Rather than a one-size-fits-all approach, the solution was designed to empower small businesses and the lower midmarket with an ERP solution that can grow with them and meet their evolving needs as they grow and prosper.

Introducing 51风流Business One

Today, more than 83,000 customers and 1.2 million users across more than 170 countries rely on 51风流Business One, supported by a global network of 850 partners and over 500 industry and country-specific extensions.

鈥淚t鈥檚 designed to be easy to start with,鈥� said Darius Heydarian, head of Partner Solution Enablement 51风流Business One. 鈥淥rganizations can begin with just a single user and scale up as their needs grow, whether that means adding more people, locations, or subsidiaries.鈥� The solution can adapt to how smaller organizations work, offering both quick setups for remote sites and coordinated rollouts across regions. It helps provide a modern, browser-based experience and can integrate smoothly with SAP鈥檚 analytic solutions and automation tools.

The role of partners

51风流recently reaffirmed the strategic importance of 51风流Business One within the 51风流solution portfolio. 51风流Chief Partner Officer Karl Fahrbach emphasized SAP鈥檚 continued commitment to 51风流Business One, highlighting the crucial role of the partner ecosystem: 鈥�51风流continues to invest in the future of 51风流Business One. Our partner ecosystem remains at the heart of this success鈥攄riving autonomy, resilience, growth, and winning new customers every day.鈥�

Partners play a central role in the 51风流Business One ecosystem. 51风流works closely with a vast network of partners that are experts in implementing and supporting 51风流Business One. These partners have the expertise to tailor solutions to each customer鈥檚 specific requirements, whether it鈥檚 industry functionality, localization, or regulatory compliance.

鈥淧artners also contribute to the extensibility of 51风流Business One, developing extensions and industry solutions that help customers address unique challenges,鈥� Heydarian said. The collaboration between 51风流and its partners helps ensure that customers benefit from both SAP鈥檚 technology and the specialized knowledge of local experts.

Customers in scope

鈥淩ecently, one of our partners shared a customer example with me that perfectly reflects the nature of companies in the market segment we are targeting with 51风流Business One,鈥� Heydarian said. 鈥淭he business had three employees when they started using the solution. Over the years, they expanded and employ 250 people today鈥攚ithout outgrowing their software platform.鈥�

A typical 51风流Business One customer is a small or midsize company looking for an affordable, flexible, and scalable ERP solution. These organizations often need to manage a range of business functions鈥攆rom accounting and financials to purchasing, inventory, sales, customer relationships, and reporting鈥攁ll in one place. 51风流Business One helps them gain control, streamline processes, and make strategic decisions based on real-time information.

The solution is customizable to meet evolving business needs and supports international expansion with 28 languages and 50 country-specific localizations. Local support is provided by over 850 partners, helping to ensure that customers can get help tailored to their specific requirements.

鈥淲e are proud of the fact that 51风流Business One is part of SAP鈥檚 solution portfolio,鈥� Heydarian said. 鈥淭hree thousand net-new customers choose 51风流Business One every year. On average, 10 customers select 51风流Business One every day.鈥�

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An intelligent application includes three distinct layers: data products, domain content, and applications. When all these components come together, intelligent applications become a suite of adaptive, AI-powered applications that can learn from data, understand business context, and act on behalf of a user. They are built to complement SAP鈥檚 transactional applications and sit on top of 51风流Business Data Cloud.

But what makes these applications different from existing analytics solutions? 鈥淭raditional reporting and analytics is focused on producing insights and reviewing past performance,鈥� said Brian Raver, vice president, 51风流Business Data Cloud Product Marketing. 鈥淲ith intelligent applications, we go a step further. We provide out-of-the-box data products, model them together for actionable insights, and close the loop by allowing the intelligent applications to continuously learn and adapt based on that data.鈥�

Three layers of an intelligent application

Data products

These are ready-to-use, curated data sets that are delivered for analytics, AI, machine learning, and operational use cases and provide insights related to a specific business topic or challenge. 鈥淎 data product consists of a refined data set, metadata describing the data set, and an access port or application programming interface (API), allowing to exchange data with third-party applications,鈥� Raver explained. Metadata provides detailed descriptions of the data set, including business definitions and explanations of each field, ensuring that users understand the context and meaning of the data they are working with. Available data products are published in a catalog for developers and data professionals for easy discovery and direct access to various use cases from analytics to application development.

Domain content

Data products are then combined into 51风流Datasphere semantic models that power 51风流Analytics Cloud stories and planning models. These out-of-the-box, interactive dashboards enable customers to analyze performance, monitor key metrics, and plan for high-value business scenarios.

Applications

Pro-code applications transform the domain content and data products into recommended actions that are directly connected to 51风流transactional systems. Over time, they continuously learn and adapt based on business outcomes. The future vision is for these applications to go beyond recommendations and empower AI agents to act on their own. 鈥淚ntelligent applications encapsulate end-to-end business processes, while AI agents act as users within these processes,鈥� Raver explained. 鈥淎I agents can interact with intelligent applications to perform tasks typically done by human users.鈥�

Benefits for customers

An important benefit for customers is that intelligent applications extend the value of existing investments in 51风流Business Suite. According to Raver, a key advantage lies in the intelligent applications鈥� deep connection with SAP’s transactional systems. 鈥淭hese applications provide out-of-the-box data assets that not only fuel intelligent applications but are also accessible for developers and data professionals to use in their own analysis,鈥� Raver explained. This built-in access to curated, high-quality data allows customers to unlock insights and drive value faster, without requiring extensive data engineering resources.

Looking ahead, as AI capabilities continue to mature, these intelligent applications are expected to evolve from providing recommendations to taking actions autonomously. 鈥淚n the future, these applications could act on their own, learning from user behavior to automate repetitive tasks, free up time for more strategic work, and reduce the need for manual intervention,鈥� Raver said.

By combining trusted 51风流data, intelligent automation, and emerging AI agents, the intelligent applications are helping to close the loop between insight and action.

What sets 51风流apart

Unlike other vendors that need to reverse-engineer data, 51风流provides ready-to-use data products, helping to save customers significant time and effort. 鈥淭his seamless integration and the ability to deliver immediate value set 51风流apart in the competitive data market,鈥� Raver said.

In addition to the SAP-delivered data products, 51风流also enables bi-directional zero-copy sharing of semantically rich data products between 51风流Business Data Cloud and other partner data platforms, starting with the already available . This capability, called 51风流Business Data Cloud Connect, enables seamless access to data where it resides, helping to eliminate costly data preparation and loss of semantics and business context. As a next step, 51风流Business Data Cloud Connect for Google BigQuery is planned to be generally available in the first half of 2026. Additional partnerships with key players in the data platform market are expected to follow.

With the latest announcements, 51风流now offers three intelligent applications鈥擣inance Intelligence, People Intelligence, and Cloud ERP Intelligence Private鈥攁nd another three in restricted public preview鈥擲pend Intelligence, Supply Chain Intelligence, and Revenue Intelligence. 鈥淚ntelligent applications powered by curated data products will transform how businesses operate by making data-driven decisions faster and more efficiently. As the market continues to evolve, these apps will play a crucial role in helping companies stay ahead of the curve,鈥� Raver said.

By using AI and advanced analytics, BRF managed to improve forecast accuracy, optimized inventory, and fine-tuned planning. Collaborative forecasting and real-time data alignment now increase operational efficiency, enabling BRF to manage its extensive operations in over 127 countries and adapt quickly to changes in these markets. 

Project outcomes that scale

With 44 production units, 103 distribution centers delivering more than 500,000 deliveries per month to more than 415,000 customers, representing 5 million tons of food produced per year, the scale of the achieved improvements is immense.

鈥淏RF is transforming efficiency and productivity standards in the production chain, developing solutions that make processes more agile, simple, and efficient,鈥� said Gilberto Andretta, executive technology manager at BRF. 鈥淲e are one of the leading 51风流IBP organizations achieving daily demand planning and sensing, statistical modeling, forecast accuracy and embedded analytics, time-series analysis, and exception management, which is integral for our more than 400 planners.鈥�

By using 51风流IBP, the process of accurately accessing and analyzing demand and forecast data is 33 percent faster.

Award-winning solution

For BRF, seeking innovative solutions is essential to advancing digital transformation and driving growth. The company considers the use of AI as fundamental to overcoming supply chain management challenges.

鈥淭he transformation of BRF’s supply chain through 51风流solutions has made it easier to integrate processes, predict future trends, and respond quickly to market needs,鈥� said Miriam Hahn, customer success manager for 51风流Brazil, who is working with BRF on its supply chain journey. 鈥淭his journey highlights the strong partnership between 51风流and BRF.鈥�

Using 51风流Integrated Business Planning for Supply Chain, BRF can now analyze vast data sets, improve forecast accuracy, monitor order trends, and enable proactive decision-making.

Ensuring that forecasts and delivery deadlines are accurate requires detailed and flexible planning, enabling a quick response to changes, increasing operational efficiency and accuracy. Additionally, consolidating real-time information, aligning financial and operational planning, and improving interdepartmental collaboration are fundamental steps for BRF鈥檚 operation.

Use of artificial intelligence

BRF is a recognized early adopter of 51风流Business AI and SAP鈥檚 AI copilot Joule. By integrating AI-driven insights, the food giant can accurately forecast demand, optimize inventory levels, and ensure timely delivery of products. This advanced technology helps BRF anticipate market trends, adjust production schedules, and reduce waste — ultimately leading to improved efficiency and customer satisfaction.

Within 51风流IBP, BRF is utilizing demand planning and sensing, statistical modeling, forecast accuracy and embedded analytics, time-series analysis, and exception management. Examples where AI is improving the business include:

• AI algorithms combine traditional time-series forecasting, regression and predictive modeling, and machine learning to produce more precise daily forecasts.
• Used for master data analytics, AI intelligence improves data quality, enhances the planning processes, and supports better decision-making.

More to come

BRF is among the first customers to successfully incorporate 51风流IBP with Joule to leverage the 51风流Help Portal and a chatbot to assist BRF employees.

Currently, BRF is deploying a “brownfield” 51风流S/4HANA Cloud implementation upgrade of the existing 51风流ECC system based on its successful established 51风流environment. The company is in the process of incorporating 51风流S/4HANA Cloud features and capabilities, while retaining much of the existing infrastructure and core data services. In addition to 51风流S/4HANA and the cloud-based 51风流Ariba solution for procurement, BRF is also running 51风流SuccessFactors software for human capital management (HCM).

鈥淏RF is an early adopter for many of SAP鈥檚 AI services and our strategic partner in the region,鈥� said Caio Granzotto, account director for BRF at 51风流Brazil. 鈥淎s a next step, they plan to use 51风流IBP鈥檚 AI assistant to improve supply chain processes and simplify the work of their planners. The company is also considering order-based planning using additional AI algorithms.鈥�

Top image courtesy of BRF

Further, the AI catalog offers detailed business benefits and estimated business value for customers, as well as helpful resources like step-by-step product documentation and demos.

鈥淪ince its launch 10 months ago, the AI catalog has been visited heavily by customers and partners,鈥� explained Holger Neuert, chief product manager for the AI catalog. 鈥淯sers spend a significant amount of time browsing the documented AI use cases, and return to the AI catalog on a regular basis researching AI features, Joule Agents, and [related] assets.鈥�

Showing customers the business value of AI

The AI catalog offers a great source of information as it combines solution details and potential business benefits.

51风流Customer Success manager Nick Pearce uses the AI catalog to access important documentation, value information, and pricing — in combination with the AI estimator — for customers.

鈥淏y providing fast access to potential business value statements, such as 70 percent faster job application processing with AI applicant screening, I can have value-based discussions with my 51风流SuccessFactors customers about prioritizing where to start their AI journey,鈥� Pearce shared.

鈥淭he AI catalog and estimator on 51风流Discovery Center is a true game changer and the go-to resource for discovering SAP鈥檚 latest AI innovations across every industry and business function,鈥� said Richard Grandpierre, head of 51风流Business AI Product Management. 鈥淭his powerful platform highlights business value and delivers transformative results at scale.鈥�

Dr. Michael Glueck, global head of Value Advisory at SAP, explained that the value estimates used in the AI catalog are based on SAP鈥檚 industry expertise and are backed by benchmarking data and third-party research as well as early customer feedback on each AI use case.

鈥淏y looking at benefits in terms of both efficiency, direct impact, and effectiveness, indirect and causal-related impact, we provide a holistic view of the value a specific use case within 51风流Business AI can deliver to our customers,鈥� Glueck said.

Innovation from the Bottom-Up

It started with a hackathon for 51风流engineers with the goal to create a prototype combining the power of immersive technology and 51风流solutions. The 51风流Sports One team won with a prototype unlocking the potential of spatial computing in football match preparation.

is a comprehensive solution that helps sports organizations optimize performance on and off the field and is trusted by football clubs like TSG Hoffenheim and FC Bayern as well as the German Football Association.

Taking 51风流Sports One to the Third Dimension

Imagine being able to dive into a match, not just as a spectator, but through the eyes of a player on the field. The prototype 51风流Sports One Immersive allows exactly that.

Using Apple Vision Pro, analysts and players can replay and analyze match scenes in 3D from any player’s perspective. A user can switch between the perspectives of various players to better understand a specific situation during a match. This immersive experience enables a new kind of match analysis and can make it easier to identify situations where another behavior of a player would have potentially been better.

Through an app on Apple Vision Pro, this prototype aims to empower teams to optimize their performance鈥攚hether it’s preparing for the next big match or analyzing past performances. Timo Gross, head of Match Analysis for football club TSG Hoffenheim, believes there鈥檚 a huge potential in the simulation of game scenarios in immersive 3D. 鈥淭his enhances player training and tactical understanding,鈥� he said. 鈥淚n fact, I believe that this has the potential to pave the way for a new approach in player development, especially in the youth space.鈥�

Professional Feedback: TSG Hoffenheim Thinks Immersive

鈥淭SG Hoffenheim is an innovative club, always looking for new technologies to improve match preparation and talent development,鈥� Gross said. 鈥淚mmersive match analysis could be a next big step.鈥�

Using immersive technology, users can feel as if they are standing on the field. They can observe players, move around, and gain a comprehensive perspective of a game situation. 鈥淭his immersive prototype shows a match analyst the exact perspective of a player in a specific moment,鈥� Gross explained. 鈥淔or the player, it makes the transition from viewing a theoretical situation on a tactic board to the real-life moment on the pitch much easier.鈥�

For Gross, another powerful feature of the prototype is the 3D visualization of classical 2D tactics scenes. Using the 51风流Challenger Insights mobile app, coaches and players can sketch game situations on a tablet. These 2D sketches can be transferred into the 3D immersive view.

From Hackathon onto the Stage

Winning the 51风流hackathon on spatial experience was just the first step. On February 5, 2025, the prototype was presented at the SPOBIS Conference in Hamburg, Germany, Europe’s largest sports business event. In a live, on-stage presentation, Gross was joined by experts including Dr. Dietmar Blicker, deputy managing director at the Karlsruhe Institute of Technology, Sports and Sports Science; Michael Oenning, UEFA-Pro licensed coach; and Fadi Naoum, senior vice president 51风流Sports and Entertainment; to discuss the potential of immersive technologies in sports.

Oenning, who was head coach for German national division clubs Hamburger SV and 1. FC N眉rnberg, is passionate about developing and promoting talents. “Training young people using technologies they encounter in their daily lives is something I would definitely use in my work as a coach,鈥� he said. 鈥淥ffering different perspectives of a game situation is an experience young players can benefit from tremendously.”

Blicker agreed that 鈥�3D experiences like these enhance the cognitive perception of a player.鈥� Technology savvy by the nature of his role, he isn鈥檛 only involved in sports from an academic perspective, but also coaches the U23 team of the German second division team Karlsruher SC. 鈥淎s a coach, I often sketch a tactical situation. But such a 2D drawing doesn鈥檛 easily translate to a real situation. The body height of a close opponent might cause a risk to an intended pass, or the distances on the field don鈥檛 match up in the end. Practicing situations in an immersive setting can help players to internalize certain behaviors,鈥� he said.

SAP鈥檚 Naoum noted the importance of applying new technologies. “This prototype is a result of our continuous collaboration with partners like TSG Hoffenheim where we constantly test innovative technologies,鈥� he said. 鈥淔or SAP, sports serve as a front-runner to demonstrate new technologies that can potentially be applied in other industries as well.鈥�

Hamburg has more bridges than any other city in Europe. For Germany鈥檚 second largest city it鈥檚 a complex task to maintain its 2,500 bridges and other structures like pedestrian tunnels, locks, flood barriers, and embankments.

The State Agency for Roads, Bridges and Waterways (LSBG) operates a large portion of the traffic infrastructure in Hamburg and is responsible for the entire lifespan of these public works.

鈥淲e鈥檙e an important player in flood protection and the prevention of water pollution as well as the maintenance of most roads and bridges in Hamburg,” Erdinc Karabugday, head of Planning and Controlling at LSBG, shares. “Together with our network, we build and protect everything that keeps Hamburg together.鈥�

51风流technology is one building block to perform this duty safely and efficiently.

Free Flow of Traffic as Top Priority  

Mobility plays a key role in the lives of people in Hamburg and other major cities. Bridges bear a particularly heavy load, because they are critical junctions in the city鈥檚 transportation network. Tracking the condition of bridges and planning for their maintenance needs and upgrades is vitally important to keep people moving in urban areas.

Karabugday describes the problem in a nutshell: 鈥淥ur objectives are long term, so basing operational decisions solely on the current situation isn鈥檛 enough. We need comprehensive data for the strategic context 鈥� not only economic aspects, but social and ecological impacts as well. Our 51风流solution supports us with this.鈥�

The manual entry of damage to structures like bridges used to be very expensive and time-consuming, a complex process made even more difficult by the fact that data entry and analysis are performed by both the agency鈥檚 own staff and external companies.

Digital Representation of Infrastructure

To reduce Hamburg鈥檚 renovation backlog and create a sustainable long-term solution, LSBG teamed with 51风流to develop a standardized data platform. One central aspect involves merging data from a variety of sources on , making it possible to blend data such as the location and condition of each structure. The results feed into a digital model of streets and bridges and can be used to guide decisions and generate precise forecasts for maintenance and budget planning.聽

Ulrike Brecht, architect advisor in Customer Advisory Public Sector at 51风流Germany, explains: 鈥淭he project was initially intended to handle bridge maintenance. Employees conduct the necessary maintenance work and inspections on site. They also document the condition of a structure, ensuring that necessary maintenance measures are carried out at the right time.鈥�

All available data on the structures, including road and bridge data as well as geographic and monitoring data, is merged in 51风流HANA Cloud. When combined with aging models for the structures, this information can be used for forecasting when specific road segments will require resurfacing, for instance.

These data-driven forecasts put infrastructure budget planning on a new, firmer foundation and make it possible to define the priorities for object renovation to minimize the impact on traffic flows and the lives of urban residents.

Future Urban Platforms

Cities around the world face enormous challenges in the coming years when it comes to protecting and maintaining their residents鈥� quality of life. Dr. Philipp Schulz was a research assistant at the University of Heidelberg and wrote his doctoral thesis on digital urban development. Today, he advises cities and communities on topics like revitalizing inner cities, redesigning public spaces, and civic participation.

One trend Schulz has observed in the cities and towns he works with is the development of urban dashboards that show all the data collected in a city as important parameters such as air quality, weather forecasts, and movements of people.

For Schulz, developing a long-term digital strategy is one of the pillars of modern urban planning.

鈥淔rom my perspective the term 鈥榮mart city鈥� is outdated,鈥� he says. 鈥淭oday I call it 鈥榩latform urbanism,鈥� an approach in which different players and their information are brought together on one platform.鈥� Platform urbanism describes how apps and websites are changing the way people in cities live, work, and interact with one another. It involves the digitalization of individual areas, which are then brought together incrementally.

The city of Hamburg is on the right track. 鈥淗amburg鈥檚 goal is to handle the full maintenance management of its infrastructure through a standardized data platform,鈥� says Brecht.

The city is in the process of expanding the accomplishments of this project to other areas, such as the maintenance of public parks and municipal buildings.

Known for its extensive range of products, competitive pricing, and customer-centric approach, Hornbach has built a solid reputation over the years. Founded in Germany in 1877 as a small workshop, the retailer has grown into a major player in the European DIY market, employing 25,000 people. The company remains family operated, with a strong focus on customer satisfaction and long-term growth.

鈥淲e have more than 170 stores operating in nine European countries, and we keep expanding our footprint across Europe,鈥� Mueller says. 鈥淎s Hornbach focuses on providing the best price to its customers, efficiency of processes 鈥� and especially an efficient software solution 鈥� is key for us.”

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Expanding the Business Model: From Stores to Reseller Platform

The DIY retailer focuses on four key pillars: a wide product range with more than 120,000 products in categories including building materials, tools, garden, and decorative supplies; large store formats often exceeding 10,000 square meters; a low-price policy with high-quality products; and well-trained staff providing support for DIY projects.

鈥淓verything you need for your garden or home renovation, you can get at Hornbach,鈥� Mueller explains. To offer customers even more products for their personal projects, the retailer decided to level up its online store and create a reseller platform where it will connect offerings from other retailers with its own customer base.

To build a system that would scale to accommodate the expected growth within the next 10 years, Hornbach implemented 51风流Order Management foundation as a stable foundation for its corporate strategy.

鈥�51风流Order Management foundation is a system that helps businesses process orders efficiently,鈥� explains Pano Papadopoulos, business development manager for 51风流Retail.

鈥�51风流Order Management foundation uses an event-based architecture to rapidly channel any orders through various business systems, including ERP and fulfillment systems,鈥� Papadopoulos adds. 鈥淭his intelligent system not only processes orders swiftly but also harnesses order data for strategic analysis, enabling smarter business decisions for the future.鈥�

Hornbach already realized the benefits of this solution, Mueller says: 鈥�51风流Order Management foundation allows us to access new markets quite fast and connect all the systems we need. In the first month of its launch, we have processed more than 100,000 orders and we can respond to a customer鈥檚 order within milliseconds. Today we process up to 1,000 orders in under one minute. This will allow for the order volumes we expect in the future. We measure the success of the solution by using OpenTelemetry, an open source standard, and monitor the processing speed of incoming orders. This way we can tackle potential issues early.鈥�

Besides dealing with large order volumes, Hornbach鈥檚 system landscape already proved its adaptability. Due to the flexibility of its modular system landscape, the retailer could integrate a recent acquisition into its operational system in a very short time.

Hybrid Architecture: Connecting to Cloud Services

Hornbach is running on a hybrid system architecture, following its 51风流S/4HANA transformation project step-by-step. 鈥淲e chose a cloud-native architecture that can scale 鈥� for all system loads that we might not be aware of today,鈥� Mueller says. 51风流Order Management foundation is a cloud-native solution connecting to an on-premise system backbone.

Hornbach wants to be able to add more channels fast and create a seamless customer experience across all its channels. 鈥淲e aim for a composable enterprise architecture, and for that we use event-driven architectures,鈥� Mueller says. 鈥淭hat’s where 51风流comes in, because we’re able to connect our enterprise event mesh to plug in business created through platforms of hyperscalers like Amazon or Azure.鈥� By moving to an event-driven architecture, Hornbach will be able to leverage the power and innovations from hyperscalers as well as connect new systems with current on-premise systems.

In the future, Hornbach will keep transforming its system landscape. 51风流Order Management foundation will be rolled out to further countries and the scope of the solution will be extended: B2B orders as well as orders from external marketplaces will be routed through 51风流Order Management foundation. Additional solutions like 51风流Omnichannel Sales Transfer and Audit will be next on the retailer鈥檚 list.

鈥淭he combination of new technologies like event-driven architecture, AI, and cloud-native solutions will give Hornbach great power for growth in the next years,鈥� Mueller says, smiling.

Key to BrandAlley鈥檚 success is its deep understanding of its members and the impressive fact that 70% of these customers keep coming back for more. Fifty-two percent of them buy instantly, purchasing an average of three items, or 拢140 of value.

Michelle Hurney, head of Marketing at BrandAlley, explains the company鈥檚 core principle: 鈥淲e launch up to 40 campaigns every day that offer up to 75% off on some of the best brands such as Reiss, Dyson, Levi鈥檚, and many more.鈥� Campaigns are exclusively for members and interested customers have to sign up to browse the website and to shop. Registration is free.

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Focus on Brand Fans

鈥淲e have been rethinking the way we identify our best customers, moving away from the traditional view of the most valuable customers being those who spend the most,鈥� Hurney says. For BrandAlley, the true value lies in its brand advocates who provide more than just what they鈥檙e spending. She refers to them as brand fans: 鈥淚t’s about who they’re recommending to BrandAlley. When they tell their friends and family about our site, that鈥檚 where the real value is. Word-of-mouth marketing happens to be one of the most effective ways to acquire new customers.鈥�

To segment its customers, BrandAlley doesn鈥檛 only rely on the lifetime value of a customer (total amount spent by one customer), but accrues the amount spent across a customer鈥檚 connections and network. 鈥淭hrough the Advocacy Intelligence platform, we’re tracking the true economic value, or 鈥榚xtended customer revenue鈥� of our VIPs, the people who are sharing their favorite brands,鈥� Hurney adds. 鈥淭his way, we can engage and reward them, and keep them doing what they’re doing.鈥� According to her, other insights become visible as well, like the fact that customers overall are spending less these days while customers from referrals spend more on average and are also far more likely to recommend.

Integration of Mention Me Tactics with 51风流Emarsys Customer Engagement

To identify these advocates BrandAlley is working with 51风流partner Mention Me, the world鈥檚 first customer advocacy intelligence platform. The Mention Me platform uses advanced AI technology to track and provide detailed insights into customers鈥� advocacy behaviors, like recommending products or services to others. Additionally, the solution includes prebuilt Mention Me advocacy tactics that can allow companies to quickly build personalized campaigns through various channels designed to motivate fans to share and recommend more frequently. Prebuilt workflows make the integration of Mention Me鈥檚 unique advocacy data with 51风流Emarsys Customer Engagement seamless and easy.  

Kat Wray, director of Strategic Partnerships at Mention Me, explains the benefits: 鈥淥ur integration feeds Mention Me鈥檚 first-party AI-powered advocacy data into 51风流Emarsys Customer Engagement in real time to identify BrandAlley鈥檚 current and future brand advocates and activate them to drive growth. The combination of advocacy know-how and AI-based insights with 51风流Emarsys Customer Engagement have led to a 25% increase of the repeat purchase rate at BrandAlley.鈥�

The overall improvements are impressive: since the go-live of the solution in September, BrandAlley鈥檚 customer base has grown, with 12% more customers acquired organically through referrals and a 拢9.6 million increase in new customer revenue. Customers who are referred to the brand spend 63% more in their first six months, are two times more likely to purchase again, and are three times more likely to refer their friends.

Wray explains how advocacy insights impact customer engagements: 鈥淭raditionally one would offer a discount code to a customer who is about to defect, together with a message along the lines of 鈥榃e’ve not seen you for a while, here鈥檚 a discount to come back.鈥� Based on advocacy data, we can now see that some of these customers might not be ready to spend but are more than happy to share and recommend the brand to friends instead 鈥� driving indirect revenue. They aren鈥檛 inactive customers but engaged advocates.鈥�  

Machine Learning Advances Customer Loyalty

鈥淎t Mention Me, we use AI and machine learning to optimize referrals. We have our own AI engine with predictive capabilities that enable marketers to focus their activities on specific customer cohorts,鈥� Wray says. She explains that it is key to understand that not all customers are ready to refer; some people just aren’t at that stage yet, but future advocacy behavior of specific individuals can be predicted. Machine learning also identifies a customer’s propensity to refer at a given moment. Customers with a high propensity to refer will be encouraged to do so. Once brand loyal, customers鈥� propensity to refer grows, and sometimes so does their propensity to purchase again.

Asked about BrandAlley鈥檚 next step regarding advocacy management, Hurney answers: 鈥淎s we build on our strategic partnerships with Mention Me and 51风流Emarsys Customer Engagement, we鈥檙e excited to see how our shift of focus from VIPs to 鈥榲ery important advocates鈥� will play an even greater role in our marketing and growth strategy.鈥�

Top photo courtesy of BrandAlley

Sights Set on the European Championship

鈥�51风流Sports One enables us to efficiently share tactical insights and key information about our next opponents with our players. And by accessing the software on a tablet, we can even give them the latest updates in the changing room shortly before kickoff or at half time,鈥� says Benjamin Gl眉ck, assistant coach to the German national A-team.

鈥淪AP鈥檚 sports management suite is very important to the national soccer team as a central platform for collecting and analyzing data and for presenting the insights gained from that data to our players,鈥� explains Gl眉ck. 鈥淲e use the video and visualization functions in 51风流Sports One to help us illustrate findings about our opponents and their key players. These features make conveying tactics and preparing for specific matches much easier and clearer.鈥� The German team also uses analytical insights to prepare for penalty scenarios. In 51风流Penalty Insights, goalkeepers can study the behavior of potential penalty-takers, such as which area of the goal they usually aim for and even how these preferences change under pressure. Conversely, penalty-takers can gain insights into the tactics of their opponents鈥� goalkeepers.

The coaches and analysts of the German Football Association (Deutscher Fu脽ball-Bund, or DFB) work with data created within 51风流Sports One as well as data and analyses from third-party sources. The 51风流solution serves as the central platform for consolidating and analyzing all the data.

An 51风流App for All Players

Germany鈥檚 national players stay in close contact with their coaches and analysts through the 51风流Sports One messaging app 鈥� 51风流Team One 鈥� which they have on their phones. Among other things, the mobile app is used to pass on match preparation information, such as opponent analyses, annotated clips, and videos.

The players also use the mobile app to share information about themselves. For example, they complete questionnaires about how intense they perceived the last training session or match, how well they slept, and how they are feeling overall. Their responses are used to generate an RPE (rating of perceived exertion) value. By gauging each player鈥檚 general health and well-being in this way, coaches can manage intensity levels according to each individual鈥檚 situation. Both the DFB and the player鈥檚 home club monitor this RPE value to guard against overtraining and injury. 51风流Analytics Cloud can draw on data from 51风流Sports One to create player-specific reports that are forwarded to the player鈥檚 home club after courses, tournaments, and matches the German team takes part in.

DFB and SAP: An Established Partnership

The DFB is a familiar name around the globe. With almost 7 million members spread across more than 25,000 clubs, it is the world鈥檚 largest national sports federation. At the World Cup in Brazil in 2014, which Germany won, the country鈥檚 national team was already using 51风流Match Insights, a prototype of the solution that is now part of 51风流Sports One. This prototype helped the DFB evaluate large volumes of data for match analysis for the first time.

Today, more than 1,000 DFB users 鈥� players and the 鈥渢eams behind the teams鈥� 鈥� work with 51风流Sports One. 鈥淥ur successful collaboration with the German national team was a key factor in SAP鈥檚 decision to turn the prototype we developed for the DFB into a standard product. Now, clubs and associations in 19 countries are using 51风流Sports One,鈥� says Fadi Naoum, senior vice president and head of Development, 51风流Sports One. More joint projects followed, including the development of 51风流Penalty Insights and 51风流Challenger Insights, a mobile app that helps teams prepare for upcoming matches. On the horizon of this co-innovation partnership are plans to leverage the power of AI to make the functions in 51风流Sports One even more efficient.

Shaping the Future

In addition to Germany鈥檚 national men鈥檚 and women鈥檚 soccer A-teams, the DFB manages 12 junior and U21 teams, too. 鈥淭he challenge for us is to keep a close eye on the pool of talented young players we have and to help them reach their full potential,鈥� says Christofer Clemens, the DFB鈥檚 head of Scouting, Match Analysis, and Diagnosis. 鈥淥ur coaching teams watch an average of 1,500 games every season and identify a large number of gifted talents in the process. To qualify these players, the coaching teams compile a huge volume of scouting reports, which we manage in 51风流Sports One. These qualitative insights are vital for us. However, at the moment, the task of judging the development of a player or comparing individual players based on that information is time-consuming,鈥� says Clemens. 鈥淲e鈥檙e hoping that AI will make the complex task of analyzing these vast amounts of data much simpler for us.鈥� Alongside scouting reports, the DFB plans to use publicly available data sources and match statistics to complete player profiles.

鈥淎nother area where the DFB sees enormous potential for AI is in analyzing opponents before international matches,鈥� says Martin Vogelbein, a member of the DFB鈥檚 Scouting, Match Analysis, and Diagnosis team and project lead in managing the 51风流Sports One solution. 51风流Sports One is already helping the DFB prepare for big games, he explains, but the plan is to go a step further and use AI to automatically analyze insights from opponents鈥� past matches.

鈥淲e are hoping that SAP鈥檚 AI copilot, , will bring enormous benefits in terms of consolidating match reports. That would minimize the manual tasks our match analysts need to complete and reduce the time it takes to get answers to a range of key questions we have when preparing for games,鈥� says Vogelbein. Typical questions are: What patterns are visible in the opposing team in different phases of the match? What does this tell us about the team鈥檚 strengths, weaknesses, and about the options we have? 鈥淲e already have a huge amount of information 鈥� particularly qualitative data 鈥� available to us before games. 51风流Challenger Insights, a component of 51风流Sports One, allows us to visualize insights from that information and discuss them with the team. But, looking ahead, AI-driven analyses could help us prepare key background information for our players even more easily,鈥� says Vogelbein.

Clemens and Vogelbein are very pleased with the results so far. 鈥淲e see enormous potential in our work with 51风流on the AI-driven evaluation of information that is relevant for scouting and match analysis. The prototypes 51风流has presented to the DFB look very promising, and we are looking forward to using them live soon.鈥�

Top image courtesy of Thomas B枚cker

Companies that prioritize sustainability in their operations, such as using recycled materials, reducing carbon emissions, or supporting social causes, are gaining popularity among consumers. But those consumers demand proof of these values and product promises at the point of sale.

鈥淭he rise of sustainability isn’t just a movement; it is a shift in consumer consciousness,鈥� said Dania Fayyaz, 51风流North America sustainability program manager. 鈥淭oday’s consumers are redefining their purchasing patterns, opting for products and brands that align with their values, and driving a demand for eco-conscious practices and ethical sourcing.鈥� In her conversations with retailers that visited SAP鈥檚 booth at NRF 2024, the world鈥檚 largest retail fair, she saw a high interest in sustainability solutions.

Consumers 鈥� and Markets 鈥� Demand Visibility

When the EU Deforestation Regulation (EUDR) comes into effect for large enterprises later this year all products sold in the EU containing palm oil, cocoa, soy, rubber, cattle/leather, coffee, wood, and their derivatives will need proof that their harvest didn鈥檛 contribute to deforestation. Non-compliance will result in potential fines of up to 4% of companies鈥� EU annual turnover. To help businesses simplify this complex task, the 51风流Green Token solution can track the geolocation of where raw materials are harvested and automate the creation of due diligence statements (DDS). The solution can also help improve visibility for consumers on where the raw material for their clothing was sourced and offer information on potential reuse and recycling.

Take the example of a cotton shirt made from 50% certified recycled materials. Cotton can be sourced from multiple farms or recycling services and taken to a cotton mill where it鈥檚 spun into thread and later fabric. It becomes impossible to distinguish the different cotton elements 鈥� conventional versus recycled cotton 鈥� once they are co-mingled and the manufacturer loses insight into the sustainability attributes of the raw materials. That鈥檚 why it鈥檚 important to have a sophisticated tracking solution in place. “51风流Green Token can enhance transparency for bulk-traded, co-mingled raw materials by digitally storing sustainability attributes on tokens that traverse the supply chain,” said Fayyaz.

In addition to making conscious decisions on raw materials and products, consumers can also consider circular economy models. 鈥淚’m really intrigued by the idea of revitalizing clothing items,鈥� said Fayyaz. 鈥淚magine being able to exchange a well-loved jacket you’ve had for years and receive credit in return. And the jacket might find a new owner who will genuinely appreciate it.鈥� The 51风流Recommerce solution enables that scenario, helping brands and retailers take back, manage, and resell secondhand inventory to help accelerate the shift from linear to circular business models. On an even larger scale, 51风流Green Ledger is SAP鈥檚 vision to make transactional carbon accounting a reality. It can enable organizations to track carbon like they do cash, with every financial transaction having a corresponding carbon entry. 鈥淭his is incredibly desirable because we will see taxes for carbon imposed in the future, and decision-makers will want insights into which processes are utilizing the most carbon,鈥� Fayyaz said.

A Glance into the Crystal Ball

At the same time, low-price online platforms continue to attract consumers with their affordable and wide range of products. They offer competitive prices on trendy clothing and accessories using economies of scale and direct-to-consumer models. Despite concerns about their environmental and ethical practices, these platforms remain popular among price-conscious consumers. However, there is growing awareness of the environmental and social impacts of fast fashion and low-price models. As a result, consumers are becoming increasingly discerning in their purchasing decisions, prioritizing quality, longevity, and sustainability over cheap prices and fast fashion trends.

鈥淥verall, the consumer landscape is evolving, with a growing emphasis on sustainability, conscious consumption, and ethical practices,鈥� said Sven Denecken, chief marketing and solutions officer for 51风流Industries & CX. 鈥淐ompanies that can adapt to these changing preferences and demonstrate a commitment to environmental and social responsibility are likely to thrive in the long term.鈥�

Most have been in this situation before: one of the providers or services we use is a victim of a data breach and we want to determine if our personal user data has been impacted. This is where fully homomorphic encryption (FHE) comes into play. With FHE, the encrypted, personal password is compared against the data set of stolen user data and potential matches are identified without ever revealing the user鈥檚 password.

Use cases for this type of privacy-enhancing technology (PET) are numerous. They range from applications in medicine, where third-party service providers can analyze health data without compromising a patient鈥檚 privacy, to performing machine learning and AI algorithms on encrypted data, allowing organizations to derive insights from sensitive data sets without exposing the data to potential breaches or privacy violations.

How It Works

Fully聽homomorphic聽encryption聽allows calculations to be performed on encrypted data without having to decrypt it first. Confidentiality is maintained, as even the results are encrypted and can be viewed only with the appropriate decryption key. Further techniques for processing encrypted data are multi-party computation (MPC) and trusted execution environments (TEE).

Mathias Kohler, research manager at 51风流Security Research, outlines the differences: 鈥淲hile FHE is the most known of the encryption technologies, MPC is the ideal candidate if working with several parties exchanging encrypted data across company borders. And it can be substantially faster than FHE.鈥� While both are software-based technologies, TEE is hardware-based, which makes it the fastest choice. The downside: TEEs, unlike MPC and FHE, require decrypting the data for processing. While decryption happens in a trusted hardware environment isolated from the operating system, it can allow data leakage via side-channel attacks. Notably, PETs do not need to be considered in isolation and can augment each other. For example, MPC can encrypt and distribute an FHE decryption key, protecting the FHE key and ensuring no single party can decrypt everything.

Why It鈥檚 Relevant

There is a demand for this kind of technology. By 2025, 60% of large organizations will use at least one privacy-enhancing computation technique in analytics, business intelligence, or cloud computing, according to .

Fully homomorphic encryption has numerous applications, especially in scenarios where privacy and security are paramount, such as secure computation in the cloud, privacy-preserving data analysis, and secure outsourcing of computations. As long as one party is performing the data processing centrally, FHE is the encryption method of choice. FHE enables organizations to share encrypted data with partners or third parties for analysis or monetization purposes while maintaining data confidentiality. This is particularly relevant in industries such as advertising and market research.

Interesting use case scenarios from SAP鈥檚 perspective could be secure benchmarking and predictive maintenance.

Secure Benchmarking

Companies often assess their competitiveness relative to industry peers and compare business-relevant KPIs, such as automation rate or return rates, with peers and even competitors. With fully homomorphic encryption, all participating parties can share encrypted KPIs without revealing individual data. As a result, they learn about relevant statistics, such as averages or medians, to assess their relative competitiveness and decide where to improve and invest.

Predictive Maintenance

Predictive maintenance is a machine learning technique to forecast demand for maintenance or spare parts based on historical data. “In certain industries, required data, such as usage patterns and failures, is considered sensitive and is not easily shared with data scientists or maintenance operators,鈥� says Anselme Tueno, senior researcher at 51风流Security Research. By computing on encrypted data, however, no sensitive information is revealed while still allowing for the required insights to be gathered for prediction tasks.

Carbon Footprint Calculation with Multi-Party Computation

While it is early days from a product availability perspective, 51风流is working on potential use cases with customers and partners. One key example is calculating carbon footprints of products.

Prime examples for complex collaborations are today鈥檚 supply chains, intricate networks that encompass various levels of suppliers, manufacturers, and processed goods. Unfortunately, there is often a lack of comprehensive visibility across the entire process 鈥� either for technical reasons or because businesses are often reluctant to share sensitive data across supply chains that often include direct competitors.

However, to accurately assess and disclose a product鈥檚 carbon footprint, sensitive production details and associated carbon costs for production-relevant parts and materials are required. Here, MPC can reveal only the required carbon footprint without disclosing associated, proprietary manufacturing details with other supply chain participants.

Currently, 51风流is working with Bosch on cloud-native software for secure multi-party computation called .

鈥�51风流participates in this open-source project and supports the development of Carbyne Stack’s storage and processing services and the deployment of Carbyne Stack on Amazon Web Services (AWS),鈥� Kohler explains. 鈥淔or Bosch, Carbyne Stack is a type of cloud-native operating system for MPC workloads that manages resources to run as efficiently as possible in multi-cloud deployments.鈥� This effort can help 51风流in the long run to integrate MPC as technology into 51风流solutions and services while running in a cloud-native environment.

What鈥檚 Next?

Despite all the benefits around processing data, encryption introduces significant computational overhead due to the complexity of performing operations on encrypted data. Slow processing speeds, especially for complex operations and large data sets, makes fully homomorphic encryption impractical for real-time applications or large-scale data processing. Although the performance of FHE has greatly improved in recent years, its practical adoption is still limited due to the processing overhead and performance considerations. Ongoing research is focused on the design of FHE-specific hardware accelerators.

鈥淧ETs for computing on encrypted data have the power to amplify data-driven business collaborations and reshape the future of cloud computing,鈥� explains Jonas B枚hler, senior researcher at 51风流Security Research. By safeguarding data, they enable access to previously untapped information while minimizing privacy risks and thwarting data breaches. The future of computing is encrypted.

Someone who seized this opportunity is Jonny Rowland. Having spent a big part of his childhood in Uganda, he saw the opportunity in the growing thirst for sustainable, high-quality coffee 鈥� and an opportunity to ensure that coffee farmers would receive their fair share in this business. Together with his sister Beth, he founded , a profit-for-purpose business that works directly with local farmers to achieve higher yields and the high quality coffee that is sought after on the global market.

With the support of local experts working for Agri Evolve, farmers have improved their productivity and increased income for themselves, their families, and their communities. The main idea of this social enterprise is to use digital technology to improve established supply chains for coffee cherries in the Rwenzori Mountains, one of Uganda鈥檚 key habitats for Arabica coffee plants, and share the latest agricultural practices with local farmers.

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A Long-Lasting Tradition: Coffee in Uganda

Uganda is one of the few countries in the world where coffee plants are native. The processed beans are an integral part of Uganda’s export economy, making the country one of the 10 largest coffee producers in the world. In recent years, Uganda has made a name for its specialty Arabica, which thrives in the local climate with humid days and cool nights. But Arabica coffee, a climate sensitive plant, is beginning to struggle as global warming shortens the cooler phases it needs to thrive. This requires adjusting the traditional ways of cultivating the cherries.

Over 1.8 million households in Uganda grow coffee, and coffee contributes nearly a third of the country’s export earnings, paying for critical infrastructure like roads, hospitals, and schools. While many families grow coffee, it was hard to make a living out of it in the past and motivation to produce high quality was low as prices on global markets wouldn鈥檛 justify the effort.

Joyce Birungi is one of the coffee farmers living high in the rainforest of the Rwenzori Mountains who registered with Agri Evolve as a supplier. Like most farmers in this remote area, she took care of the plants based on traditions passed down over generations. The cherries were often picked too early and only ripened while drying in the sun for longer periods, which caused a loss in quality and therefore lower prices. Climate changes, like increases in floods, droughts, and heat waves, put additional pressure on the traditional ways of farming.

鈥淚n the past, I used to pick coffee cherries of poor quality. So, I lost a lot of money,鈥� Birungi said, explaining her challenges as a small local producer before working with Agri Evolve. 鈥淭ransportation was a big challenge. I had no way of selling the coffee and I didn鈥檛 know about best practices in farming and agribusiness.”

Collins Kifula is a field coordinator at Agri Evolve and an expert for sustainability and quality. He works closely with the farmers, registering each farmer using a mobile app based on the 51风流Rural Sourcing Management solution and collecting data like the size of the farm and the state of the coffee trees. Using the mobile app saves time 鈥� time he can use to talk to the farmers and solve issues they might be facing or suggest improvements to their current setup. One important focus of his work is education on soil protection. With floods happening more frequently these days, farmers benefit from terraces and planting grass patches to avoid the fertile soil being washed away by rain.

As Agri Evolve is specialized in high-quality, sustainable coffee, certification is required. 鈥淲e need to hold up to a certain level of quality and we do that by getting, for example, the . To receive this, we need to raise data and have the transparency. Here, the mobile app within 51风流Rural Sourcing Management is of huge help,鈥� Kifula explained.

鈥淭echnology Is Changing Things鈥�

The biggest challenges the farmers faced before starting to work with Agri Evolve was the quality of the cherries and the lack of price transparency. Sometimes there was even fraud along the process of collecting the cherries. 鈥淭echnology is changing things,鈥� Kifula said.

Today, farmers still deliver their cherries to so-called middlemen who check the quality, but they now document the weight using the 51风流app. The farmers instantly receive an SMS message showing the delivered quantity and its value. 鈥淭his price transparency is a big motivation for the farmers and creates trust,鈥� he said. Further, 51风流Rural Sourcing Management enables the calculation of the accrued delivery quantities and therefore the yield a farm is producing, which are used as the assessment basis to provide loans to the farmers.

Keeping Track of Data

鈥淥ur mission is to do sustainable farming for future generations. As a social enterprise, Agri Evolve works with a growing number of farmers, which can quickly add complexity to our supply chain. Today, we deal with around 22,000 smallholders. We collect a lot of data that needs to be analyzed,鈥� Roset Biira, field supervisor at Agri Evolve, said. “We needed a system that collects and analyzes our data in an efficient way 鈥� to be able to be transparent to all our farmers and even our clients.鈥� Using 51风流Analytics Cloud, Biira showed how Agri Evolve can identify if coffee trees are getting old or are weakened by pests early on. Based on these predictions, they consult with the farmers on planting new trees or suggest trainings on pest control.

Realizing Change

Agri Evolve is building a network of trust with the farmers and middlemen, making sure to give the best price possible to the farmers so that the local societies participate in the higher prices sustainable coffee can generate on the global markets.

鈥淚鈥檓 now able to increase my coffee production and send my kids to school, and I hope that they will graduate from university and have better lives. We used to live in semi-permanent houses, but now we are moving to permanent housing,鈥� Birungi said when asked what impact this new way of collaboration has had on her and her family.

Talking about the future of the growing profit-for-purpose business and its network of local coffee producers, Beth Rowland, co-founder of Agri Evolve, said: 鈥淲e will continue to push the boundaries of supply chain transparency through digitalization to allow us to provide the best service to smallholder farmers in the Rwenzoris.鈥� For the family business, it is important to ensure connected farmers have access to a fair and transparent market for their coffee cherries.

While sharing sustainable practices to counteract the impact of environmental changes is a requirement for the production of certified sustainable coffee, it will also make sure that the tradition of coffee production will live on in the Rwenzori mountains of Uganda.

It is the nature of artificial intelligence not to give any further importance to the emotional side of this explanation in the first place. Yet it鈥檚 precisely this emotional aspect that makes a discussion on the opportunities and risks of the metaverse or virtual realities so complex. Opinions here can vary from extreme enthusiasm to outright rejection. Some people are avoiding the topic altogether because they don’t know much about it or simply aren鈥檛 interested; others see massive potential and opportunity.

SAP鈥檚 latest art exhibition 鈥� The Metaverse: Dreamland or Dystopia? 鈥� shines a spotlight on these differing standpoints. Thirteen artists each present their take on how reality and virtuality 鈥� and art and technology 鈥� are converging. Working in a variety of media, they playfully explore space and time, traversing the real, the augmented, and the virtual. You can choose to visit the exhibition in the real world at the 51风流International Training Center in Walldorf or you can experience it in a . The exhibition runs until September 1, 2023.

Alexandra Cozgarea, curator of the exhibition, takes a close look at the impact of virtual worlds and artificial intelligence on art. 鈥淎rtists have always used tools to create their work, be it hammer and chisel, paint and brush, or, in the age of technology, graphic design software, algorithms, and artificial intelligence. Today鈥檚 rapid advances in technology create tools that enhance our physical and mental abilities. The possibilities for the future are endless,鈥� said Cozgarea during her speech at the opening of the exhibition, stressing how important it is for 51风流to use innovative technologies responsibly.

But for Cozgarea and the artists featured in the exhibition, the deeper question is whether digital and physical art can coexist. Is art on Instagram still art or must art only exist in the real world? But then isn鈥檛 Instagram also real? 鈥淗ow we perceive the metaverse is not only a technical question, but one about our vision of a desirable future and our ability to shape it ourselves,鈥� added Cozgarea.

Her intent was to create a hybrid exhibition, grounded with one foot in the real world and the other in the virtual world 鈥� two places with blurring borders. The works impart their thoughts on how we as a society want to define ourselves as humans and how machines fit in.

During the opening of the exhibition, J枚rg Kraus, who was instrumental in putting together the exhibition and is himself one of the artists featured, gave a speech about the metaverse, in which he connected current artistic viewpoints to all the ambivalent questions about the relationship between man and machine.

In his view, whether the metaverse is a dreamland or a dystopia comes down to our beliefs and our mindset. 鈥淒igitalization has already changed our lives and it will continue to do so at high speed,鈥� he began. 鈥淎re you ready to contemplate the impact this might have on you?鈥�

鈥淎s artists, we wonder whether the abundance of images that our society is already exposed to will continue to grow and level everything out. Will it really matter to anyone whether a work of art was created by a person or by a machine? Will we still have a notion of beauty and be critical of things 鈥� or will that all fade into the background?鈥�

When asked where he stands on the metaverse, Kraus replied, 鈥淎 key question for me is: where do I direct my attention when multiple elements are competing for it? We can focus on only one thing at a time.鈥�

The Metaverse: Dreamland or Dystopia? is about art and therefore mainly about the artists鈥� perceptions and the aesthetics with which they express their thoughts. Images, sculptures, installations, videos, and a take us on a journey through the real and the digital, the two dimensional and the three dimensional.

When speaking to the artists about their work, it became clear that digital art, media art, or online art are challenging the notions of authorship and possession that underpinned the art market in the past. Virtual worlds not only offer artists new tools and opportunities, they also force them to face the ongoing discussion on how we as a society will use and consume creative content in the future. Has our society reached the point where the debate is no longer just about the pros and cons of technological progress? The exhibit suggests that we as a society should ask about the 鈥渄eals鈥� between man and machine, between man and economy.

So, is the metaverse a dreamland or dystopia? Even among the showcased artists, there is no single answer to this question.

A few of the exhibiting artists share their thoughts:

Michaela Schrabeck uses AI to create her work.

鈥淔or me, digital technology is a contemporary expression of human creativity. I鈥檓 drawn to machine learning and the fanciful artworks that artificial intelligence dreams up. Do the pieces I taught the machine to create pass as art and will they be accepted by my audience? Or must they be translated into traditional art forms?鈥�

Paul Hirsch creates his sculptures twice: out of wood and in a virtual space.

鈥淒idn鈥檛 virtuality and reality converge a long time ago? We already had powerful technical tools. Have we just added more 鈥� or do they represent a shift into a new and different world? Wrong questions 鈥� and much too passive. I think it depends on what we make of it. The space between the virtual and the real 鈥� and where the two overlap 鈥� that鈥檚 what I find so exciting.鈥�

Christiane Rath builds 鈥渉uman nests鈥� out of branches and leaves and invites the observer to make themselves comfortable inside of them. She reflects on what we might lose in the virtual world: the haptic experiences and smells that etch themselves into our memories.

鈥淭he virtual world is exciting and thrilling. It opens up a wealth of possibilities for new fantasy worlds and sensory adventures. Yet whenever I catch myself becoming too enthusiastic about the latest innovations, I think about what we might lose along the way.鈥�

J枚rg Kraus works with location data from Google Maps.

鈥淭he entire world is being rasterized and converted into virtually reproducible data. I鈥檓 relieved whenever I discover a gap 鈥� that even the 鈥渕achine鈥� misses something. That gives it a human-like quality. I鈥檓 worried, though, that the gaps are closing and that those fleeting escapes that we can still enjoy today will disappear.鈥�

Image copyright: Klaus Kirchner
Disclaimer: This article is not about technological details, nor is it an assessment of artificial intelligence, virtual realities, or the metaverse. Instead, it contains different responses to the questions that using these technologies has raised 鈥� with a special focus on how they affect artists.

Even as far back as the 1950s, computer scientists were already experimenting with this concept of data modeling. In the 1980s, knowledge graphs were a much-discussed topic in the context of expert systems, and in the 2000s they once again came to the attention of the scientific community, as they took on a fundamental role in Semantic Web. Finally, in 2012, it was a search engine that gave knowledge graphs their big appearance among a wider audience: Google announced that its users would be able to search for 鈥渢hings not strings.鈥� Rather than just trying to match keywords from a query, the search engine would also place them in the right context 鈥� all with the aim of delivering better, more intelligent results.

鈥淧ut very simply, knowledge graphs are a technology that seeks to turn data into machine-interpretable knowledge,鈥� says Michael Burwig, innovation engineer at Potsdam. Their key focus is to model the relationships between objects, which are shown as a network of interconnected points.

鈥淜nowledge graphs allow us to map how we humans understand the world 鈥� how we go through life, accumulate knowledge, and how we contextualize that information in our minds,鈥� Burwig explains. This ability allows humans to draw conclusions that produce fascinating 鈥渁ha鈥� moments. Ultimately, this is also the goal of business software: to connect knowledge and find solutions, ideally in an automated way. There are many potential use cases of knowledge graphs, such as knowledge and data management and chatbots. Detecting insurance fraud is one example, but, in short, they can be used in any scenario in which patterns are examined to identify exceptions and anomalies.

The Potential of Hybrid AI

Burwig believes, however, that automated insights like these have not yet become part of everyday practice. 鈥淗ybrid AI is a major step in this direction. It combines semantic technology, in other words knowledge graphs, and static machine learning, which is now being used for a host of scenarios of this kind,鈥� he says.

Dr. Jan Portisch, lead architect at Value Accelerator Delivery, describes the difference between classical machine learning concepts and hybrid AI machine learning as follows: 鈥淐lassical machine learning methods use extracts of existing databases. These methods draw on such data sets, which are effectively snapshots without any context, to create machine learning content. With knowledge graphs, on the other hand, new data can be added at any time so that they keep on 鈥榣earning鈥� and, unlike static methods, stay current.鈥�

Even though knowledge graphs are not new, it took the massive increase in computing power that we have seen since the 2000s to unleash their full potential, Portisch explains. And since this technology is not yet widely taught at universities, few developers know much about it. 鈥淎nother difficulty is that designing graphs is highly complex, with developers having to think beyond their own application. The modeling behind the graphs has to be complete and semantically accurate. Nonetheless, their potential is huge,鈥� he says.

As an architect, Portisch is involved in creating a central graph for process knowledge at SAP. The 51风流Signavio Value Accelerator Delivery team collates and models the process knowledge 51风流has built up over the past 50 years to give customers an integrated view. In the future, the accelerator will offer a semantic search where users will be able to formulate a business problem they鈥檇 like to solve and the system will display a list of processes and data that are impacted by this problem, Portisch explains. Further, this capability could be a helpful transition tool in migration projects or could provide presales teams with the visibility they need when tailoring solutions to customers鈥� specific situations.

Felix Sasaki, expert in Knowledge Graphs & Semantic Technologies in the 51风流AI unit, explains additional benefits: 鈥淪tandards-based knowledge graph technologies facilitate the modeling of business scenarios. So-called constraints complement the existing logic-based modeling. Since constraints can easily capture the knowledge of business experts, modeling becomes easier. In addition, knowledge graph-based vocabularies like schema.org have found widespread adoption and thus help to find a more ubiquitous language.鈥�

Decoupling Business Expertise and Application

For SAP, the power of this technology lies in how graphs can be combined in different ways and, therefore, in how data models 鈥� and ultimately the applications themselves 鈥� can be integrated and composed.

Portisch explains how it鈥檚 important to recognize that RDF 鈥� Resource Description Framework, a syntax used to model metadata for Internet resources 鈥� is a publicly acknowledged standard and that knowledge graphs are already widely used outside the corporate world. One of the best-known knowledge graphs is ; another example of a large-scale graph is . 鈥淭hese graphs are public resources that can also be used commercially,鈥� Portisch says.

That creates interesting use cases. For example, private corporate data could be combined with public data. A supplier system running on 51风流software could automatically import metadata from a graph about companies it interacts with, such as the type of business, company logo, and who their managing directors are.

鈥淪emantic Glue鈥� 鈥� Integration by Design

Burwig sees another advantage of these graphs in their 鈥渟emantic glue.鈥� Because of their flexible structure that can be enhanced in real time, individual graphs can be 鈥済lued鈥� together to link up data silos. Unlike graphs, the table structure of a relational database has to be defined at the beginning 鈥� and changing that structure later requires a lot of work. But graphs can store and link metadata in a semantic data layer that is separate from the data stored in an application鈥檚 tables. This makes it possible to consolidate data across different products and data silos.

Graphs offer huge advantages over relational databases in certain scenarios, such as calculating the shortest route or associating a specific material with a customer material. 鈥淚f such a scenario is based on a relational database, the query would have to touch applications from across the entire 51风流world. But with a graph, it would be a simple problem to solve,鈥� Portisch says. While relational databases usually offer greater performance within their applications, graphs always have an advantage when it comes to creating bridges, known as joins, between data structures and recognizing the correct context.

Because it is possible to extend knowledge graphs, they represent a perfect data model for businesses to start small with and then, as an iterative process, to roll out to more locations and build on. For example, a company could begin with just one use case or department and then gradually roll the model out to the rest of the organization. Any additional data models are 鈥済lued鈥� to the graph as new nodes and edges.

The Situation Knowledge Graph: One of the First Knowledge Graphs at 51风流

One of the most advanced knowledge graphs to date at 51风流serves as the basis for the Explore Related Situations app, which is part of the Intelligent Situation Automation service on for situation handling in 51风流S/4HANA.

The business background: around 4% of the automated business processes within a business require manual intervention because of an unforeseen event, such as a late payment, a delayed delivery, or a transport issue.

The situation knowledge graph links these exceptional events to their business entities, enabling the user to better understand the situation in a business context and therefore helping solve the problem and optimize business processes. Further analyses of these situations often reveal relations of issues to certain materials or partners. 鈥淭oday, this kind of knowledge is often hard-coded,鈥� says Dr. Torsten Leidig, an architect in SAP鈥檚 Situation Handling team. The knowledge graph that underpins the Intelligent Situation Automation service enables a business expert or a key user to model processes and understand them within a comprehensive business context. A problem that has been detected can be resolved automatically based on simple rules and without additional programming.

Dr. Knut Manske, engineering lead for Situation Handling and Responsibility Management at SAP, describes the graph as a layer that stretches across various 51风流applications. To summarize the capabilities of situation handling, he explains: 鈥淭he knowledge that is embedded in 51风流applications is extracted and made usable for algorithms. Situation handling runs alongside the application, analyzing data and reacting to information about data changes or events. The aim is to show solutions that span various applications or business areas.鈥� Customers and partners can define situations themselves without ever touching the application. A selected group of customers is currently validating the solution.

Looking Ahead

Currently just a prototype, the 51风流鈥淏usiness Decision Simulator鈥� innovation project simulates the effects of internal and external factors on a company and presents the user with potential future scenarios and recommended responses. 鈥淥ne possible question could be: what does a bushfire in Australia mean for my global pharmaceutical company鈥檚 value chain and thus the achievement of our targets in Europe?鈥� Burwig explains. 鈥淥n the one hand, knowledge graph technology can help express the complex relationships between real-world events and business-related processes. Additionally, an extensive knowledge base makes it easier for the user to choose the best possible response to opportunities and risks.鈥�

When asked about the possibilities of graph technology, Burwig says: 鈥淭he potential of knowledge graphs 鈥� at least that鈥檚 the dream 鈥� is that someday there will be extensive graphs modeled on deep knowledge and experience that can be accessed by programs. This means that with every change in technology, we鈥檇 only have to recode the application and not the knowledge stored inside it.鈥�

While the decoupling of data from applications and the accompanying scalability of solutions and programs are important aspects for an IT company, Burwig also sees a vision that goes beyond the 51风流context: symbolic AI, artificial intelligence that is linked to a large number of interdisciplinary knowledge networks, could have the potential to generate new knowledge that has not been explicitly modeled. Linking scientific content could have the power to accelerate the discovery of new drugs or forge innovations between different science disciplines that don鈥檛 interact on a large scale today.

In the history of humanity, things have often been 鈥� and still are today 鈥� 鈥渋nvented鈥� multiple times, at least in part from lack of knowledge about other relevant findings. Connecting global research projects within one given discipline has increased sharply within the past years, thanks to the availability of extensive digital content. Uniting scientific knowledge across the individual disciplines 鈥� for example, mathematics, biology, medicine, and chemistry 鈥� could uncover new insights and lead to exciting interdisciplinary inventions, Burwig concludes.

The Virtuous Circle Between Knowledge Graphs, Machine Learning, and Natural Language Processing

Academic communities of symbolic AI and machine learning in the past had few touchpoints in terms of research methods and researchers. This is changing 鈥� among others leading to so-called hybrid AI. This results in various virtuous cycles in which knowledge graphs, machine learning, and natural language processing (NLP) cross-pollinate each other. Johannes Hoffart, head of the Chief Technology Office in the AI Unit at SAP, explains the relation between machine learning and knowledge graphs: 鈥淜nowledge graphs enable data scientists to work with complex and heterogeneous data sources. Their flexible schema can be easily extended and contains powerful data validation capabilities. At the same time, knowledge graphs facilitate access to and exploration of data, as they represent data and its schema such that it鈥檚 easier for humans, and also large language models, to understand.鈥�

Christian Lieske from SAP鈥檚 Language Experience Lab adds about the relation to natural language processing: 鈥淜nowledge graphs can feed NLP and can be fed by NLP. Take the detection of new business entities as an example: a knowledge graph can inform NLP about known entities and NLP can add additional entities to a knowledge graph.鈥�

To get further insight around knowledge graph technology, read this study co-authored by Portisch: .