With the introduction of SAP Datasphere in March 2023, SAP Customers and Partners were provided an opportunity to explore new possibilities for growth and innovation through advanced analytics, machine learning, and AI-driven insights using SAP Datasphere.

SAP Partners, in particular, found themselves immersed in a wealth of learning opportunities. The SAP Learning Hub , hands-on workshops, and the chance to dive into SAP Datasphere instantly with the free tier of SAP BTP became valuable resources. The Hack2Build initiative, not only provided a collaborative platform for partners to team up with SAP but also offered the chance to ideate, build, and monetize SAP Datasphere solutions.

Spanning from October 10 to 18, the Hack2Build event saw 17 partners from Europe, the Middle East, and the Asia Pacific region coming together. During the Hack phase, SAP experts provided crucial support, offering guidance on solution ideas, architecture, content validation, and advice. The culmination of this intense week-long effort was the Demo Jam, where participating teams showcased their prototypes to a senior panel of judges.

Partners represented in Hack2Build SAP Datasphere 2023

The blog captures the essence of this collaborative journey, shedding light on the most promising solutions that caught the judges’ attention. From addressing customer pain points to hands-on demos of their prototypes, the blog depicts the innovative strides taken by these partners during the Hack2Build event.

EMEA Region

Winner: Capgemini

Workers / Employee safety monitoring

The purpose of this application developed by Capgemini is to automate worker’s safety in production line. The whole use case is built around human sustainability, to simplify a manual process. Today, there is still high manual intervention needed to monitor health and safety in plants. The solution allows manufacturing company to gather images of workers wearing their protective gear as per requirements and those who are not wearing the required protective gear. Videos and pictures captured in the plant is fetched and verified through AI algorithms.The model output is fetched in SAP Datasphere using the Google BigQuery connector. Injected data is enriched in SAP Datasphere with HR master data. Using SAP Analytics Cloud, the compliance report is visible for HR and plant supervisor and managers for further action.

Workers safety monitoring by Capgemini

1st Runner-up: Exxeta

 Salesforce Content for SAP Datasphere and Analytics Cloud

In today’s fast paced world, it is more important than ever to have a clear picture of mission critical business processes, no matter how complex or distributed they are. With our solution, a standard content for integrated Salesforce Sales Cloud and S4/HANA data, we leveraged the business data fabric approach form SAP and closed the integration gap between these two systems. It enables business users to analyze the complete sales pipeline from campaigns to sales orders and get an end-to-end view of the process. Therefore, we used open connectors from SAP Integration Suite to integrate Salesforce data into SAP Datasphere and harmonize the data there with S4/HANA Cloud Content. As a result, we developed an analytic model that covers data including campaigns, leads, opportunities, quotes, and orders as well as respective master data. The SAC story on top enables end users to analyze this process and take necessary actions to optimize their sales activities.

Exxeta’s Salesforce Content for SAP Datasphere and SAP Analytics Cloud

2nd Runner-up: NTT Data Business Solutions

HXM Controlling with ML approach

NTT Data’s solution is based on SAP Datasphere and SAP BTP which enables HR departments to do a headcount forecast based on known and unknown facts. Employee master data and employment events are taken from SAP SuccessFactors and based on these data the headcount is forecasted into the future. In addition the solution used the HANA PAL library in the HANA Cloud for a machine learning approach based on regression to calculate the churn probability of every single employee based on master data from SuccessFactors. The aggregated churn probabilities are deducted from the future headcount. This advanced headcount enables HR departments to improve their headcount planning and to identify workforce risks.

HXM Controlling with ML Approach by NTT Data

Asia Pacific Region

Winner: Infosys

Cognitive Customer Insights

The Infosys Cognitive Customer Insights’ solution helps to improve supply chain processes such as demand planning and order fulfillment. It offers a 360° view of customer sales process and helps improve forecast by leveraging external insights such as trends, weather data for predictions. The solution uses machine learning capabilities for prescriptive analytics to improve demand forecast and thereby improves fulfillment, reduction of stock-outs and returns. It offers an automated feature to get weather information and google trends and uses them in algorithms to get the short-term forecast. The solution also helps organization provides visibility of carbon footprint in entire supply chain including returns and helps achieve the sustainability goals by reducing CO2 footprints and packaging waste. SAP Business Technology Platform capabilities such as Data Provisioning and Integration, Data Modeling and Processing, Data Visualization and Analytics, AI/ML modeling and python are used by leveraging SAP Datasphere, SAP Data Intelligence Cloud and SAP Analytics Cloud.

Infosys Cognitive Customer Insights

Runner-up: LTIMindtree

Supply Chain Intelligence

LTIMindtree developed the supply chain intelligence solution to create resilient supply chains that are predictive, intelligent, and agile. The solution helps to identify potential disruptions and suggest actions for remediation; utilize untapped external data sources to predict issues, and finally reduce the impact on end customers by increasing reliable order fulfillment. The solution addressed some of the challenges of integrating external factors like weather and geopolitical events, coming in an unstructured format along with SAP data from SAP S/4HANA. Leveraging SAP Datasphere, SAP Analytics Cloud, and Machine Learning, the solution provides real time insight into the full supply chain and order fulfillment, helps to identify disruptions, and mitigates risks by allowing the users to review the recommended corrective actions suggested by the solution.

LTIMindtree Supply Chain Intelligence

We extend our heartfelt appreciation to the esteemed panel of judges for dedicating their time and expertise to evaluate the innovative solutions presented by our partners during the Hack2Build initiative. The judges insightful feedback and encouragement play a pivotal role in motivating our partners to further develop and implement their groundbreaking ideas.

 Panel of Judges

• Pavel Penaz, Head of SAP BTP Strategy & Execution, Partner Solution Adoption, SAP Czech Republic
• Stephane Borg, Team Lead, Partner Solution Adoption, EMEA-South, SAP SE
• Guido Eichmann, Delivery Manager, SAP BTP – SAP Analytics Cloud and SAP Datasphere Business Content, SAP SE
• Manjunath Gopadi, Director, Cross Engineering India, HANA and Analytics, SAP Labs India
• Rudolf Held, Vice President, Global Head of SAP Co-Innovation Lab, PES, SAP SE
• Gareth Bowen, Vice President, Regional Head, Partner Ecosystem Success, SAP Singapore
• Klaus Werner, Vice President, Data Warehouse Engineering Services, SAP SE

We extend our heartfelt appreciation to all participating companies for their dedication and ingenuity.

Moving Forward

Beyond the hack phase, the SAP Co-innovation Lab stands ready to support partners in bringing their innovations to full fruition. Those who complete the journey gain access to SAP’s influential go-to-market teams, amplifying the impact of their solutions. This is just the beginning of an exciting partnership, where collaborative innovation thrives.

For those eager to embark on similar ventures with SAP, we encourage you to express your interest by registering for upcoming initiatives through the following link: Hack2Build Calendar

Special thanks to  Raghuvira BHAGAVAN and  Karthik P   for their contributions to this article.