Global Battery Manufacturer Taps Pythian to Unlock Insights from SAP Data to Improve Demand Forecasting in Google Cloud

⇨ The integration of multi-sourced third-party data with the SAP environment using Google Cloud Cortex Framework significantly enhances forecasting intelligence and customer service levels for the manufacturer.

⇨ Companies are increasingly prioritizing diverse data sources for business intelligence, with 75% viewing cloud analytics capabilities that unify disparate data as crucial for successful strategies.

⇨ Effective demand forecasting and inventory management can be achieved by utilizing technologies like Google Cloud BigQuery, which allows seamless integration and analytics of both SAP transactional data and external information.

For this global manufacturer and distributor of consumer and automotive batteries, enhancing customer service levels without sacrificing efficiency was key to achieving their goals. The ability to analyze and predict manufacturing and sales demand would significantly improve resource planning, product delivery and customer satisfaction—but amalgamating the necessary data to make those decisions was proving difficult. The company’s SAP environment could manage its manufacturing processes and financial controls, but it was difficult and costly to source and incorporate third-party data like population demographics, weather forecasts, and other outcome-influencing information into one analytics environment.

SAP Silver PartnerEdge firm Pythian was engaged to implement a data environment leveraging Google Cloud to integrate the client’s SAP environment with multi-sourced third-party data. This would help to deliver a substantial improvement in forecasting intelligence and ensure that customer needs were reliably met. Pythian determined that the Google Cloud Cortex Framework, specifically designed to consolidate data sources, could effectively consolidate and analyze the manufacturer’s data to achieve its goals. Pythian managed the entire implementation of the Google Cloud Cortex Framework and its integrations, including building dashboards to provide visuals of the data and providing training for the in-house IT team.

This manufacturer is one of among many modern companies striving to become a more data-driven enterprise, which can be defined as an organization that prioritizes the use of data as a fundamental element of its strategic decision-making processes. Defining attributes include:

• Data sets are consolidated into a unified architecture to provide a comprehensive view
• Employs advanced analytical tools and technologies to extract insights from data
• Culture of data literacy
• Decision-making processes are predominantly based on data analysis
• Adopts predictive analytics to forecast future trends and behaviors
• Data governance frameworks are in place to ensure data quality, privacy, and compliance

Recent SAPinsider research indicates that enterprises are increasingly pushing their business intelligence and analytics solution partners to incorporate a diversity of data sources. The research report, Evolving Business Intelligence and Analytics to Create the Intelligent Enterprise, revealed that 75% of companies consider cloud analytics capabilities that unite data from disparate sources as an important or very important requirement for their business intelligence strategy to succeed.

Disparate data, including external data like weather forecasts, supply chain trends, or social sentiment, can improve the accuracy of predictive models used in SAP analytics solutions. For example, combining production data from SAP S/4HANA with weather patterns can help manufacturers anticipate supply chain disruptions, optimizing production and distribution plans accordingly. When multiple data sources are unified, prescriptive analytics becomes more effective in suggesting actionable insights. Integrating financial and operational data, for instance, allows SAP customers to predict future cash flow needs or inventory requirements, enabling proactive resource allocation.

The Pythian team utilized the following technologies: Google Cloud Cortex Framework, Google Cloud BigQuery, Google Cloud, Google Cloud Composer, Looker, SAP SLT, SAP HANA, SAP ECC, and AecorSoft.

Pythian successfully deployed Cortex-enabled demand forecasting in the customer’s SAP environment, resulting in an analytical model that now combines third-party data—such as long-term weather forecasting and population data— with their ERP data, to better predict and plan for demand fluctuations in the battery product and automotive product categories.

• More accurate production and product placement in the warehouse to fulfill store-level inventory needs.
• Development of a strong foundation for further transformation and the ability to use machine learning for different product lines in other parts of the business.
• Ability for the marketing team to kick-start insights, adapt to changing market demands and reduce time to value.

What this means for SAPinsiders

Share your data management strategies. The focus on enterprise data management is intensifying with the proliferation of 5G, IoT, AI/ML and other transformative technologies. SAP customers are increasingly looking for new data management models for the storage, migration, integration, governance, protection, transformation, and processing of all kinds of data ranging from transactional to analytical. Balancing the risks, compliance needs, and costs of data management in SAP HANA on-premise and on the cloud while also providing reliable, secure data to the organization is increasingly important to the business We will be releasing the 2025 Data Management Strategies research report in February 2025. Contribute to the research by completing this survey: https://www.research.net/r/DataMgt25.

Leverage Pythian’s BigQuery expertise to enable enhanced data analytics. Google BigQuery enables large-scale data analysis with the ability to handle structured and unstructured data. SAP customers can integrate BigQuery with SAP data using tools like SAP Data Services or Google Cloud’s BigQuery Data Transfer Service, enabling them to analyze SAP transactional data alongside external data sources, such as customer behavior or market trends. Pythian specializes in optimizing data pipelines and developing analytics solutions on BigQuery. By leveraging Pythian’s expertise, SAP customers can build efficient ETL processes, ensuring seamless data flow from SAP to BigQuery and gaining access to advanced analytics and ML models for predictive insights on inventory management, customer segmentation, and sales forecasts.

Realize unified access to insights across the enterprise. For SAP customers operating in hybrid or multi-cloud environments, Pythian can assist in architecting solutions that allow seamless data sharing and integration across platforms. Google Cloud’s Anthos can further support hybrid deployment strategies by providing a unified platform for SAP data access, regardless of the underlying infrastructure. Also, by integrating SAP data with Google Cloud’s Looker platform, SAP customers can create powerful dashboards that provide a comprehensive view of business operations, improving accessibility to insights across departments and supporting a data-driven culture.