Product shortages and supply-chain disruptions have dominated the headlines in the past few years, fueled by the far-reaching impact of pandemics, natural disasters, and political instability. Supply chain teams must predict, prepare, and respond to rapidly evolving demand and a continually changing product and channel mix.
While AI can help unpack the complexity of today's supply chain, many companies do not have sufficient experience to scale Artificial Intelligence (AI) initiatives across their business functions.
Our unique approach to AI tackles exactly that.
At SAP, we deliver AI that is available from day one, as it is already built into the SAP applications that power your most critical business processes. It works for your entire business because it is developed using extensive industry-specific data and deep process knowledge. Organizations can use it with confidence, as it is created using responsible AI practices. In essence, SAP AI is AI built for business.
AI is a Game Changer for Supply Chain
CIOs are building more resiliency into their supply chain processes and adopting modern technology to increase business visibility, foresight, and efficiency. AI is instrumental in enabling the modern resilient digital supply chain. Let’s take a closer look.
First, AI provides the visibility and foresight to help organizations navigate changing market dynamics with greater agility and efficiency. For example, you can optimize inventory management by leveraging insights from real-time IoT feeds from moving goods across the globe. You can also better understand causes and effects of supply chain interactions by taking advantage of prediction models and correlation analysis.
Second, when AI is applied across end-to-end supply chain business processes, functional teams can more effectively collaborate, communicate, and balance supply chain trade-offs. For example, with visibility into planning, manufacturing, and logistics, it is possible to use advanced analytics to simulate whether it is best to pay for overtime production at a given plant or incur transportation costs from different plants.
SAP AI Powers a Resilient End-to-End Supply Chain
At SAP, we enable you to adopt AI strategically across the entire design-to-operate business process. And since AI-powered insights, recommendations, and automation are built into your SAP applications, you can transform every aspect of your supply chain faster and with less risk – from day one.
The result is greater visibility and efficient collaboration across your enterprise that grow supply chain’s agility and resilience. Let's look at a few examples.
Simplifying the Idea-to-Market Phase
With business AI from SAP, your product development teams can implement customer feedback faster and improve product demand. The AI capabilities embedded in our solutions also allow better synchronization among all stakeholders in and beyond the design phase and shorten the product time to market with faster product designs.
For example, AI-powered tools in SAP Product Lifecycle Costing assist costing engineers to prepare intelligent bill of materials for products early in the design phase and define costs of future products even when they are just ideas. Additionally, SAP Enterprise Product Development uses AI algorithms to automatically generate hotspots and map them to images of corresponding items in S/4HANA and the interactive 2D SAP Commerce Cloud catalog when technicians upload 2D images of an asset. This intelligence empowers you to innovate, iterate, and introduce new products faster.
Optimizing the Plan-to-Optimize-Fulfillment Phase
Our business AI technology can help you anticipate risks and take immediate corrective actions. For example, we all know that having a complete picture of the daily demand is essential to optimize profitability, deliver high customer service levels, and enable accurate supply planning. AI-powered demand-sensing algorithms within SAP Integrated Business Planning for supply chain (IBP) can produce accurate short-term forecasts daily by efficiently parsing high volumes of diverse data.
Demand planning with artificial intelligence in SAP Integrated Business Planning for Supply Chain
Take the example of ZF Friedrichshafen, a global technology innovator in mobility for the automotive industry, which utilizes demand planning capabilities in SAP IBP to quickly anticipate and adapt to shifting demand. By using AI embedded within SAP IBP, ZF Friedrichshafen decreased its forecast turnaround time by 92%, freeing planners from time-consuming, repetitive tasks. As a result, the company now enjoys flexible control over levels of the supply chain, including location, product, channel, and customer.
Streamlining the Make-to-Inspect Phase
Business AI in our applications can also help you improve manufacturing accuracy, reduce inventory-carrying costs, and meet delivery deadlines. For example, AI embedded in SAP Digital Manufacturing enhances the productivity of shop floor operators by simplifying visual inspection tasks. Algorithms built into this SAP solution process images of the manufactured parts, enable you to identify defects and log them with the appropriate nonconformance code. This automation also ensures that defective parts are appropriately handled.
Visual Inspection with artificial intelligence in SAP Digital Manufacturing
Additionally, AI-powered manufacturing analytics within SAP S/4HANA helps you optimize resource orchestrations by automatically dispatching manufacturing operations to available resources. These advanced analytics also help you reduce your inventory-carrying costs with prompt detection of slow-moving materials and accurate delivery date predictions. Enhancing Acquire-to-Decommission Phase
Leveraging AI from SAP, you can enhance the lifecycle management of assets. We combine AI, the Internet of Things, and rule-based frameworks, to help you correlate sensor data, inspection results, and historical maintenance records so you can devise predictive and prescriptive maintenance strategies. For example, AI models in SAP Asset Performance Management trained on your historical data can detect anomalies in live data from equipment sensors and generate a maintenance backlog to address the issue. With adequately trained AI models, you can also determine the probability of impending equipment failures and deliver advanced warnings to maintenance and operations.