot of issues and opportunities with our vendor partners. We actually found opportunities within ourselves,” that manager said. “There were actually multiple instances where we were creating late trucks. That was a little bit of a gut check. We had to swallow our pride on that one.” As I mentioned, collaborative forecasting hits its stride once everyone in the supply chain is onboard with visibility. This grocery retailer’s network achieved just that in about two years.
The end result? Reduced inventory and overtime from dealing with late trucks and overstaffing, stronger relationships, improved timeliness, and better problem-solving all around. “We’re all looking at the same data,” the manager said. “It’s like I tell our vendors: If you’re on the fence about sharing this much data, come and talk to me. It all works.”
That’s a great outcome that demonstrates the power of real-time supply chain data to help manage fluctuations in demand.
Is your supply chain struggling to keep up with supply or demand? Let’s talk about it — let us know how we can help.