5 Keys to Managing Costs in the Automotive Supply Chain
Brian Hoey - March 19, 2020
Let’s say you’re a kid, and you’re trying to set up a lemonade stand in front of your parents’ house. You go to the store (possibly with parental supervision) to get lemons and sugar, you come home and mix the two into a pitcher, and you set up a little folding table near the sidewalk. Since children are notoriously bad at big-picture thinking, you probably think of the lemons and the sugar as your only real costs, and you price the cups of lemonade (which are set out by the pitcher) accordingly in order to achieve a worthwhile ROI.
Of course, as an adult, it’s easy to see that there were a number of hidden costs that you weren’t thinking about at the time: the cups, the pitcher, the folding table (all of which were in your “inventory,” so to speak), to say nothing of labor, time, transport to and from the grocery store, etc. In this way, it’s a lot like the modern supply chain. When it comes to something like an automobile, there are thousands of parts, countless hours of labor, transport costs, and so much more that counts against your eventual ROI. While this might be daunting from a pure accounting perspective (i.e. how can you keep track of all of your supply chain costs effectively?), it’s actually an opportunity in disguise. The more costs there are, the more opportunities you have for optimization.
1. Forecast Accuracy
For our lemonade stand above, one potential pitfall you could easily run into is overestimating demand for lemonade. This leaves you with a bunch of unsold stock that has to be stored in the fridge or thrown away, and it means that a percentage of the money you spent on raw materials was wasted. This happens all the time in the automotive industry. Why? Because it’s difficult to forecast consumer demand accurately. And yet, this is an area with a huge upside in terms of cost optimizations—cost optimizations that are increasingly available in the Industry 4.0 era to those who are willing to collect and take advantage of the right data. By gathering information about customer buying patterns and market conditions from every applicable touchpoint on the value chain and using advanced analytics to derive insights from them, you can create forecasts that are more accurate than ever before. In this way, you stand to reduce the costs associated with SLOB (slow-moving, obsolete stock).
2. Sales and Operations Planning
Once your forecasts are improved, the next question is how to operationalize those improved forecasts into actual supply chain optimization. Here, it’s critical to have the right planning workflows in place, specifically: sales and operations planning (S&OP) and sales and operations execution (S&OE). These two processes work in tandem to help you match your capacity and throughput to real demand. S&OP tends to involve big picture strategies based on quarterly or yearly projections, while S&OE focuses on making minute adjustments to inventory and transport plans in order to keep those plans on track. By implementing these workflows, you can make sure that your entire supply chain is responsive enough to adapt to changing forecasts in real-time, thereby maximizing the value of those forecasts. It is, however, important to note that effective S&OE requires a level of supply chain visibility and IT integration (especially regarding Industry 4.0 technologies like IoT devices and RFID tracking chips) that not every supply chain can boast.
3. Network Optimization
Advanced analytics typically come in two flavors: predictive and prescriptive. Predictive analytics are what we’ve been talking about above—they help turn data into improved predictions for demand, shipping costs, potential disruptions, etc. Prescriptive analytics, on the other hand, can analyze the structure of your factory floor, logistics network, or supply chain in order to suggest potential improvements. Maybe one of your plants is redundant and you’d be better of increasing capacity at another one. Perhaps you’ve got a warehouse across town that could be moved to a more central location in order to save on fuel costs. Maybe you’re missing a chance to utilize backhauls in your transport network. Whatever areas for improvement or optimization there might be, advanced prescriptive analytics are a reliable way to find them. Of course, the output here is only as valuable as the data you back it up with—meaning that the more high quality information you can collect about what happens in your value stream the more effectively you can reduce hidden costs and increase your operational agility.
4. Planning for Every Part
If there’s a major theme to these cost optimization tips, it’s the importance of visibility. And if you can extend this visibility to the parts level, you can optimize costs even further while increasing supply chain control. This might seem daunting in something as complex as the automotive supply chain, but the huge number of necessary parts is precisely why tracking each part’s journey from your suppliers to your customers (in the form of finished products containing thousands of individual parts) can be so value-additive. You might, for instance, find that a certain part from a certain supplier has a much higher reject rate than others, in which case you can work to either source those parts from elsewhere or make some adjustment to the way they’re handled. Conversely, you might notice that parts that are most frequently combined in the manufacturing process aren’t actually being stored together, resulting in inefficiencies in your production flows. Again, this is pretty deep-in-the-weeds stuff, but it can potentially add up to a sizable value-add.
5. Vendor Management
This one is related to the previous suggestion, but it bears its own mention. Especially in a PFEP workflow, it can be extremely valuable to have some visibility into your suppliers’ IT, which can be most easily achieved through software integration. Once you and your suppliers have that level of transparency, it’s much easier to cut back on the kinds of delays and disruptions that often result from poor inter-operational infrastructure. Since these delays often prove costly, this provides an excellent opportunity to keep costs in check. The only catch is that, in order to truly take advantage of a high level of integration, you need to have at least some of the planning and analytics capabilities we outlined above.