All the way at the far end of the supply chain, when an automobile reaches its end consumer, it looks like they’re buying one large item. But automotive manufacturers know differently—they know that each car on the road is really comprised of about 20,000 different parts, and all of them had to come from somewhere.

After being sourced, they had to be stored, allocated for various production plans, brought to the production plant, and assembled into a road-worthy vehicle that someone could drive off the lot at their local car dealership.

This rundown barely gets into the real complexities of the automotive supply chain, and yet it should at least suggest the high degree of complexity that would be involved in true supply chain optimization. Given the number of moving parts, it would be ridiculous to expect a single supply chain planner with an Excel spreadsheet to create a supply stream that was even remotely optimized. In the past, for practical purposes this has meant that a fair amount of waste was baked into the structure of the automotive industry—but with the advent of digitization and the rise of Industry 4.0, it’s increasingly possible to create value chains that reduce waste and ward off disruptions. 

What’s more is that most automakers already know this, which is why a recent Emporias survey found that 45% of logistics managers in the auto industry said that potential cost savings to be found in their supply chains were either ‘high’ or ‘very high.’ The question is: how do you optimize your supply chain in order to achieve those savings?

Integrating Inbound and Outbound Logistics

When 20,000 different parts go into creating one product, it’s easy to see how a small supply chain disruption could set back production and distribution workflows considerably. You might be making your outbound logistics plans with all the information in the world, but if something happens to a shipment of raw materials in transit, the risk of late deliveries (or of increased costs due to the necessity of using premium freight) is bound to spike. Unfortunately, small disruptions (to say nothing of large disruptions) are an inevitable fact of supply chain management. The question is, how can you minimize their likelihood and impact? 

For starters, you can try integrating your inbound and outbound logistics processes. Though these are both crucial elements of the larger supply chain, they often wind up siloized, meaning that when something goes wrong on the inbound side it can be difficult for outbound transport planners to adjust accordingly. By integrating these two processes—either connecting them through shared IT infrastructure or giving them a closer organizational relationship—you can ensure that the left hand always knows what the right is doing, so to speak. Rather than finding at the last minute that you can’t complete production because a part earmarked for a particular production flow was damaged in transit, you can identify that possibility far in advance.

You might even leverage IoT (internet of things) devices to monitor raw materials as they’re being shipped, so that if something goes wrong you can re-allocate from your buffer stock or reshuffle your production programs as needed—leading to improved throughput and thus a greater likelihood of on-time customer delivery.

Ultimately, this integration is going to represent the foundation of any optimization attempts within the broader supply chain. Why? Because without a high degree of visibility shared between these two touchpoints, it will be impossible to predict the outcomes and consequences of any proposed changes. Sure, you can implement new ideas in route or tour planning, or reconfigure your inventory management, but without access to mission critical, digitized data from these two functions, you’re gambling with the health of your supply stream. At the same time, of course, this has been an industry-wide stumbling block, with 90% of automotive executives claiming that their companies’ logistics master data is incomplete or outdated.   

Backhauls, Milk Runs, LTLs

Okay, let’s say you’ve successfully integrated the processes discussed above into a unified digital workflow—what then? Sure, we’ve seen the ways that you can be more flexible in the face of disruptions, but how else will your supply chain respond to increased visibility of the sort under discussion? For starters, you might be able to take better advantages of milk runs and backhauls in order to get the most out of your freight routes. 

If you think of transportation management like a factory, the best way to optimize throughput is to look closely at any way to decrease the total number of trips your fleet has to take. This means only using LTLs (less-than-full truckloads) when they’re strategically savvy, rather than when you simply can’t find a way to fill an entire truck with products. Here, digitization will be your best friend. Once the relevant supply chain data is made available to you, it’s suddenly possible to run advanced analytics algorithms on it in order to uncover potential opportunities to boost efficiency. Where a supply chain planner using pen and ink might not be able to identify a correspondence in timing or route structure that enables you to consistently make use of a backhaul, for instance, advanced analytics processes can uncover potential areas for optimization with relative ease. This means that everything from the structure of your transport network to the demand forecasts you use to determine your sourcing requirements can be analyzed and improved upon.

Lean Supply Chain Management

So far, we’ve listed a handful of ways that any given automotive supply chain might be improved by increased visibility and the use of analytics. Because automotive supply chains are some of the most complex across any industry, whatever chance you have to stabilize costs can have a huge impact. But what if we go one step further? That’s right, we’re talking about lean supply chain management. As you continually work to boost visibility and integration, you can move beyond discrete process improvements, and instead begin to rethink the value chain in its entirety.

Previously, the potential for disconnect between the two halves of the supply chain meant that, for most automakers, a fair amount of buffer stock would have been required. Even as parts were being distributed to regional manufacturing centers, it would have been virtually impossible to go fully lean—meaning that you’d be spending considerable money and resources tracking and storing unused parts. With a high enough degree of visibility, you could largely do away with that buffer stock, reducing your overall costs. Sure, you’re putting more pressure on your supply chain, but in a truly digitized environment your supply chain should be able to handle that pressure. Likewise, your transport flows could rely less on static routes and tours and instead use on-the-fly planning to choose the most efficient path each time. This may sound futuristic, but as Industry 4.0 gains steam in the auto industry, these ideas really could shape the automotive supply chain of the future.  

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