From Target Architecture to Design Blueprint for Finance
In my previous post, updated on September 1 2025, I outlined a modern finance target architecture using core ERP, reporting, a finance data hub, and BI/analytics. That post covered how these components fit together for compliance, reporting, and strategic insight.
This follow-up shows how to turn that architecture into a structured model that connects capabilities, information, organizational structure, technology, and user experiences to drive decisions and investments.
1. Scope and Outcomes
- Scope: Finance operations, financial close, consolidation, statutory reporting, data hub (integration + MDM), BI, and advanced analytics.
- Outcomes: Faster and auditable close, single source of truth, governed data products, predictive planning, and self-service insights.
2. Blueprint
Identity
- Purpose: Deliver compliant, timely, and explainable finance information
- Value: Reliable reporting, governed data, predictive insights
- Success Metrics: Close cycle time, report lead time, forecast accuracy, audit findings
Experiences
- CFO monthly close and board reporting
- Controller variance analysis and rolling forecast
- Business leader self-service KPI drill-downs
- Auditor traceability and lineage validation
Capabilities
- Record to Report (GL, AP, AR)
- Consolidation and Close
- Revenue Recognition and Allocation
- Planning, Budgeting, Forecasting
- Regulatory and Management Reporting
- Data Integration and Master Data Management
- BI Self-Service and Advanced Analytics
Organization
- Finance Operations
- Group Consolidation and Reporting
- FP&A
- Data Platform Team
- Information Governance
- Security and Risk
Information Assets
- Chart of Accounts, Journal, Ledger, Trial Balance
- Consolidated Financial Statements
- Entities, Cost Centers, Products, Projects
- KPIs and Metrics (margins, cash flow, working capital)
Technology Assets
- ERP / Accounting System
- Reporting and Close Tools
- Enterprise Data Hub (ETL/MDM, lineage, APIs)
- BI and Analytics Platform
3. Key Connections
Capability linked Information
| Capability | Information Objects |
|---|---|
| Record to Report | Journal, Ledger, Chart of Accounts |
| Consolidation and Close | Consolidation rules, Adjustments |
| Revenue Recognition | Contracts, Schedules |
| Planning and Forecasting | Plans, Versions, Assumptions |
| Reporting and Compliance | Statements, KPIs, Disclosures |
| Data Integration and MDM | Chart of Accounts, Entities, Product master |
| BI and Analytics | Metrics, Dimensional models |
Capability linked Technical Assets
| Capability | ERP | Reporting/Close | Data Hub | BI/Analytics |
|---|---|---|---|---|
| Record to Report | Yes | Ingest | ||
| Consolidation and Close | Yes | Management views | ||
| Revenue Recognition | Yes | Align | Margin views | |
| Planning and Forecasting | Yes | Drivers | Predictive | |
| Reporting and Compliance | Yes | Lineage | Distribution | |
| Data Integration and MDM | Yes | |||
| BI and Advanced Analytics | Feature | Yes |
4. Logical Target Architecture
Scope
Finance ERP and Close as systems of record, enterprise data hub for integration and MDM, governed semantic layer for access, BI and data science as consumers.
Component View
- Finance ERP
- GL, AP, AR, Fixed Assets, Cash
- Authoritative journal and subledger data
- Consolidation and Close
- Eliminations, intercompany, adjustments
- Planning, budgeting, forecasting
- Enterprise Data Hub
- Ingestion: CDC, batch, APIs, files
- Transformation and orchestration
- Data products publishing
- Master Data Management
- Chart of accounts, entities, cost centers, products
- Hierarchy and reference data stewardship
- Storage Zones
- Raw, standardized, curated, analytics
- Semantic Layer
- Governed metrics and dimensions
- SQL and API access
- BI and Reporting
- Dashboards, board packs, regulatory outputs
- Data Science and Feature Store
- Forecast features and model outputs
- Governance and Security
- Catalog, lineage, data quality, access control, audit
- Integration Interfaces
- Event streams, REST APIs, file exchange
Interaction Flow
+------------------+ +--------------------------------------------+
| Source Systems | | ERP (GL/AP/AR/FA) | Close/PBF | RefMDM |
+-----------------+ +---------------------+-------------+--------+
| CDC, batch, APIs, files | 🮧 Bidirectional Synchronize
v v |
+-----------------------------------------------------------------------+
| Enterprise Data Hub |
| ingest | transform | data products |
+---------------------+-------------------------------------------------+
| uses | publishes
v v
+------------------------+ +------------------------+
| Master Data Management | | Storage Zones |
| CoA, entities, hier. | | raw | std | curated |
+------------------------+ +------------------------+
|
| semantic contracts
v
+-----------------------+
| Semantic Layer |
| metrics, dimensions |
+-----------+-----------+
|
+---------------------+----------------------+
| |
v v
+------------------+ +------------------+
| BI and Reporting| | Data Science/ML |
| dashboards, packs| | feature store |
+------------------+ +------------------+
Crosscutting concerns
- Catalog and lineage
- Data quality and observability
- Security and access control
- Audit and retention
5. Design Principles
- ERP and Close are systems of record — analytics never writes back.
- One semantic layer for KPIs — multiple visualizations, one definition.
- Data as a product — owned, documented, with SLAs.
- Lineage and audit by design.
- APIs and event streams for integration.
- Zero Trust and role-based access.
- Cloud-agnostic where possible.
- Incremental rollout — coexistence with legacy systems.
6. Roadmap
Wave 1: Stabilize
- CDC from ERP to Data Hub
- Basic reporting pack from consolidated ledger
Wave 2: Unify and Govern
- Introduce MDM for chart of accounts and entities
- Replace ad-hoc reports with governed BI
Wave 3: Predict and Automate
- Rolling forecasts using machine learning
- Self-service data portal for finance users