Executive Summary

Data Mesh is a decentralized way of managing data. It treats data as a product and makes domains responsible for their own data. Combined with IFS Cloud’s project methodology, it creates a framework for strong governance and scalable data management across business domains.

This approach replaces centralized control with a federated model. Business domains own and manage their data products while following shared governance standards.

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Core Principles for IFS Cloud

Domain ownership

• Map IFS functional modules to business domains during project scoping
• Set boundaries by process areas such as Supply Chain, Finance, Projects, HR
• Assign each domain responsibility for its own data products
• Align enterprise structure with IFS Cloud domain design

Data as a product

• Design products with clear service levels and quality measures
• Products must be discoverable in the IFS data catalog
• Expose them through REST APIs and OData
• Define validation rules and full metadata
• Document specifications in the Book of Rules
• Set quality metrics in the Data Tracker
• Align SLAs with IFS Cloud capabilities

Self-serve platform

• Use IFS Cloud’s built-in integration and migration tools
• IFS Connect for services and protocols
• REST API with OData for direct access
• Data Migration Manager and Excel Add-in for processing
• Support data sharing across domains with IFS Connect

Federated governance

• Apply governance through the IFS project organization
• Define rules in the Enterprise Book of Rules
• Use IFS Cloud security and access controls for compliance

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Implementation Phases

Phase 0: Define Project and Scope

• Mapping IFS Functional Modules to Business Domains
• Define governance structure
• Set data product vision

Phase 1: Initiate Project

• Form a Data Governance Committee with domain reps
• Create the Enterprise Book of Rules
• Define ownership and quality standards
• Deliverables: Domain Architecture, Governance Charter, Draft Catalog

Phase 2: Confirm Prototype

• Validate product definitions in prototypes
• Confirm data sharing agreements
• Establish lineage and metadata processes
• Test governance model

Phase 3: Establish Solution

• Implement full product specs
• Deploy self-service tools
• Automate governance policies
• Configure catalog for discovery
• Set up APIs, dashboards, and security

Phase 4: Implement Solution

• Train teams on data product ownership
• Test end-to-end workflows
• Validate compliance and readiness

Phase 5: Go Live

• Activate production data products
• Monitor performance and governance
• Set up lifecycle management

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Data Governance Framework

Committee

• Executive sponsor (often CDO)
• Domain data product owners
• Technical platform team
• Data stewards

Processes

• Automated validation and monitoring dashboards
• Exception handling and quality reporting
• Federated access controls, tagging, and audits

Technology

• IFS Connect for integration
• REST API with OData
• Built-in migration and security tools
• Data catalog, pipeline automation, quality monitoring, and metadata management

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Roadmap

Months 1–3

• Build governance structure
• Define domains
• Set up initial framework
• Train core team

Months 4–8

• Deploy 1–2 pilot products
• Enable self-service
• Validate governance and architecture

Months 9–12

• Expand to all domains
• Add advanced analytics
• Optimize governance and performance
• Build continuous improvement loop

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Success Measures

Data Products

• Time to release new products
• Adoption rate
• Quality scores
• User satisfaction

Governance

• Compliance rate
• Security incidents
• Process efficiency
• Domain autonomy

Business Value

• Faster decisions
• Lower data management costs
• Better data access
• Higher analytics adoption

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Risks and Mitigation

Technical

• Integration complexity → phased rollout and proofs of concept
• Performance issues → good architecture and monitoring
• Security gaps → federated model and regular audits

Organizational

• Resistance to change → training and change management
• Lack of resources → proper staffing and external support
• Weak governance adoption → executive sponsorship and clear roles

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Conclusion

Using Data Mesh within IFS Cloud projects creates a modern data model that balances domain ownership with enterprise governance. It makes use of IFS Cloud’s native tools while building a federated architecture for agility and decision-making.

Success depends on strong leadership, change management, and a phased rollout. By combining IFS methodology with Data Mesh, organizations can deliver a working ERP and a scalable data foundation for future growth.

In modern enterprise ERP implementations such as IFS Cloud, accurately mapping functional modules to an organization's business domains is foundational to project success. This is especially vital when implementing advanced architectural paradigms like Data Mesh, which emphasize decentralized data ownership aligned with business domains. The following outlines a structured approach to achieve this alignment during project scoping, highlights key business domains typically involved in IFS mapping, and proposes essential tools to facilitate the implementation.

Structured Mapping Approach in IFS Cloud Implementation

The IFS Implementation Methodology provides a comprehensive framework for projecting and detailing the scope of IFS functional modules vis-à-vis business domains through distinct project phases:

• Initiate Project Phase: This phase initiates collaboration between the IFS delivery team and the customer to define high-level business domains, company structure, and strategic objectives. Key business processes and organizational models are mapped into the IFS Scope Tool, aligning business domains with IFS application modules. Foundational governance and operational rules are documented in the Enterprise Book of Rules, shaping how modules correspond to specific domains.
• Confirm Prototype Phase: A prototype covering 40 to 50 main end-to-end business processes is developed, demonstrating how selected IFS modules operate within the customer's context. Through collaborative workshops, prototype scope is refined, ensuring close alignment of modules with business processes and domain requirements. This phase emphasizes minimizing customizations while maximizing process adherence to IFS best practices.
• Establish Solution Phase: This phase expands on the prototype, incorporating remaining scenarios to build a full solution. Detailed training, testing, and integration ensure the mapped modules comprehensively support the business domains. Detailed documentation and specifications for configurations, reports, interfaces, and modifications (CRIM objects) are prepared.
• Data Mesh Application: Aligned with this modular mapping approach, Data Mesh principles facilitate decentralized data ownership across business domains. Each domain associated with specific IFS modules manages its data autonomously but interoperates within an overarching unified IFS solution, fostering agility and governance.

Central to this approach are the IFS Scope Tool - for capturing and refining scope at multiple levels - and the Enterprise Book of Rules, which codifies business operations and governance as prerequisites for mapping. The Solution Architect plays a crucial role in orchestrating solution design, ensuring modules effectively map to business processes and domains, and managing scope control throughout.

Key Business Domains for IFS Functional Mapping

Enterprises generally recognize a set of core business domains which serve as the natural structuring units for mapping IFS modules, including:

• Finance and Accounting: General ledger, accounts payable/receivable, financial reporting, budgeting, asset and cash management, and consolidation.
• Procurement and Supply Chain: Purchasing, supplier relationship management, demand planning, inventory management, warehousing, logistics, and supply chain operations.
• Manufacturing and Production: Discrete and batch manufacturing, production planning, shop floor control, quality assurance, and maintenance management.
• Project and Contract Management: Project planning, scheduling, cost and resource control, and contract oversight.
• Service and Maintenance: Field service management, service contracts, warranty management, and customer service workflows.
• Human Resources and Payroll: Employee records, payroll processing, competency management, and organizational structuring.
• Quality, Health, Safety, and Environment (QHSE): Compliance tracking, incident management, risk assessments, and auditing.
• Customer Relationship Management (CRM): Sales processes, marketing, customer interactions, and service delivery.
• Document Management and Collaboration: Document control, workflow processes, and collaborative tools integral to business operations.
• Data and Analytics: Master data management, data governance, and cross-domain reporting, enhanced by Data Mesh to assign clear data ownership at the domain level.

Effectively mapping IFS modules to these domains enables enterprises to define clear role responsibilities, maintain data stewardship, and optimize processes holistically.

Recommended Tools for Mapping and Implementation

To execute this structured approach effectively, the following tools within the IFS ecosystem and complementary solutions should be leveraged:

• IFS Scope Tool: Central for documenting, managing, and refining the functional scope against the customer's business domains. It allows detailed process and scenario modeling, documentation generation (Book of Rules, Main Process documents), and supports change and scope management workflows.
• Enterprise Book of Rules: Captures governance, organizational structure, business rules, and operational prerequisites that influence solution mapping. It acts as a master document referenced throughout the implementation project.
• CRIM Tracking Tools: For managing Configurations, Reports, Interfaces, and Modifications, ensuring that all tailored elements align with business domains and project scope. This promotes traceability and impact analysis.
• IFS Project Management Tools (Project Tracker, Project Calculator): These aid in scheduling, resource allocation, milestone tracking, and risk management aligned with scoping and domain mapping activities.
• Workshop and Collaboration Platforms: Tools integrated within IFS or external collaboration software should be used for conducting workshops, gathering data, and aligning stakeholders. Effective facilitation of workshops during the Initiate and Confirm Prototype phases is critical for domain definition and validation.
• Data Migration Toolkit: Supports data profiling, cleansing, migration planning, and execution aligned to domain datasets. This tool is essential to address the data domains in the context of Data Mesh, ensuring ownership and quality.
• Testing and Training Tools (Test Tracker, ClickLearn): These ensure that solution scenarios per business domain are verified and that comprehensive end-user training is provided aligned with the mapped processes.
• Data Mesh-Specific Tools (if integrated): Tools that support federated data governance, domain-oriented data pipelines, and self-service data infrastructure should be aligned with IFS data management practices to enable autonomous data domain ownership while maintaining integration.
• Solution Architect Dashboards and Reporting: Customized dashboards offer visual oversight of domain coverage, module usage, training status, and open issues, helping Solution Architects and project leadership maintain control and insight.

Conclusion

Mapping IFS functional modules to business domains during an IFS Cloud implementation with Data Mesh integration involves a systematic methodology supported by a suite of powerful tools. These tools facilitate detailed scope capture, domain-specific workshops, traceability of customizations, project and risk management, and data governance. Leveraging these enables solution architects and project teams to deliver cohesive, modular solutions aligned perfectly with business domains, empowering decentralized data ownership through Data Mesh principles and delivering scalable, agile enterprise value.

References: IFS Implementation Methodology, Scope Tool, Enterprise Book of Rules, Solution Architect guidelines, IFS PM Handbook for Partners, Data Mesh frameworks

A governance structure gives clarity around who does what in an IFS Cloud Data Mesh setup. It establishes who makes decisions, who is responsible for specific data, and which rules everyone needs to follow. This structure helps companies handle complex data projects by making sure work doesn’t fall through the cracks and everyone follows the same standards.¹²

What Governance Structure Means in IFS Cloud Data Mesh

Governance in IFS Cloud projects organizes oversight bodies such as steering committees and assigns roles such as domain owners and compliance stewards. It lays out processes for making decisions, handling problems, and keeping track of progress. This is important since authority is shared between central teams and business units. The goal is to give teams freedom to manage their data without losing sight of company rules or security.³

Using Data Mesh in IFS Cloud means moving from a fully centralized model to something more shared. Business teams are in charge of their data, but still follow company-wide rules. Standards like data contracts and compliance policies tie everything together.³⁴

How IFS Cloud Methodology Uses Governance

IFS Cloud projects have several stages. Each stage handles governance differently.

• During scoping, solution architects and stakeholders decide who owns each piece of data and set the first set of rules.¹
• Committees make sure data processes and contracts meet expectations and legal requirements as the solution is established.¹
• When moving to implementation and go-live, governance processes ensure ongoing quality, compliance, and change management as teams deploy and run the system.¹

Key Parts of the Governance Structure

• Committees give direction and keep business units in sync.¹
• Processes and rules, found in core documents, guide risk management and how to handle changes.¹
• Technology tools like the IFS Scope Tool and Data Catalog make sure rules are actually followed and can be checked anytime.¹

How Federated Governance Helps Scale Data Management

Federated governance lets business units work independently while following central rules. Each team manages its own data using the standards everyone agrees to, and central teams handle things like compliance and security.

• Business units adjust how they manage data based on their needs, which speeds up decisions.⁵¹
• Company-wide standards for things like security and compliance apply to all data, no matter where it comes from.²
• Shared tools help everyone follow the rules automatically. Things like data catalogs and APIs keep things working the same way everywhere.²

Teams move faster, stay compliant, and work better together. They can share and reuse data without much confusion or extra work. This approach gives companies the control they need without blocking innovation.⁶⁵¹

Governance Roles in Data Mesh

Success depends on having the right people in the right roles.

• Executive sponsors such as the CDO or CIO make sure the company supports the effort and provides resources.¹
• Data governance managers or a central council set company standards and keep everyone aligned.⁷⁸
• Domain data owners are responsible for the quality, security, and compliance of their own data.⁹
• Data product managers or owners look after the design and improvement of specific data products.⁹
• Domain data stewards keep daily operations running smoothly. They handle cataloging and ensure data is well documented and accessible.⁹¹
• Technical platform teams supply the tools and automation that help every group stick to standards.¹
• A federated governance committee helps align practices and resolve issues across teams.¹⁰

In IFS Cloud Data Mesh, these roles and processes work together. They give business teams enough control to move fast but make sure important rules are never ignored. This balance supports both strong compliance and quick innovation as a company grows.²⁹¹

Let me know if anything here is unclear or if you want details on specific roles or processes.