The News: SAP announced several new AI-driven capabilities targeted at retailers that are seeking to optimize business processes and improve profitability, while also increasing customer loyalty. SAP Business AI capabilities are being embedded throughout the platform to improve planning, personalization, data analysis and insights generation, and advertising. You can read more about these announcements on SAP’s website.
SAP Announces AI Capabilities to Improve Retail Business Processes
Analyst Take: SAP announced new innovative capabilities that leverage artificial intelligence (AI) to help retailers improve business processes that should support the dual aims of driving profitability and customer loyalty. These new capabilities are embedded within SAP’s core architecture to allow retail customers to select the capabilities that best meet their individual and specific needs, thereby creating a customized experience built on a composable architecture. Some of the new capabilities announced just prior to the National Retail Federation’s 2024 Big Show include the following.
SAP Predictive Demand Planning: Out of stocks and overstocks can negatively impact a retailer’s financial position, as well as the customer experience. If a customer continually finds that products that appeal to them are out of stock, they will quickly shift to other suppliers. Retailers, meanwhile, continually struggle with trying to anticipate demand for products, particularly at a granular level (such as identifying demand for specific sizes or product configurations).
SAP’s predictive demand planning is designed to offer retailers more accurate and longer-range demand forecasts across channels using a self-learning demand model. According to SAP, the solution will support precise forecasting and automatically identify and consider a variety of demand factors and external data within the model. The solution will provide apps for forecast configuration, analysis, adjustment, and simulation and offer intelligent alerting with root causes and recommendations, and because it is a self-learning model, it will consider rapidly occurring changes in the market.
SAP Predictive Replenishment: SAP’s store replenishment capabilities are being incorporated in a phased manner into its existing SAP Predictive Replenishment solution. This capability is designed to automatically replenish inventory in stores and distribution centers for an optimized, multilevel supply chain across flexible planning horizons, with the model considering demand volatility, business targets, rules, and constraints to determine optimal order quantities with the lowest expected costs.
SAP Order Management for Sourcing and Availability: SAP’s Order Management for Sourcing and Availability can be used to determine the optimal business processes and sourcing strategies to deliver customer satisfaction while also minimizing fulfillment costs. This permits users to set up specific goals around delivery time, utilized capacity, cost to ship and shipments per order, and then run simulations to test the strategies before implementation.
SAP Order Management Foundation: The SAP Order Management Foundation allows business users to create omnichannel order flows that can automatically respond to business events, such as a fraud hold, delivery, or in-store pickup activity. The function is available through an intuitive, drag-and-drop workflow automation tool, which also permits retailer customers to customize event triggers based on their unique business processes. After a trigger has been activated, corresponding actions can be automated to take place within the order management system or within the relevant system of customer engagement.
The value of these tools is that the underlying solution can look at not only in-store demand factors, but also the ability to control their business processes and the associated costs based on multiple and concurrent real-world factors, such as supply chain issues, delivery patterns, weather, and other disruptions. The solution is designed to incorporate these factors to ensure delivery of the correct quantities for the right locations, while keeping costs low. Further, the built-in workflow automations can increase efficiency, reduce errors due to manual processes, and can ensure that the key decisions are informed via data, rather than instinct. This is critical to retail businesses that are often faced with unforeseen circumstances that can quickly and drastically impact their operations.
TikTok and LinkedIn Integrations for Digital Ads: In addition to the operational and planning solutions, SAP also announced that the SAP Emarsys Customer Engagement platform now integrates TikTok and LinkedIn for targeted digital ads. Given the wide reach of both platforms, marketers using the solution will be able to create, sync and expand audiences with consumers across these additional social channels and platforms, while continuing to leverage data-driven insights to convert leads and reengage at-risk customers.
As a whole, SAP’s announcements are a clear sign that despite the hype, generative AI is not the only way in which retailers can improve their business processes and operations. The solutions announced by the company largely are based on analytics and machine learning-based AI, which can still provide a wide range of operational benefits to organizations that are incorporating a wide range of concurrent and interdependent data streams each day.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other Insights from The Futurum Group:
SAP’s Generative AI Copilot, Joule, Coming to SAP Applications
SAP Q3 Revenue Up 4% to €7.74 Billion as Cloud Growth Continues
SAP’s New Generative AI Capabilities to Enhance Customer Experiences
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
