The discussion surrounding automotive technology is dominated by autonomous vehicles and advanced robotic control systems. You’ll also hear about numerous emerging in-car technologies including automatic emergency braking, lane departure warning systems, adaptive cruise control, stolen car tracking systems, and an array of in-vehicle infotainment technologies.
But the topic of automotive technology stretches beyond the bells and whistles designed to attract the average consumer as a car buyer.
Driving from Behind the Desk
ASUG members might be interested in all the fancy controls and conveniences that come with technology when sitting behind the wheel. But when sitting behind a desk, they’re likely more interested in knowing how technology is affecting the automotive supply chain, the engineering shop floor, the market-facing commercial side of getting cars to market, and the after-sales operation that follows.
The SAP division dedicated to the automotive industry is primarily concerned with how to best get automotive business operations to become more data-driven. Georg Kube, SAP’s global VP of automotive, works with the SAP discrete manufacturing division on initiatives designed to modernize legacy IT structures in the auto industry with an emphasis on creating a global operating model that drives consistency and process improvement.
During his keynote address at Best Practices for Automotive, Oct. 7–8 in Detroit, Kube will share five strategic priorities to run your operations better today while preparing for the disruption that will come along with the future of mobility. He’ll also share how these priorities are driving SAP’s strategy and road map to help automotive companies become intelligent enterprises.
Unique Automotive Automation IT Challenges
What makes automating automotive businesses into new, data-driven, cloud-centric operating models so tough?
One of the key challenges is the huge number of SKUs that an auto manufacturer needs to keep track of at any one time to feed its production line. A SKU itself takes the form of a machine-readable barcode printed onto product or component labels that allows automotive companies to scan and track the movement of inventory.
Toyota is one of the automakers showcasing its work in this area at the SAP Best Practices for Automotive conference. It has tackled its SKU mountain and used SAP Integrated Business Planning to establish a global template to provide time-series-based demand and supply planning, as well as vehicle-driven accessory demand planning, product life cycle planning, and financial planning.
During his session, Mohamed Najera, associate partner, industrial EA SAP, IBM Global Business Services will discuss how Toyota improved its balance between inventory and profitability, as well as demand, supply, and financial planning—all with one common platform.
The End-to-End for Automotive Technologies
The term end-to-end is massively overused in technology circles, but perhaps nowhere is it so substantially validated than in automotive supply chain management. In this industry, we can clearly see raw materials moving through machining processes onward to market, and a whole tier of other distinct phases that need to happen before we, as car owners, drive off the dealership lot.
Consequently, SAP’s software tools in this area are focused on optimizing resource efficiency by creating supply plans based on prioritized demands, allocations, and supply chain constraints. In the SAP automotive IT world, end-to-end breaks down this way:
- The management of base resources through demand-driven material requirements planning (DDMRP).
- The manufacturing of discrete components that come together to form automotive parts.
- The in-shop assembly of automotive end products.
- The testing and safety rating of each finished product before it rolls off the production line.
- The shipping of finished products to distribution hubs and channel sales partners.
- The integration of after-sales and vehicle maintenance requirements into the supply chain that the organization uses as its base foundation for manufacturing.
- The need to apply stringent levels of data governance through this entire life cycle so that supplier and customer data is segmented, secured, and policy controlled to make sure each stakeholder in the supply chain is protected and served within the full scope of regulatory compliance demands.
Connecting Siloed Data Is Critical
This is not an exhaustive list, and it’s certainly not an official seven-step guide. But it does go to show how the phases of automotive production exist as defined stages. Even if we can successfully define production, there’s another challenge: The automotive industry has plenty of data resources for each tier of production, but it’s often disconnected, siloed data that has no clear owner or point of management.
If the automotive industry wants to embrace digital transformation and enjoy the benefits of decentralized cloud-centric services-based computing, then master data management is a primary requirement. SAP is positioning its SAP Integrated Business Planning as the antidote to this, offering interconnectedness when used alongside SAP Leonardo to construct Design-Thinking-driven technologies that can pave the way to data management help delivered through artificial intelligence (AI).
Where AI Is Changing the Automotive World
Automakers see AI as a huge opportunity and are currently dabbling in it to assess consumer demand. In this respect, AI plays a key role in helping create new transparency into demand levels across the short, medium, and long-term. This approach can help reduce stock waste and result in a sharper competitive edge.
Currently, AI will be used to manage complex business rule frameworks inside contemporary automotive organizations. SAP works directly in this space with SAP S/4HANA and SAP Business Rule Framework plus (BRFplus) to help auto firms create business rules that can ultimately appear inside different applications.
Looking forward, AI also will be used to serve drivers themselves. According to Gartner, 250 million cars will be connected to each other and the infrastructure around them by 2020 through various V2X (vehicle-to-everything communication) systems. But this will generate even more massive amounts of data than auto manufacturers are generating within their plants. It’s clear why it’s so important to know where that data is, who owns it, and how it should be managed and fed into SAP S/4HANA’s analytics engine.
The conversation around automotive technology is vast and complicated. That's why you should join us to hear from the automakers sharing their own experiences with back-office automation, migrations to SAP S/4HANA, the connected warehouse, and smart shop floors during Best Practices for Automotive.
Register today to join your peers to discuss these topics and beyond at the Best Practices for Automotive conference, Oct. 7–8, in Detroit.