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Topics

Explore critical topics shaping today’s SAP landscape—from digital transformation and cloud migration to cybersecurity and business intelligence. Each topic is curated to provide in-depth insights, best practices, and the latest trends that help SAP professionals lead with confidence.

Regions

Discover how SAP strategies and implementations vary across global markets. Our regional content brings localized insights, regulations, and case studies to help you navigate the unique demands of your geography.

Hot Topics

Dive into the most talked-about themes shaping the SAP ecosystem right now. From cross-industry innovations to region-spanning initiatives, explore curated collections that spotlight what’s trending and driving transformation across the SAP community.

SAP APO

SAP APO: Advanced Planning and Optimization for SAP Supply Chain Practitioners

SAP Advanced Planner and Optimizer (SAP APO) is a core component of SAP’s supply chain planning portfolio, helping organizations manage demand, production, inventory and logistics in an increasingly complex global environment. As companies navigate shifting consumer habits and mounting supply chain volatility, SAP APO provides the planning intelligence needed to align supply with demand. SAPinsider research on supply chain planning in the cloud shows that these planning capabilities have evolved from operational tools to strategic enablers of business agility and resilience. This page covers use cases, research and insights SAP practitioners need.

What Is SAP APO?

SAP APO is a supply chain planning solution that complements SAP ERP Central Component (ECC) logistics processes including procurement, production and sales. Built around four core modules, SAP APO addresses the end-to-end planning lifecycle: Demand Planning (DP) analyzes sales trends and seasonality; Supply Network Planning (SNP) manages inventory and safety stock; Production Planning and Detail Scheduling (PPDS) covers procurement proposals and resource management; and Global Available to Promise (GATP) optimizes customer demand fill rates by tracking product availability across the supply network.

What Use Cases Are Referenced?

Demand Sensing Improves Short-Term Demand Forecasting at Arla Foods

Arla Foods, the world’s fourth largest dairy company, deployed SAP Integrated Business Planning demand sensing, which uses machine learning to match forecasts to real-time demand patterns. The implementation improved forecast accuracy by 5.5% in Denmark and 2.4% in the UK, delivering higher order fulfillment rates and reduced inventory costs.

Enhancing Supply Chain Efficiency With SAP IBP and CloudPaths

A phased SAP IBP implementation highlights how organizations can overcome fragmented data and skill gaps in supply chain planning. SAPinsider research found that poor integration capabilities dropped from 47% to 27% as a top inhibiting factor between 2023 and 2024, reflecting meaningful progress in the SAP IBP ecosystem.

Leverage SAP S/4HANA PPDS Block Planning Functionality to Optimize Production Schedule

SAP S/4HANA Production Planning and Detail Scheduling block planning functionality enables manufacturers to pre-assign resource capacity to product groups with similar characteristics. The approach reduces changeover time and improves production yield while ensuring high-priority customer demand is fulfilled first across complex multi-SKU production environments.

How to Set Up Demand Planning in SAP Advanced Planning and Optimization

This guide covers the full configuration lifecycle for SAP APO demand planning, from time series and planning books to statistical forecasting and demand plan release to SAP ECC. Practitioners learn configuration steps, transaction codes, performance optimization tips and troubleshooting guidance for implementing a production-ready demand planning platform.

Supply Chain Leaders Balancing AI Ambition, Execution Discipline

Organizations integrating SAP Business Network into their supply chain strategies are reporting measurable outcomes. Grainger, CDW and Graybar achieved 20% faster go-to-market timelines, 37% higher customer satisfaction and 50% faster invoice submission by connecting procurement and planning systems through a unified network. More than half the data driving intelligent supply chains exists outside organizational boundaries.

What SAPinsider Research Supports This Topic?

Supply Chain Planning in the Cloud Benchmark Research

Based on a survey of 106 SAPinsider community members, this benchmark report found that supply chain planning capabilities have evolved from operational tools into strategic enablers of business agility and resilience. The report examines top challenges, strategies and the benefits of transitioning on-premise planning solutions to the cloud.

SAP S/4HANA Migration 2025

Surveying 170 SAPinsider community members, the SAP S/4HANA Migration 2025 report found that 32% of organizations have already transitioned to SAP S/4HANA, up 10 percentage points from 2024, while 27% are in active implementation, marking the most concentrated migration momentum on record.

ERP Migration and Transformation 2026

The SAPinsider ERP Migration and Transformation 2026 report found that 55% of organizations have deployed SAP S/4HANA or SAP S/4HANA Cloud, while 48% cite SAP AI announcements as the top external factor influencing their ERP and supply chain transformation strategies.

See Latest Related Content Below

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SAP Security Patch Day March 2026: Quotation, Portal, and Supply Chain VulnerabilitiesSAP’s March 2026 Security Patch Day delivered 15 new Security Notes, including critical vulnerabilities affecting SAP Quotation Management Insurance, NetWeaver Enterprise Portal, and supply chain systems. The release highlights recurring authorization and injection risks across complex SAP landscapes.
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Enterprise-Class Demand Planning at Agilent TechnologiesFor Agilent Technologies, a manufacturer of analytical instruments for the life science and laboratories sector, growth has been dramatic over recent years, including a number of acquisitions. Such growth has caused the company’s pathology division to experience a rapid expansion of sales, but also revealed that the division had outgrown its demand planning practices, which were largely manual and based on desktop productivity software, instead of a true enterprise solution. Driven by a need to better support its expanding demand pipeline, Agilent's pathology division determined it needed to implement a solution with greater ability to scale and more flexible statistical modeling. By increasing the efficiency and sophistication of its demand planning and, therefore forecasting, Agilent targeted optimizing inventories, supply readiness, and capacity planning. Distinguishing between one-time events versus long-term trends was identified as a key forecasting capability that needed improvement. By enhancing the statistical methods to generate forecasts, Agilent planned to tune its production and distribution pipelines to be as proactive and efficient as possible. Read this article and learn: - How demand planners can fine-tune their forecasts through their knowledge of products and markets; - How Agilent leveraged its existing GIB investment to make a strong technology and business case for adopting GIB Forecast for demand planning; - The outcome of implementing GIB Forecasting into Agilent's pathology division and what it achieved; - How the GIB implementation enabled a self-service modality and greater process control by Agilent's users.
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Balancing supply and demand
How to Setup Demand Planning in SAP Advanced Planning and OptimizationSAP Advanced Planning and Optimization, demand planning allows a business to perform forecasting of their materials while considering all the factors that affect the demand. Demand planning is periodic and contains multi-step processes such as data gathering, statistical analysis, reviewing market intelligence reports, and performing adjustments against budgeted forecast to drive material requirements planning. SAP Advanced Planning and Optimization, demand planning is designed as a platform so it must be tailored to an organization’s product types and nature of their business with various key figures, characteristics, data aggregations or disaggregation factors, planning object structures, planning areas, planning books, macros and data views to execute the process. This article will provide steps for implementing the solution, along with reasoning behind the configurations, prerequisites, navigation with transactions codes, relevant SAP notes, and tips and tricks for troubleshooting issues during implementation. In this article you will learn: - The essential steps of SAP demand planning configurations including time series, planning books, statistical forecasting, background job set up, and demand plan release to ECC; - Explanation of each configuration step involved with navigation path, transaction codes, and tables; and - Tips and tricks on configurations, performance optimization, and error resolutions.
Demand Sensing Improves Short-Term Demand Forecasting at Arla Foods

Most organizations today are somewhere along the journey toward becoming a digital business, with meeting high expectations for the customer experience a central driver. One of the keys to creating an exceptional experience is the ability to access data in back-end systems in real time, which means that robust integration is critical. This article introduces a new, standardized approach to integration that can help you accelerate your digital transformation and ensure a seamless customer experience.

A holistic integration approach is a key prerequisite for organizations pursuing a digital path for their business. This article introduces SAP’s Integration Solution Advisory Methodology (ISA-M), which helps organizations shape their integration strategy — using predefined integration patterns for processes-, data-, user-, and Internet of Things-centric integration scenarios — and become an Intelligent Enterprise.

Secure connections between applications is critical in modern, hyperconnected landscapes. The SAP Cloud Platform Credential Store service enables highly secure connections between applications in cloud-based landscapes by storing the required credentials and making them available to applications via a REST API. This article provides an overview of the key concepts and configuration tasks that are required to use this service in SAP Cloud Platform landscapes.

Organizations and citizens worldwide have seen the results of the global plastic crisis. In response, policymakers, society, and leading companies, such as SAP, are coming together to work on solutions — by avoiding single-use plastics, better managing and recycling the plastic waste stream, and creating what’s called a “circular economy.” SAP specifically is helping its customers redesign global value networks toward more circular business models through efforts such as the Circular Economy 2030 and SAP Leonardo Plastics challenges and a number of circular uses cases – around secondary materials marketplace, extended producer responsibility, waste insights, and citizen engagement – that are already at work across various industries. Learn about these and other ways that SAP customers can adopt more sustainable business practices, which could unlock $4.5 trillion in growth by turning waste into wealth.


Organizations and citizens worldwide have seen the results of the global plastic crisis. In response, policymakers, society, and leading companies, such as SAP, are coming together to work on solutions — by avoiding single-use plastics, better managing and recycling the plastic waste stream, and creating what’s called a “circular economy.” SAP specifically is helping its customers redesign global value networks toward more circular business models through efforts such as the Circular Economy 2030 and SAP Leonardo Plastics challenges and a number of circular uses cases – around secondary materials marketplace, extended producer responsibility, waste insights, and citizen engagement – that are already at work across various industries. Learn about these and other ways that SAP customers can adopt more sustainable business practices, which could unlock $4.5 trillion in growth by turning waste into wealth.


Discover how SAP customers can improve short-term forecast and delivery accuracy using SAP Integrated Business Planning demand sensing, which uses machine learning and pattern recognition to match and balance forecasts to patterns in demand with inputs from historical and future sales orders, historical shipments, promotions, weather forecasts, and social media sentiment. With this functionality, companies can achieve higher order fulfillment rates and reduced inventory costs with more inventory turns. Learn how the Arla Foods, the world’s fourth largest dairy company, deployed the demand sensing functionality of SAP Integrated Business Planning and improved its forecast accuracy by 5.5% in Denmark and 2.4% in the UK.


Logistics and SCM: Case study: Building a stable supply plan — See how Hollister reengineered a capacity planning solution without an engine and still managed to drive successLearn how the Hollister expanded the standard capacity-leveling algorithm to include additional parameter checks in its system. SCM2017_Syed_Grace_Casestudybuildingastable Azeemullah Syed If you have comments about this article or publication, or would like to submit an article idea, please contact the editor. Steve Grace If you have comments about this article or publication, or would like […]
Not Your Same Old Advanced Planning System Implementation!Panelists: Robert Birdsall and Ryan Rickard, SCMO2 Date: September 6 Sponsor: IBP Bootcamp and SCM 2018 Gone are the days of engaging a System Integrator and waiting nine to twelve months for the first in a series of rollouts. With today’s cloud platform, and specifically SAP Integrated Business Planning (SAP IBP), the platform is upgraded […]
Carry Out Planning for Production Replenishment Using the Supply-to-Production ProcessLearn the configuration, master data setup, and process flow for the supply-to-production process to replenish the components from a warehouse to production supply areas. Key Concept The supply-to-production process is used to organize the physical replenishment of components for production. It is generally used in the short-term horizon and uses a control cycle and supply […]

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