SAP S/4HANA and Cloud ERP Strategy

Sessions in this track examine the strategic, commercial, and technical foundations required to define and launch SAP S/4HANA and cloud ERP migrations. 

Key learning objectives: 

• Evaluate greenfield, brownfield, and SDT approaches to determine migration strategy based on business need, technical complexity, and timeline 
• Select a licensing path across RISE with SAP, GROW with SAP, and standalone SAP S/4HANA, and model TCO to support investment and contracting decisions 
• Assess RISE with SAP contract structure and negotiate SAP, hyperscaler, and system integrator agreements 
• Build an implementation partner strategy by evaluating capability, delivery model, and industry experience, and establish governance and accountability to manage performance across the program 
• Use the integrated toolchain to support readiness assessment, process and landscape analysis, approach selection, and scope definition
• Map technical dependencies and define environment strategy, testing scope, and automation requirements to support migration sequencing 
• Define program structure and migration phasing — including workstream design, wave sequencing, and go-live scope — to manage delivery complexity and execution risk 
• Plan cutover and hypercare by identifying execution failure points and stress-testing delivery assumptions across timelines, staffing, and scope 
• Identify where AI applies and how it should influence scope, architecture, and investment decisions 

Data, Integration, and Process Alignment

This track covers migration readiness, integration redesign, process standardization, and cutover planning for SAP S/4HANA and cloud ERP programs.  

Key learning objectives: 

• Determine data migration scope, including what to migrate, archive, or rebuild, based on SAP S/4HANA data model changes, usage, quality, reporting dependencies, and business need  
• Establish data governance foundations, assess readiness, and assign master data ownership across domains and systems 
• Develop a data cleansing, enrichment, and validation approach to prevent downstream defects and reporting issues  
• Compare migration tools and services to select the right solutions and define the execution plan based on data volume, complexity, and program structure 
• Evaluate fit-to-standard adoption decisions through a clean core lens to understand how process customization choices drive data migration scope, integration requirements, and long-term upgrade risk
• Design the future integration landscape by selecting appropriate patterns to replace ECC interfaces and applying SAP Integration Suite capabilities 
• Define the cutover strategy, including mock migration runs, delta load sequencing, and system freeze planning 
• Understand how SAP Business Data Cloud and AI requirements inform data foundation and migration decisions

GRC, Security, and Controls

This track examines how to define identity, access, and control models that maintain security, enforce accountability, and support compliance across SAP and cloud environments. 

Key learning objectives: 

• Assign ownership for access, controls, and risk within shared responsibility models across SAP, hyperscalers, and system integrators 
• Redesign access model and architect identity and provisioning across SAP and non-SAP systems, including federation and lifecycle management 
• Establish segregation of duties aligned to redesigned processes and role structures 
• Embed controls into process design and system configuration  
• Mitigate risks introduced by integrations, APIs, automation, and distributed architectures 
• Build a continuous monitoring framework covering security events, controls exceptions, and user activity to detect risk and maintain ongoing compliance 
• Validate access controls, SoD rules, and security configurations to confirm they operate as designed before go-live 
• Plan for auditability and traceability across migration phases and into steady-state operations, including evidence collection, logging, and reporting requirements 

Designing for Change, Adoption, and Value

Sessions in this track unpack the decisions and mechanisms required to manage change, drive adoption, and connect program execution to expected outcomes including AI initiatives. 

Key learning objectives: 

• Establish program structure, roles, and responsibilities across IT, business, and system integrators to ensure alignment and accountability 
• Set decision ownership, governance, and escalation paths to prevent delays and misalignment 
• Control scope by establishing criteria for evaluating changes and preventing expansion, rework, and cost overruns 
• Sequence functionality and deployment phases to balance delivery speed, risk, and business impact 
• Identify and address organizational readiness gaps, including skills, capacity, and stakeholder alignment 
• Structure change management approach, including stakeholder engagement, communication, and change network design 
• Build training and enablement approach aligned to deployment phases, including role-based learning and adoption support 
• Establish adoption metrics and track expected value during the program to maintain alignment between scope, priorities, and business outcomes