Latest news with #SAPBDC
Economist
20-05-2025
- Business
- Economist
How data and intelligent applications will reshape business
Businesses have faced more instability in 2025 than in the last 25 years. While the pandemic challenged corporate leaders with supply chain slowdowns and rapidly changing consumer demand related to global lockdown, we're operating in an environment where age-old business rules and conventions are shifting beneath our feet. In fact, the Economic Policy Uncertainty Index shows that since January, daily trade policy uncertainty has spiked to unprecedented levels globally. 1 At the same time, artificial intelligence (AI) promises to be the most significant transformation in business software since the maturity of cloud computing over the last decade. But to fully take advantage of AI, business and technology leaders must address the data silos and complexity within their organisation. How can business leaders stay on top of—and even anticipate—the quickly shifting economic environment and ensure the success of their AI initiatives? The answer lies in creating a holistic data strategy that feeds relevant data into their AI landscape. The new data imperative Every organisation on a digital transformation journey needs to turn intelligence into action at scale. Gartner predicts that by 2028, over 50 percent of enterprises will adopt industry cloud platforms, integrating critical business processes to create a robust, flexible, and agile platform. 2 Chief information officers (CIOs) are already in the process of creating the technology infrastructure required to harness every signal from their business—and that of their extended ecosystem of partners and customers. But to drive reliable decision making and AI efforts, CIOs must harmonise that data into a single, unified and trusted layer. That's where SAP Business Data Cloud (BDC) comes in. This new software service integrates all of a company's most important information—both structured and unstructured no matter where it resides—ensuring that business context and data semantics are preserved and exposed as consumable primary data products reflecting the most critical business processes. BDC provides a fully governed and AI-ready foundation enabling businesses to expose the agility needed to navigate today's volatile landscape. Through a partnership with the Databricks platform, SAP BDC also offers seamless machine learning capabilities to data and AI professionals. The advent of intelligent applications A modern data platform like SAP BDC empowers enterprises to create and use intelligent applications. These can utilise a wide spectrum of SAP data products that promise to reshape how organisations operate—embedding real-time data and critical operational context within AI models to enable swift and insightful decisions. Unlike traditional software governed by rigid business rules, these modern applications can learn and adapt to rapidly evolving customer and market demands—detecting changes to optimise processes, anticipate needs, and collaborate with both human and artificial 'thinkers' to create competitive advantage for your organisation. Intelligent applications align with organisations' most important business functions such as human resources, finance and supply chain. For example, at SAP, People Intelligence is designed to provide HR and business leaders with AI-driven recommendations to optimise talent decisions, drive employee engagement and ensure compliance. At the same time, SAP is actively collaborating with leading partners to build the next wave of intelligent applications including Adobe, Thomson Reuters, Accenture and Moody's. By working together, SAP and its partners aim to enable organisations to navigate the complexities of today's business environment and become truly AI-ready. The future belongs to data-driven organisations SAP customers generate 84 percent of total global commerce and 98 of the 100 largest companies run on SAP systems. In other words, the vast majority of the most important business data powering the global economy runs through SAP software. This is a watershed moment, providing seamless access to information within SAP and non-SAP solutions. In a zero-sum game, only a robust data strategy will allow businesses to deftly navigate volatility, remain agile and keep their competitive edge. Learn more about SAP Business Data Cloud at
Forbes
15-04-2025
- Business
- Forbes
Retail's Data-Driven Future: Turning Insights Into Action
According to a new report released from SAP Emarsys, 51% of U.S. brands say their organization suffers from 'dark data,' which is data that is collected but not effectively used. By Balaji Balasubramanian, President and Chief Product Officer for SAP Customer Experience and Consumer Industries In today's retail landscape, customer expectations have never been higher. Shoppers want to move effortlessly between in-store visits, mobile browsing, social commerce, and digital marketplaces, expecting every interaction to be seamless and personalized. Behind the scenes, retailers struggle to deliver these experiences due to fragmented, outdated, and incomplete data that makes real-time decision-making nearly impossible and hampers engagement, operational efficiency, and, ultimately, profitability. When retailers' data exists in silos, the problem is compounded from all angles. With sales, inventory, marketing, and customer engagement data living in separate systems, retailers lack the clear view of customer behavior and business insights they need to respond with critical actions in real time. Lack of context within the data means businesses struggle to extract meaningful insights. Consider the impact: At a moment when retailers must optimize every facet of their business to remain competitive, a unified data strategy isn't optional—it's essential. To break these silos, retailers need a unified data foundation—one that consolidates insights across all customer touchpoints, enabling real-time intelligence and business agility. SAP Business Data Cloud (SAP BDC) is an integrated solution that can bring data together from all sources, owned and external, to help create a single, trusted source of truth. With SAP Business Data Cloud, retailers can have the total picture of data from sales, inventory, marketing, loyalty, service, and near-real-time statuses of third-party logistics. With this holistic view, retailers can: By shifting to a data-first approach, retailers can move beyond managing transactions to driving intelligent, customer-centric experiences for long-term loyalty and growth. Despite the rise of e-commerce, more than 80% of retail interactions still take place in physical stores. Brick-and-mortar locations remain central to the retail journey, yet, as retailers' largest cost center, they also encompass the biggest operational challenges—from inventory carrying costs to labor and store operations. Although today's consumers are fluid in how they shop—researching products across multiple platforms or buying online and picking up in-store, for example—they still expect accurate, real-time visibility into inventory wherever they engage. In this landscape, data is the lifeblood that allows retailers to orchestrate orders, manage workflows, and ensure that customers can trust the information they see. Yet, according to a new report released from SAP Emarsys, 51% of U.S. brands say their organization suffers from 'dark data,' which is data that is collected but not effectively used. To remain competitive, retailers must harness real-time transactional insights to optimize store efficiency, maximize revenue, and provide seamless customer interactions. For Hornbach, one of the largest DIY stores in Germany, the idea of interconnected retail is more than just omnichannel. It needs to be able to add new channels quickly—and to maintain a seamless customer experience over all channels. Hornbach adopted SAP Order Management Services as a foundation for this vision, enabling the flexibility to address new markets quickly, connect new systems, process orders rapidly and efficiently, and adopt new innovations. With the addition of SAP Omnichannel Sales and Transfer Audit, the Hornbach team expects to get more visibility in day-to-day operations, like checking fraud detection and the completeness of transactions. 'The most exciting thing will be the combination of all these new technologies we're seeing: artificial intelligence, event-driven architecture, as well as native cloud solutions,' said Carsten Mueller, head of Enterprise Architecture and Security, Hornbach. 'The combination will give Hornbach great power in the next year.' The retail industry is evolving at an unprecedented pace, with AI redefining how businesses operate and interact with customers. According to the same SAP Emarsys report, 89% of U.S. consumer product marketers believe AI will be essential for engaging new customers. However, the effectiveness of AI hinges on the reliability and accuracy of the data it processes. Retailers that embrace AI-powered data intelligence will lead the next era of omnichannel excellence. The future isn't just about connecting data—it's about activating it in real time to drive seamless customer interactions. To stay ahead, retailers must: As omnichannel complexity grows, brands that fail to unify their data risk falling behind. SAP Business Data Cloud and intelligent order management solutions can provide the foundation for a future-proof transformation. As AI continues to evolve, retailers must shift from reactive decision-making to proactive, predictive commerce, where every transaction is optimized for efficiency and profitability. The future of retail is here. Those who harness AI to unify, analyze, and act on their data will define the next generation of customer experience and retail success. I'm excited to partner with companies navigating this transformation and empower them to seize new opportunities for success. Learn more about SAP's solutions for retail.
Forbes
09-04-2025
- Business
- Forbes
What SAP's Business Data Cloud Means For Enterprises
I recently spent time in New York City with SAP leadership as they unveiled the company's Business Data Cloud. I think the BDC represents a significant shift in enterprise data management for SAP because it integrates both structured and unstructured data from various SAP applications as well as external sources. Besides its advantages for data management, it represents a key part of SAP's AI strategy. BDC leverages a partnership with Databricks to improve data access and governance, which benefits users of SAP S/4HANA Cloud ERP while also enhancing Joule, SAP's AI assistant. BDC offers several advantages, including simplified data integration, potential cost savings on data storage and enhanced AI-driven analytics capabilities. It creates new opportunities for customers, partners and their developers and data scientists. The platform also enables new roles that combine technical expertise with business acumen, such as a BDC architect who designs and implements new solutions for organizations. In essence, SAP BDC is set to transform the data landscape for SAP customers into a dynamic environment ripe for innovation and collaboration. Let's look at how BDC benefits SAP customers, the broader ecosystem and Databricks — and how it supports SAP's transformation into a cloud-first ERP provider. (Note: SAP is an advisory client of my firm, Moor Insights & Strategy.) SAP's BDC consolidates data from SAP HANA Cloud databases, SAP Datasphere (formerly SAP Data Warehouse Cloud), SAP Analytics Cloud and SAP Business Warehouse into a unified platform. SAP Datasphere functionality keeps business rules and metadata intact, which makes data easier to access and interpret, regardless of its original format or storage location. The intent is to reduce data silos and make it easier to discover, combine, manage, govern and analyze data by applying data fabric principles. A data fabric is an architecture that supports consistent data management and access across different systems. I'm seeing many organizations adopt these principles to handle their growing data needs. BDC also integrates with non-SAP data sources including relational databases like Oracle Database and Microsoft SQL Server, cloud storage services such as Amazon S3 and Google Cloud Storage and enterprise applications such as Salesforce, ServiceNow and Workday. This helps enterprises with hybrid IT environments unify their data for a more complete view. Because of this, BDC should be especially valuable for enterprises that use SAP alongside third-party systems such as Salesforce, ServiceNow or Oracle to handle customer data. As a core part of SAP's AI strategy, BDC provides a unified data foundation for AI-driven automation. Beyond that, it strengthens Joule. Enterprises can customize Joule AI agents or develop proprietary AI solutions, leveraging the SAP Knowledge Graph to connect data across systems for more effective AI model training. Meanwhile, Databricks' collaborative tools enable real-time data processing, supporting use cases such as fraud detection and supply chain monitoring. By integrating SAP data with AI applications while preserving business semantics, BDC can deliver critical insights without disrupting workflows, as well as enhancing machine learning, automation and forecasting. By eliminating complex data extraction and replication, BDC provides enterprises with real-time, reliable data in one place. Centralizing data management with BDC — especially because it integrates seamlessly with SAP ERP's core operational functions — could improve business operations and compliance while reducing costs across finance, supply chain, HR, customer experience and sustainability. Let's look at how this might play out in some different areas of enterprises. In finance, BDC can integrate real-time financial data from SAP S/4HANA with external economic indicators, potentially improving forecasting while automating reporting. Automation should reduce manual reconciliation and accelerate financial close cycles. CFOs can also model different market conditions — such as inflation scenarios or supply chain disruptions — to assess potential revenue and profitability impacts. Among other possible benefits for financial agility, enterprises might be able to adjust budgets more quickly in response to fluctuating exchange rates. For supply chains, BDC combines SAP and non-SAP data to enhance visibility, optimize inventory and improve logistics monitoring. Predictive analytics help enterprises anticipate disruptions like raw material shortages or supplier delays. A retailer could use real-time demand sensing to adjust stock levels across distribution centers, reducing excess inventory while ensuring product availability. HR teams stand to benefit from integrated analytics for talent management, workforce planning and compliance reporting. Predictive modeling can help anticipate employee turnover, allowing HR to implement targeted retention strategies. For example, an enterprise might identify departments with higher attrition rates and introduce engagement initiatives to reduce recruitment costs and maintain workforce stability. BDC could enhance customer experience by integrating SAP CRM data with external sources like social media and customer feedback. AI-driven segmentation and real-time behavior analysis might enable enterprises to refine engagement strategies and personalize interactions. A telecom company, for instance, could detect patterns in customer service inquiries and proactively offer tailored solutions to improve satisfaction and reduce churn. BDC also centralizes ESG data, automates compliance reporting and enables real-time carbon footprint monitoring. AI-powered scenario planning helps enterprises meet regulatory and sustainability goals. For instance, a manufacturer could track energy consumption across global facilities, identify inefficiencies and implement targeted reductions to align with corporate sustainability commitments. For more on this topic, see my overview of sustainability data practices, as well as my analysis of the Sustainability Data Exchange that SAP launched last year. The Databricks partnership enhances enterprise data management by integrating SAP's structured and unstructured data with Databricks' AI and analytics capabilities. One of Databricks' standout features is its zero-copy data sharing through Delta Sharing, which eliminates redundant data replication, reducing storage costs and simplifying data governance. Additionally, its Apache Spark-based processing engine enables real-time analytics, predictive modeling and AI-driven decision-making. For example, a manufacturing plant might use Databricks to integrate IoT sensor data with SAP maintenance records in BDC to enable predictive maintenance, helping to prevent equipment failures, reduce downtime and improve operational efficiency. The SAP/Databricks partnership enables SAP to expand its AI and data analytics footprint by simplifying the process of using SAP data for advanced analytics and machine learning. This collaboration accelerates AI and machine learning initiatives, shortens time to value and enables more modern, scalable AI-driven use cases beyond traditional reporting and BI. All in all, this partnership positions SAP to deliver more value from data in today's competitive data-driven environment. Beyond Databricks, BDC also supports interoperability with platforms including Google Cloud, Collibra and Confluent, allowing enterprises to manage and analyze diverse data types across various environments. Moving to SAP BDC will be a key step toward modernization for many SAP customers, but some customers currently using SAP's on-premises ERP may be hesitant to make the shift because of concerns over data migration complexity, potential downtime during the transition and the need to retrain staff on new cloud-based workflows. In New York, I spoke with SAP CEO Christian Klein, who emphasized the importance of supporting legacy customers through this transition. We can expect SAP partners to play a key role in easing the shift, helping enterprises adopt the cloud-based solution more smoothly. SAP also has two well-established in-house programs to aid with these transitions. RISE with SAP, launched in 2021, streamlines migration with tailored tools and services like automated conversion and code analysis. Ongoing support includes business process intelligence and a guided adoption framework for legacy customers to modernize at their own pace while minimizing risk. The GROW with SAP program, introduced in 2023, accelerates SAP S/4HANA Cloud Public Edition adoption for mid-sized companies and scaleups by offering preconfigured best practices, embedded AI and automation. The company touts this approach as reducing implementation timelines from years to months. Together, RISE with SAP, GROW with SAP and BDC expand SAP's cloud offerings and provide flexible modernization options. Note that BDC operates differently for Databricks and non-Databricks customers. Non-Databricks users can still access BDC's native data integration capabilities through SAP Datasphere, but they won't have access to Databricks' advanced AI and machine learning features. For SAP Cloud ERP customers, Databricks functionality is not included by default. It is offered as an optional component within the BDC subscription and is priced based on BDC Capacity Units. Customers must purchase enough units to enable and utilize SAP Databricks capabilities. It's important to remember that companies must also bridge skill gaps between SAP-centric and Databricks teams. While the benefits seem compelling, organizations should evaluate the added cost and complexity. Customers considering SAP's BDC may face several challenges. Since BDC is a managed cloud service, it does not support on-premises strategies, limiting its appeal for enterprises that are committed to on-premises infrastructure. Additionally, enterprises that have built their own data semantics or rely on third-party technologies may see little benefit from SAP's predefined content. While I think the Databricks partnership benefits both companies as well as their customers, there could be concerns about long-term interoperability down the line, especially if Databricks were ever to be acquired by an SAP competitor. The Databricks platform's bundled approach, combining analytics, semantics, data integration and storage, could also lead to vendor lock-in, making it difficult to replace individual components or integrate non-SAP services. Customers may also end up paying for redundant data and analytics components, mainly if they use similar tools outside BDC. In particular, pricing concerns exist for SAP Business Warehouse customers, although the company has partially addressed how it will prevent these customers from paying twice when transitioning to BDC. Beyond that, SAP BW developers may need to adapt to BDC's relational modeling approach, which is different from SAP BW's guided application framework. This transition requires learning new data modeling concepts and techniques. Pre-built data products for S/4HANA and finance in BDC can help mitigate this learning curve by providing ready-to-use datasets. These data products offer a starting point for analysis and can be customized to fit specific business needs, potentially easing developers' workload transition. The data warehouse and analytics market offers several alternatives to the SAP/Databricks solution, with varying integration complexities for potential SAP BDC customers. Oracle is a notable option for those seeking a single-vendor solution for both ERP and data management. For organizations looking to combine SAP with other data warehouse solutions, options include cloud-based platforms such as Snowflake, Google BigQuery, and Amazon Redshift; analytics platforms such as Azure Synapse Analytics; open-source and specialized solutions including Dremio, Teradata and Cloudera Data Warehouse; and enterprise solutions including IBM Db2, Oracle EPM and Microsoft SQL Server. The ease of implementing these alternatives depends on existing SAP infrastructure and specific business requirements. Some solutions may offer simpler integration, while others might require more extensive customization and data migration. The choice should be based on factors including scalability needs, AI integration requirements, analytics capabilities and long-term strategic alignment. Each option has its strengths and limitations, and the best fit will vary depending on the organization's specific context and goals. SAP's introduction of BDC improves its cloud and AI strategy. With the Databricks partnership, SAP improves AI-driven analytics, governance and operational efficiencies for its customers while delivering real-time insights across finance, supply chain, HR and customer experience. Certainly, the challenges mentioned above — for companies with on-premises commitments, pre-existing data architectures or concerns about vendor lock-in — mean that enterprises should carefully evaluate the transition. But for enterprises committed to SAP's ecosystem, I believe BDC presents an important opportunity to modernize data management while leveraging AI-powered automation. The choice will ultimately depend on an enterprise's specific data strategy, infrastructure investments and long-term digital transformation goals.
