Procurement in the automotive industry is complex. The number of parts in a modern car varies. But on average, there are 30,000 parts if you count everything from the nuts and bolts to the engine.
Sourcing all these parts is integral to the automotive industry but time-consuming and complicated.
Most manufacturing companies have sophisticated ERP, finance, engineering, and quality systems. But when it comes time for purchasing, most automotive suppliers and OEMs are stuck in an Excel world. So they’re straddled between systems, pulling data from all over the company.
As a result, there’s a dispersion of data throughout the company, and data isn’t easy to find. Suppliers and manufacturers are hungry for a system to bring all this information together. Enter predictive procurement. Predictive procurement is central to solving a wide range of complex supply chain problems efficiently and effectively.
How can predictive procurement help solve the automotive industry’s biggest challenges today? And how can it help business leaders make quicker, more intelligent decisions?
Arkestro Account Executives Mike Betz and Mike Betts discuss how Predictive Procurement Orchestration (PPO) is the future of the automotive industry.
What is the challenge or uniqueness of automotive sourcing and procurement?
Mike Betts: I think the uniqueness is that automotive manufacturers are typically high-volume, low-margin operations and not early adopters of new technologies. However, right now, the industry’s EV direction is driving the transformation of its supply chain to include new companies not acclimated to USMCA regulation and a heavy dose of design change-driven sourcing activity to meet launch schedules.
Additionally, the physical tracking of non-conforming material (reverse material flow) is frequently a cumbersome manual process, even using handwritten tags, which is error-prone and impacts inventory reconciliation accuracy. So the speed of sourcing or procurement events can impact premium freight, obsolescence, repair dwell time, and even machine downtime.
So in the automotive industry right now, procurement and sourcing processes have heightened operational efficiency impact. What comes in handy with the Arkestro approach is the event simulation. It enables incredible acceleration and automation of otherwise disrupted purchasing and sourcing process workflow.
How does predictive procurement help the automotive purchasing process?
Mike Betz: I think you have to step back and say it affects more than just the purchasing processes within automotive or any manufacturing company. It really affects the entire corporation across the enterprise.
The example that I would give is a salesperson who’s selling to General Motors, for example or any OEM. And that person walks back into the purchasing department and says, “Hey, you know what? I have a great opportunity to win new business here.”
Sixty to 70% of that new business award is going to come from the supply chain, which means they’re leaning on purchasing to help them with this new opportunity and find suppliers for it. Frankly, that’s a very difficult and time-consuming task. So, what seems like it should take a couple of days could take a few weeks—even months—to just get a response back to the OEM customer.
Predictive procurement saves time
With predictive procurement, I’m looking at cutting the time from three weeks to three minutes. Immediately I have instant feedback on what my supply chain is capable of sourcing these parts for. So now I’m putting my salesperson in a position to respond quicker to my customer. I’m putting my salesperson in a position to have accurate, clean data. So now, when they defend the price in front of the customer, they have a strong base of knowledge on how the quote was put together. That’s just one example.
I can go around the company. This can become the CFOs secret weapon in navigating choppy waters with visibility of purchasing data to forecast margin from COGS and control G&A. When designing products, the engineering folks constantly interact with purchasing to figure out, “Okay, what is the potential cost impact of an engineering change?”
So, predictive procurement definitely helps the purchasing process. But it affects the entire organization. At the end of the day, what predictive procurement delivers is a faster way to do business from an enterprise perspective.
How does data technology bridge the gap between analytics and operations?
Mike Betts: Right now, in automotive, there is a huge increase in the number of vehicle platform launches scheduled because OEMs are trying to hit targets for road-ready electric vehicles in production vehicle sales. And that’s resulted in Tier 1s being inundated with programs to quote. So they have to prioritize which programs to quote (a manual process with lots of back-and-forth) due to limited human resources.
What a company like Arkestro brings to the table is it allows Tier 1 (now with their limited resources) to respond to more quotes faster. Now they can handle things via an email with a suggested price already there, instant feedback for submitted proposal pricing, and terms and conditions they can address rapidly. They don’t have to search through 20 tabs of an Excel spreadsheet or wait two weeks to get feedback.
Arkestro streamlines the process to enable suppliers to handle more engagement in new program sourcing events with existing resources.
How does predictive sourcing cut sourcing cycle time in the auto industry?
Mike Betts: Along the lines of the example with all the electric vehicle platforms being launched. For the OEMs to get an ROI from each platform, they have to get an ROI off of fewer vehicle sales because there are more vehicles on the market.
So, you have to reduce your program and development launch costs for a new vehicle to break even in the same amount of time as you would have when there were half as many vehicle launches.
By reducing the cycle time of a sourcing or procurement event, Arkestro helps to hit that program launch schedule—like during a PPAP (Production Part Approval Process), for example. Every part of the vehicle goes through this process. And it requires sourcing and procurement processes in the midst of it. When you can do that faster, hitting inventory fill dates, release schedules, and build deadlines with correct change levels is much easier. This is where Arkestro contributes!
Mike Betz: Going back to the concept of the enterprise being affected and purchasing responding quicker to engineering on changes: if I can have instantaneous feedback to my engineering team, that’s certainly going to cut the cycle time. And that transcends throughout the entire organization.
If I can provide my deal team or the finance team with alternatives, they can start chewing through the data and figuring out the profitability level of the programs that we’re quoting on. If I can speed up that process, my sales team will be in a better position to respond to the customer, not only in terms of defending the price but bring speed to the market—being the first one to respond to the customer. This gives sales more time for interaction and collaboration with the potential customer.
How can you drive direct material cost improvement in inflationary times with predictive procurement?
Mike Betz: I think that the key word here is predictive and analyzing third-party industry data. And that’s certainly the value of Arkestro. It’s not only looking at the customer information and supply chain data but bringing in third-party sources. This prediction of where the market is heading can provide warning signals to not only purchasing but also to the finance team and C-suite that something’s happening where their trend lines are coming up or coming down.
This way, you can better brace for an impact. If the trend line is coming down or up, it’s time to start talking with your customers and suppliers. It’s all about predictability and looking at that into the future. The value Arkestro creates is bringing all this data together in a centralized format. So you can start to run those analytics and be more prescriptive.
How will AI and machine learning drive the future of auto supply chains?
Mike Betts: I think AI and machine learning combined with behavioral science and game theory are critical. Procurement and sourcing are a series of dialogue-driven collaborative events. And if you can get instant feedback that gives you confidence about a decision you’re going to make—opposed to spending two or three weeks going back and forth—it will enable you to make a decision faster. And that streamlines all the workflow surrounding that activity, whether it’s sourcing or procurement.
I think the future of AI and machine learning will incorporate other sciences. Behavioral science and game theory are front burners for that. This will enable much faster transactions, decisions about preferred suppliers, capabilities, risk assessments, and program awards. This will contribute to shrinking that program development life cycle and enable vehicle manufacturers to turn around new products at a rate much closer to how cell phone manufacturers do today.
What is user adoption like (in the auto industry) with embedded systems like Arkestro?
Mike Betz: I think that embedded systems are taking hold of OEMs and suppliers based on overall market conditions and working environments. It is an approach that is being adopted at an increasing rate. Profit margins in the automotive market are razor-thin. In the past, companies have invested millions of dollars into ERP systems, CAD systems, engineering-type tools, PLM systems, and all the things we discussed earlier.
And frankly, it’s questionable whether the value of those transactional systems has been delivered. For example, along comes a new app, a new kind of app to install and train users. So we put a project team together. Then we’re in a war room implementing the system and rolling it out over a protracted period. Those days are gone, especially in the automotive market, where the supply chain is volatile, margins razor-thin, and companies don’t have the time for major system installations.
So, companies are turning to embedded applications like Arkestro, which can sit in the cloud and leverage the data they’ve already accumulated from these transactional systems. And that’s the key—taking the data, leveraging what you have, bringing it into a central format, and then running analytics on that information. I think that’s certainly a trend that we’re seeing in automotive.
Predictive Procurement: The Future of the Automotive Industry
The auto industry faces a wide range of complex and evolving needs. Procurement professionals need technology that simplifies and speeds up the purchasing process while providing strategic value.
Arkestro does just that. Predictive Procurement delivers tangible business impact without organizations having to re-do their entire tech stack to be more strategic. Combining machine learning, human behavior science, and game theory, Arkestro helps you find the right supplier, at the right price, right now.
Want to learn more? Watch the Auto Panel From Predictive Pricing to Predictive Procurement: The Road To Self-Driving from Optimal Las Vegas here.