SAP Sets Vision for Autonomous Supply Chain

⇨ The evolution of supply chains progresses through three critical stages: digital, adaptive, and autonomous, with each stage building on the previous one to enhance efficiency and responsiveness.

⇨ Technological advancements such as predictive analytics, machine learning, and generative AI play a pivotal role in transitioning supply chains towards autonomy, enabling decision-making with minimal human intervention.

⇨ Businesses must invest in understanding their end-to-end processes, develop a talent strategy for evolving job roles, and remain aware of rapidly changing enabling technologies to successfully navigate the journey to autonomous supply chains.

SAP sees a future in which supply chains operate efficiently and responsively with little to no human intervention. It won’t happen instantaneously. But it will happen gradually, progressing through the three stages of digital, adaptive and autonomous.

Digital: Digitalization is the starting point. The SAP Supply Chain portfolio automates manual processes, enabling a seamless, digital end-to-end business process and digitalizing paper-based systems. This results in better access to data, greater visibility, and control over the entire supply chain, setting the foundation. Most importantly, SAP provides the tools and systems to get data ready for more advanced stages.

Adaptive: This step is marked by an integration of cutting-edge technologies into business processes, including the use of predictive analytics and simulation for decision-making and Big Data, as well as the introduction of Joule, SAP’s copilot for every supply chain cloud application. These technologies empower supply chain professionals with intelligent insights and recommendations, enhancing decision-making for greater agility and resilience.

Autonomous: Next, we envision a path characterized by technological, procedural, and data enhancements that will propel the supply chain into an autonomous era. This transition will happen gradually but ultimately enable supply chains to operate autonomously with minimal human intervention, resulting in even greater efficiency, adaptability, and responsiveness. It empowers supply chain experts to focus on truly value generating activities and spending precious time on only the most critical disruptions and business opportunities.

“According to recent research, 63% of companies have an AI strategy linked to business objectives to improve operational efficiency, business resilience, and increase employee productivity,” said Mindy Davis, Vice President, Global Marketing, SAP Digital Supply Chain. “Our objective in this digital, adaptive, autonomous supply chain journey is to utilize the breadth of AI technologies to assist customers in achieving their business goals and drive significant value regardless of their current maturity level in business practices and technology.”

There are specific categories of technology that will enable the autonomous supply chain, according to SAP. These are as follows:

Optimization models, rule-based predictive analytics, and heuristics improve, for instance, transportation plans, production scheduling, supply plans and spare part fulfillment. This allows a powerful way to automate decision-making in balancing conflicts of interests, such as customer service levels versus supply chain cost.

SAP-owned machine learning is applied across the SAP Supply Chain portfolio; for example, in gradient boosting algorithms for demand forecasting, intelligent lead time predictions and failure curve analysis. SAP also offers customers a “bring-your-own-model” approach to enable extensibility for specific domains such as visual inspection and anomaly detection.

Generative AI, when embedded in digital supply chain applications and combined with Joule, will allow users to conduct complex business transactions in simple conversational ways. We will augment tasks like conducting what-if scenarios for supply chain planning, assisting in new product ideation, analyzing manufacturing issues to accelerate the onboarding of new equipment, and assessing advanced failure modes of assets with generative AI.

One example of an autonomous supply chain process is in the planning space – the Interactive Planning Assistant within SAP Integrated Business Planning. Demand, supply, and inventory planners often use complex machine learning algorithms. By using generative AI and conversing with Joule in natural language, planners can gain insights into the models’ variables, constraints, and decision processes, leading to much more informed decisions and proactive planning. SAP helps customers boost explainability but also enable what-if scenario simulations for complex planning decisions.

What this means for SAPinsiders

Invest in business process mining and mapping. It’s critical to fully understand all the end-to-end business processes that make up your supply chain operations, especially since so much of your operations likely relies on external partners. It could very well be the case that some processes like demand planning and forecasting are at the digital phase, some like procurement and sourcing are at the adaptive phase, and others like supplier-to-pay are at the autonomous phase. Treat your supply chain as interconnected modular business processes and subprocesses each of which will modernize at its own pace.

Don’t overlook a talent strategy. The autonomous supply chain operates with much lower dependency on human inputs. So job functions like demand planners, buyers, logistics managers, and production schedulers will evolve and adapt as business processes evolve through the three stages. It’s important for companies to plan for these job changes, anticipate where new skills will be required and where some workers will need to be retrained and redeployed.

Remain ever vigilant regarding enabling technologies. The landscape of technologies that are enabling the autonomous supply chain is rapidly and constantly shifting. SAP itself has adopted an AI-first strategy and is aggressively embedding business AI across its solution portfolio. Also, SAP’s partner ecosystem is always breaking new ground with innovations in optimization, analytics, machine learning, data visualization, and AI. Companies would be well-served to stay abreast of new entrants and new capabilities in their assessments of potential technology partners as they attempt to match fit-for-purpose tools with specific business process modernization objectives.