SAP BTP: “Change Agent” or “Scale Agent” Part 7 – How to select Data & Analytics BTP Services

[AshokNM]

SAP Business Technology Platform offers a robust suite of over 80 services, many of which play critical roles in supporting enterprise-level operations. The challenge lies in determining the right combination of services tailored to specific use cases. Crafting an effective SAP BTP solution requires a deep understanding of the platform. While established architectural patterns provide a solid foundation, assessing individual use cases to identify the most suitable architecture is a skill that requires experience and strategic evaluation.

How to decide when to use what services in SAP BTP

To effectively choose the right services, it is essential to understand the core archetypes within SAP BTP, which include:

• Application Modernization
• Data Modernization
• AI & Generative AI

The first step in determining the appropriate services is to classify your application as either transactional or analytical. Transactional applications typically align with the Application Modernization archetype, while analytical applications are categorized under Data Modernization. This classification serves as the foundation for building an application on SAP BTP.

Once the core archetype is defined, further enhancements can be incorporated, particularly with AI or Generative AI services, which fall under the AI & Gen AI archetype. For a broader understanding of the classification, please refer to Figure 1.

Figure 1 – Determining application as Transactional or Analytical

After identifying the correct use-case type, you can begin designing the appropriate architecture. This step is crucial for determining which SAP BTP services are essential for implementing and optimizing the solution.

Data Modernization archetype

Applications categorized as analytical fall under the Data Modernization archetype, highlighting their role in transforming and enhancing data processes and infrastructure. This categorization is essential as it aids organizations in identifying and leveraging technological advancements to optimize data management and utilization.

Figure 3 below provides a decision flow to further illustrate this classification and guide stakeholders in understanding and applying these principles effectively. By adhering to these frameworks, businesses can enhance their data processing capabilities, ensuring more efficient and insightful data-driven decision-making.

Figure 3 – Data Modernization archetype decision matrix

Step-1 – Business Intelligence

Ask if it's a standard report or dashboard accessed from a single source; if yes, use SAP Analytics Cloud.

Creating non-standard custom reports in SAP S/4HANA and extending them with SAP Analytics Cloud (SAC) can greatly enhance your reporting capabilities. Here are some examples where custom reports can be developed:

Application Type	Finance	Sales, Service & Marketing	Procurement & Expense Management	Supply Chain	Human Resources	Operations	IT
Multi source Financial Analysis Report	X
Procurement and Supplier Performance Dashboard			X
Sales Pipeline & Revenue Forecast Report	X	X
Manufacturing Efficiency & Downtime Analysis						X
Customer Profitability and Segmentation Report	X	X
Environment, Social & Governance (ESG) Report	X		X	X	X	X	X
Consolidated Budget vs Actuals Report	X

• **Multi-Source Financial Analysis Report**:

   - **Objective**: Aggregate financial data from different source systems or modules like FI, CO, and external databases.

   - **Features**: Real-time currency conversion, dynamic profit center hierarchy adjustments, and custom KPIs.

   - **SAC Integration**: Use SAC’s Visualization tools for dynamic dashboards and predictive analytics to forecast financial trends.

• **Procurement and Supplier Performance Dashboard**:

   - **Objective**: Evaluate and monitor supplier performance in real-time, integrating data from procurement, quality management, and external vendor ratings.

   - **Features**: Supplier scorecards, lead time analysis, and quality non-conformance rates.

   - **SAC Integration**: Create interactive dashboards with scorecards and trend analyses to manage supplier risks and opportunities.

• **Sales Pipeline and Revenue Forecast Report**:

   - **Objective**: Provide insights into sales pipeline status and revenue projections.

   - **Features**: Sales cycle analysis, probability-adjusted forecast, and win/loss ratios.

   - **SAC Integration**: Use predictive analytics to forecast sales and identify the highest impact leads using machine learning models.

• **Manufacturing Efficiency and Downtime Analysis**:

   - **Objective**: Track production efficiency and downtime to improve operational performance.

   - **Features**: Machine-level efficiency reports, downtime causes analysis, and OEE (Overall Equipment Effectiveness) calculation.

   - **SAC Integration**: Use SAC to visualize production KPIs and create automated alerts for operator action.

• **Customer Profitability and Segmentation Report**:

   - **Objective**: Analyze customer data to understand profitability and identify high-value segments.

   - **Features**: Profitability scorecards, churn analysis, and segment-based profit comparisons.

   - **SAC Integration**: Utilize SAC for customer profitability analysis with segment drill-downs and advanced data visualizations.

• **Environmental, Social, and Governance (ESG) Report**:

   - **Objective**: Compile and analyze ESG metrics for sustainability reporting.

   - **Features**: Carbon footprint analysis, diversity metrics, and compliance tracking.

   - **SAC Integration**: Leverage SAC to create comprehensive ESG dashboards with benchmarks and performance indicators.

• **Consolidated Budget vs. Actuals Report**:

   - **Objective**: Compare budgeted figures against actuals across various organizational units.

   - **Features**: Variance analysis, periodic trends, and multi-level budget hierarchy reports.

   - **SAC Integration**: Use SAC’s planning capabilities to simulate future budget scenarios and variances.

To create these custom reports, collaboration between business analysts, report developers, and subject matter experts is essential. SAC’s capabilities in data connectivity, visualization, and machine learning provide a robust platform to build and deploy these tools effectively. Always ensure data integrity and security when handling sensitive business information across these platforms.

Step-2 – Business Data Fabric

Consider if data from multiple sources is needed; if yes, employ SAP Datasphere for a unified enterprise data view.

Application Type	Finance	Sales, Service & Marketing	Procurement & Expense Management	Supply Chain	Human Resources	Operations	IT
Billing and Revenue Innovation Management	X	X
Transforming operations and enhancing efficiency						X
Streamline Global Operations							X
Scaling via Compliance Regulations	X
Water Management Innovation
Integration of business processes across LOBs
Combining Billing data with Revenue	X
Brand Ambassador customer 360 Application		X
Centralized Group-wise Reporting	X
Insight-Driven Financial Decision Making	X
SAP-Driven Data-Driven Decisions							X
Real-time Procurement Report Building			X
Financial Planning Acceleration with SAP	X
Nutrition Data Fabric Application	X
Unplanned stoppages with Machine Learning		X
Fashion E-Commerce Digitalization		X
Next Gen reporting capabilities with Datasphere	X
Data Analytics Integration	X
Efficiency Enhancement in HR					X
Data Harmonization and Management			X
Advanced Supply Chain Analytics				X
Cloud Migration for Business Continuity and Improved Reporting	X
Digital Transformation in Sports and Entertainment Industry					X
HR Data Analytics Self-Service					X
Streamlined IT Processes							X
Centralized Sales Dealership reporting		X
Ethanol operations automation				X
Operational Reporting				X
Remediation of financial discrepancies	X
Anamoly Detection							X
Planning, budgeting, forecasting & re-forecasting	X
Intercompany Reconciliation & Group Consolidation	X
Data Governance Eco-system with collibra		X				X
Cocreating a data fabric infused with context and governance for true business-wide data-driven decision-making			X

SAP Datasphere, formerly known as SAP Data Warehouse Cloud, is a comprehensive data management solution designed to integrate, manage, and analyze data across an enterprise. With its capabilities, businesses can build various kinds of applications and solutions, including:

• **Data Warehousing Applications**:

   - Centralize data from disparate sources for more accessible reporting and analytics.

   - Create a unified view of organizational data to streamline business intelligence processes.

1. **Business Analytics Applications**:

   - Develop robust analytical dashboards and reports using data models and visualization tools.

   - Leverage prebuilt connectors for SAP and non-SAP sources for comprehensive insights.

• **Data Integration Solutions**:

   - Integrate and harmonize data from various sources, such as on-premise databases, cloud services, and external systems.

   - Establish real-time data pipelines to ensure up-to-date insights.

• **Financial and Operational Planning**:

   - Implement planning solutions that integrate financial, sales, and operational data for comprehensive financial forecasting and analysis.

   - Facilitate scenario planning and what-if analysis.

• **Predictive and Advanced Analytics**:

   - Build predictive models using integrated Machine Learning services to forecast trends and behaviors.

   - Use advanced analytics to derive deeper insights from structured and unstructured data.

• **Contextualized Data Access**:

   - Provide tailored data access to various business units, ensuring relevant insights are easily accessible.

   - Enhance decision-making by delivering contextualized data in real-time.

• **Data-Driven Applications**:

   - Develop applications that consume and display data insights directly to end-users, integrating analytics into business processes.

   - Create SaaS offerings for clients that leverage their data for enhanced productivity and operations.

• **IoT and Big Data Analytics**:

   - Harness IoT data by integrating with SAP’s IoT solutions and processing large volumes of data efficiently.

   - Analyze big data sets to extract actionable insights for operational improvements.

• **Customer and Supply Chain Insights**:

   - Develop customer analytics solutions to improve customer experience through insights on behavior and preferences.

   - Optimize supply chain operations with data insights into logistics, inventory, and supplier performance.

The flexibility and scalability of SAP Datasphere allow businesses to innovate and quickly adapt to changing data landscapes, thereby fostering data-driven decision-making across the organization.

Step-3 – Predictive Analytics

Determine if predictive capabilities are necessary; if yes, add HANA Cloud to your data platform and business intelligence.

SAP HANA Cloud's predictive capabilities can be applied across various lines of business (LOB) to provide valuable insights and enhance decision-making processes. Here are some common use cases by LOB:

Application Type	Finance	Sales, Service & Marketing	Procurement & Expense Management	Supply Chain	Human Resources	Operations	IT
Cash-Flow Forecasting	X
Fraud Detection	X
Credit Risk Assessment	X
Expense Management	X
Customer Segmentation		X
Churn Prediction		X
Campaign Effectiveness		X
Market Basket Analysis		X
Demand Forecasting		X
Lead Scoring		X
Revenue Forecasting	X	X
Sales Pipeline Analysis		X
Employee Turnover Prediction					X
Talent Acquisition					X
Skill Gap Analysis					X
Workforce Planning					X
Inventory Optimization				X
Demand Planning				X
Supplier Risk Assessment			X	X
Logistics Optimization				X
Predictive Maintenance						X
Quality Control						X
Capacity Planning						X
Waste Reduction						X
System Outage Prediction							X
Resource Optimization							X
Security Threat Analysis							X

### Finance

1. **Cash Flow Forecasting**: Predict cash flow to optimize liquidity and financial planning.
2. **Fraud Detection**: Identify unusual patterns that may indicate fraudulent activities.
3. **Credit Risk Assessment**: Evaluate the creditworthiness of customers and predict potential defaults.
4. **Expense Management**: Analyze expense patterns to forecast future costs and optimize budgets.

### Marketing

1. **Customer Segmentation**: Identify distinct customer groups based on purchasing behaviors and preferences.
2. **Churn Prediction**: Predict which customers are likely to leave and design retention strategies.
3. **Campaign Effectiveness**: Analyze past campaign performances to predict the success of future initiatives.
4. **Market Basket Analysis**: Understand product associations and optimize cross-selling and up-selling strategies.

### Sales

1. **Demand Forecasting**: Predict future sales volumes to optimize inventory and supply chain operations.
2. **Lead Scoring**: Rank leads based on their likelihood to convert to closed deals.
3. **Revenue Forecasting**: Estimate future revenue based on historical data and market trends.
4. **Sales Pipeline Analysis**: Predict the closure of deals and optimize sales strategies.

### Human Resources

1. **Employee Turnover Prediction**: Forecast employee attrition and identify factors contributing to turnover.
2. **Talent Acquisition**: Predict the success of job candidates based on past hiring data.
3. **Skill Gap Analysis**: Identify gaps in employee skills and predict future training needs.
4. **Workforce Planning**: Model future workforce requirements based on business growth scenarios.

### Supply Chain

1. **Inventory Optimization**: Predict inventory levels to reduce carrying costs and prevent stockouts.
2. **Demand Planning**: Forecast demand fluctuations and align supply chain operations accordingly.
3. **Supplier Risk Assessment**: Evaluate risks associated with suppliers based on historical performance.
4. **Logistics Optimization**: Predict logistics bottlenecks and optimize transportation routes.

### Production

1. **Predictive Maintenance**: Forecast machinery breakdowns and plan maintenance activities proactively.
2. **Quality Control**: Predict defects and improve quality control processes.
3. **Capacity Planning**: Forecast production needs to optimize capacity utilization.
4. **Waste Reduction**: Identify patterns contributing to waste and optimize processes for sustainability.

### IT and Operations

1. **System Outage Prediction**: Predict and prevent IT system failures and downtimes.
2. **Resource Optimization**: Forecast IT resource needs to optimize infrastructure and reduce costs.
3. **Security Threat Analysis**: Predict and prevent potential cybersecurity threats.
4. **Process Automation**: Use predictive insights to enhance

Step-4 – Planning

Evaluate if planning capabilities are required; if yes, include SAP Analytics Cloud planning solutions with your data platform and business intelligence.

SAP Analytics Cloud Planning is a versatile tool that can be applied across various lines of business (LOBs) to facilitate better decision-making through integrated planning, analysis, and insights. Here are some common use cases for different lines of business:

Application Type	Finance	Sales, Service & Marketing	Procurement & Expense Management	Supply Chain	Human Resources	Operations	IT
Budgeting and Forecasting	X
Profitability and Cost Management	X
Cash Flow Management	X
Consolidation and Financial Close	X
Scenario Planning	X
Sales Forecasting and Planning		X
Territory and Quota Management		X
Revenue Planning		X
Customer and Product Profitability Analysis		X
Workforce Planning and Analytics					X
Headcount and Capacity Planning					X
Compensation Planning and Analysis					X
Talent Management and Retention					X
Diversity and Inclusion Analytics					X
Demand and Supply Planning						X
Inventory and Production Planning						X
Logistics and Distribution Planning						X
Marketing Spend and ROI Analysis		X
Campaign Planning and Effectiveness		X
Brand Performance and Competitive Analysis		X
Product Launch Planning		X
IT Budgeting and Cost Management							X
Project Portfolio Management							X
Infrastructure and Resource Planning							X
IT Service Performance Analysis							X
Spend Analysis and Procurement Planning			X
Supplier Performance and Risk Management			X
Contract Management and Compliance			X
Sourcing and Category Management			X
Cost Reduction Strategies			X
End-to-End Supply Chain Visibility				X
Demand Planning and Forecasting				X
Sales and Operations Planning (S&OP)				X
Supplier Collaboration and Risk Management				X

• **Finance:**

   - Financial Planning and Analysis (FP&A)

   - Budgeting and Forecasting

   - Profitability and Cost Management

   - Cash Flow Management

   - Consolidation and Financial Close

   - Scenario Planning

• **Sales:**

   - Sales Forecasting and Planning

   - Territory and Quota Management

   - Revenue Planning

   - Sales Performance Analysis

   - Customer and Product Profitability Analysis

• **Human Resources:**

   - Workforce Planning and Analytics

   - Headcount and Capacity Planning

   - Compensation Planning and Analysis

   - Talent Management and Retention

   - Diversity and Inclusion Analytics

• **Operations:**

   - Demand and Supply Planning

   - Inventory and Production Planning

   - Resource Optimization

   - Logistics and Distribution Planning

   - Quality Management and Monitoring

• **Marketing:**

   - Marketing Spend and ROI Analysis

   - Campaign Planning and Effectiveness

   - Customer Segmentation and Profiling

   - Brand Performance and Competitive Analysis

   - Product Launch Planning

• **IT:**

   - IT Budgeting and Cost Management

   - Project Portfolio Management

   - Infrastructure and Resource Planning

   - IT Service Performance Analysis

   - Cybersecurity and Risk Management

• **Procurement:**

   - Spend Analysis and Procurement Planning

   - Supplier Performance and Risk Management

   - Contract Management and Compliance

   - Sourcing and Category Management

   - Cost Reduction Strategies

• **Supply Chain:**

   - End-to-End Supply Chain Visibility

   - Demand Planning and Forecasting

   - Sales and Operations Planning (S&OP)

   - Supplier Collaboration and Risk Management

   - Inventory Optimization

These use cases highlight the flexibility of SAP Analytics Cloud Planning in addressing the specific needs and objectives of various departments within an organization, enabling integrated planning and informed decision-making across the enterprise.

Step-5 – Custom Reporting or Analytics

For needs not covered above, consider a mix of SAP Analytics Cloud, SAP Datasphere, SAP Data Intelligence, and other SAP BTP services.

SAP Analytics Cloud and Planning can be applied to a variety of complex and nuanced use cases across different lines of business (LOBs). While there are many common applications, here are some of the more intricate and less common use cases that leverage the full capability of SAP Analytics Cloud along with specific solutions:

Application Type	Finance	Sales, Service & Marketing	Procurement & Expense Management	Supply Chain	Human Resources	Operations	IT
Demand Sensing and Shaping				X
Integrated Business Planning				X
Talent Retention & Development Strategy					X
Scenario based Risk-Management	X
Strategic Workforce Planning linked with Financials	X				X
R&D Investment Valuation						X
Lifestyle analytics for Product Innovation						X
Predictive Maintenance with IOT Data						X
Production Yield Optimization						X
Carbon Footprint and Environmental Impact Analysis	X		X	X		X
Compliance and Risk Management Reporting	X					X
Omni-channel Strategy Optimization:		X
Personalized Promotions and Pricing Strategies		X
Infrastructure Lifecycle Management						X
Urban Mobility & Transportation Freecasting	X		X

• **Advanced Supply Chain Planning:**

   - **Demand Sensing and Shaping:** Use predictive analytics to enhance demand forecasting with real-time data inputs like social media trends, weather patterns, and economic indicators.

   - **Integrated Business Planning (IBP):** Complex scenarios where finance, sales, and operations planning are integrated to optimize inventory levels and production schedules.

• **Human Capital Analytics:**

   - **Talent Retention and Development Strategy:** By analyzing employee performance, engagement surveys, and external benchmark data, the tool can help predict turnover risk and formulate talent development strategies.

   - **Diversity and Inclusion Impact Analysis:** Assess the effectiveness of diversity initiatives on organizational performance through scenario modeling.

• **Complex Financial Planning and Analysis:**

   - **Scenario-based Risk Management:** Running multiple stress-test scenarios to assess financial risks under various economic conditions with real-time data adjustments.

   - **Strategic Workforce Planning linked with Financials:** Integration of workforce cost planning with long-term financial forecasts to assess the strategic implications of workforce decisions.

• **High-Tech and R&D Portfolio Optimization:**

   - **R&D Investment Valuation:** Simulate and forecast the potential return on investment for various R&D projects using historical data and predictive analytics.

   - **Lifecycle Analytics for Product Innovation:** Analyze the entire lifecycle from ideation to market penetration and end-of-life, optimizing resources and timing for product release.

• **Complex Manufacturing Process Analytics:**

   - **Predictive Maintenance with IoT Data:** Utilizing IoT sensor data to predict equipment failures and optimize maintenance schedules.

   - **Production Yield Optimization:** Analyzing the various parameters that impact production quality and yield, and implementing scenario planning to increase efficiency.

• **Cross-Industry Sustainability and Regulatory Reporting:**

   - **Carbon Footprint and Environmental Impact Analysis:** Complex modeling involving environmental data to forecast carbon footprint and align with sustainability targets.

   - **Compliance and Risk Management Reporting:** Dynamic modeling of regulatory changes and their impact on business operations and financial performance.

• **Retail and Consumer Behavior Analytics:**

   - **Omni-channel Strategy Optimization:** Evaluating customer touchpoints and optimizing marketing spend across various channels to maximize ROI.

   - **Personalized Promotions and Pricing Strategies:** Advanced analytics to tailor promotions at an individual customer level based on purchase history and predictive behavior analysis.

• **Smart Infrastructure and Urban Planning:**

   - **   :** Planning and analyzing the long-term sustainability and cost implications of infrastructure projects.

   - **Urban Mobility and Transportation Forecasting:** Visualizing and forecasting urban travel patterns to improve city planning and public transport efficiency.

These complex use cases require a deep integration of multiple data sources, sophisticated analytical models, and cross-functional collaboration, often involving advanced features of SAP Analytics Cloud like predictive analytics, machine learning, and integration with other SAP and non-SAP systems.

Conclusion

In conclusion, designing an optimal SAP Business Technology Platform (BTP) solution requires a thorough understanding of the platform’s diverse services and their application to specific business use-cases. By carefully evaluating whether an application is transactional or analytical, businesses can select the appropriate archetype—such as Application Modernization, Data Modernization, or AI & Generative AI—ensuring that the right SAP BTP services are deployed to meet their needs.

The platform offers a range of services, from SAP Analytics Cloud for reporting and planning to SAP Datasphere for data foundation and SAP HANA Cloud for predictive analytics and vector engine. By leveraging these tools, organizations can enhance their data processing capabilities, improve decision-making with advanced analytics, and foster innovation across their operations. Customization of reporting, data integration, and predictive capabilities enables businesses to drive more efficient, insightful, and forward-thinking outcomes, establishing a strong foundation for both present needs and future growth.

Thanks for your time in reading this blog, will see you in the next blog in this series SAP BTP from “Change Agent” to “Scale Agent”.