From Blueprint to Execution: Making Finance Target Architecture Real
In the first post, I outlined a target architecture for finance — built on ERP, reporting, a finance data hub, and BI. In the second post, I explored how to translate that architecture into a design blueprint with capabilities, intersections, and logical components.
This third and final post looks at the next step: execution. How do organizations move from blueprint to reality?
1. Why Execution Is Hard
Designing a target architecture is inspiring, but execution is where most initiatives stall. Common challenges include:
- Legacy systems: Difficult integrations, slow performance, and fragmented data.
- Siloed ownership: Finance, IT, and business units may not share the same priorities.
- Data quality gaps: Reporting suffers if master data and hierarchies are not aligned.
- Change management: New processes and tools require adoption across the business.
2. Governance and Ownership
Execution starts with clear ownership:
- Finance owns processes and definitions (chart of accounts, KPIs, reporting rules).
- IT owns platforms and integrations.
- Data governance ensures quality, lineage, and access control.
Without this accountability, even the best architecture risks becoming shelfware.
3. Incremental Roadmap
Big-bang transformations rarely succeed. Instead, execution should follow a phased roadmap:
- Phase 1: Stabilize
- Identify system of record (ERP, Close).
- Set up data ingestion and initial reporting packs.
- Phase 2: Unify and Govern
- Introduce master data management.
- Replace ad-hoc reporting with governed BI.
- Phase 3: Predict and Automate
- Add forecasting and scenario planning with ML.
- Provide self-service data products for finance users.
This approach ensures visible value at every step.
4. Continuous Improvement
Target architectures are not static. Continuous improvement means:
- Regularly reviewing KPIs and data quality metrics.
- Adjusting the semantic layer as business evolves.
- Expanding data hub integrations to new domains (HR, supply chain, sales).
- Embracing new analytics capabilities as they mature.
5. Lessons Learned
From working with finance and architecture teams, three lessons stand out:
- Start with outcomes. Technology choices matter less than delivering faster closes, better forecasts, and trusted reports.
- Invest in data governance early. Without consistent master data, BI and analytics cannot deliver on their promise.
- Adoption beats perfection. It is better to deliver a good-enough semantic layer with clear KPIs than to aim for a perfect model.
6. Conclusion
Over this series, we’ve gone from:
- A target architecture for finance (ERP + reporting + data hub + BI).
- To a design blueprint mapping capabilities, information, and technology.
- And now to execution strategies that make the vision real.