Author: Miki Sato is a Product Manager, Product Management Team (Data Management) at Anaplan.
Many companies are investing in Enterprise Planning, AI, and BI to improve forecasting and decision-making.
Yet across industries, business users still ask the same question:
“If we have trusted data, why can’t we use it in planning?”
Because
“trusted” and “usable” are NOT the same.
In reality, planning teams often struggle with:
- “Customer ID” formats that differ by region
- Product hierarchies that don’t match sales views
- Supplier data that's inconsistent across systems
- External data that arrives in the wrong shape, at the wrong time
These aren’t just integration problems. They reflect a deeper issue: The data is mastered — but not aligned for planning. Governance makes it trustworthy; context makes it useful. Until both exist, planners will keep staring at “clean” data that can’t answer their most urgent questions.
Why traditional MDM isn’t enough
However, more than 75% of MDM programs fail to meet business expectations through 2025, largely due to weak alignment with business needs (via Dataversity, Common Master Data Management (MDM) Pitfalls, July 2025) .
McKinsey also reports that 82% of business users spend one or more days per week managing data quality issues, creating operational drag and lost productivity (McKinsey, Elevating Master Data Management in an Organization, 2024).
This doesn’t mean MDM is broken — it just means it’s not optimized for planning. Most MDM systems are designed for enterprise-wide consistency, but they often lack the flexibility to deliver data in the structure, granularity, and timing that planning models require.
This creates a disconnect between strategic goals and the day-to-day needs of planning teams.
Why planning needs a different kind of MDM
Planning teams need more than clean, consistent data. They need:
- Scenario-specific hierarchies
- Custom attributes and calculated fields
- Data structured around planning logic
- Fast delivery to multiple models — with traceability
Traditional MDM wasn’t built for this. That’s where Anaplan Data Orchestrator (ADO) comes in.
What makes Anaplan Data Orchestrator different
Anaplan Data Orchestrator (ADO) is not a traditional MDM — but it solves the last-mile problems that planning teams care about most.
It transforms data from upstream systems (ERP, MDM, CRM, etc.) into formats that reflect how planning works:
- Planning logic, not just data correctness: Define hierarchies, levels, and custom fields the way planners use them — no reshaping needed inside the model.
- Shared definitions across systems: Align customers, products, and other entities without relying on manual mapping.
- Reusable transformation logic: Automate delivery to multiple models without copy-paste or redundant scripting.
- Visual monitoring and lineage: Trace how data flows from source to model — step-by-step, no black boxes.
See how ADO solves last-mile transformation challenges — aligning hierarchies, attributes, and relationships the way planners need.
Instead of embedding transformation logic inside planning models — like traditional data hubs — ADO separates it into a governed orchestration layer. This improves transparency, performance, and reusability across models and teams.
With ADO, teams can:
- Organize hierarchies and levels to reflect planning logic — no need to reshape data inside models
- Standardize entity definitions across systems — ensuring products, customers, and other lists are consistently understood
- Define calculated or planning-specific fields directly in ADO’s data catalog — without changing source systems
- Automate delivery to multiple models using shared, reusable transformation logic
- Trace data lineage — visually monitor pipeline execution and transformation steps from source to model
Figure 1. Transformation View — Define business logic visually in ADO
Figure 2. Map View: Data lineage showing from source to model with full traceability
Figure 3. Create, monitor, and act on data pipelines in ADO’s link view
Where ADO is headed next
ADO is purpose-built for planning — not intended to replace full-scale MDM platforms.
It doesn’t create golden records or perform fuzzy matching, and that’s by design.
Instead, it focuses on transforming governed data into planning-ready structures that are consistent, traceable, and aligned with how planners actually work.
Looking ahead, ADO will continue to evolve — enabling stronger governance, clearer data trust, and more control at the planning layer. It is becoming more than a data pipeline, it’s emerging as the control tower for planning data across the enterprise.
Ready to start?
If you're still relying on traditional Data Hub models, or struggling to connect upstream MDM with planning needs:
- Try aligning one product hierarchy.
- Automate delivery to one model.
- Start small — and scale fast.
Learn more
Featured research and industry insights:
Anaplan product documentation:
- ADO Overview & Use Cases – Anaplan Data Orchestrator (Platform Page)
Highlights ADO’s key benefits—no-code connectors, workflow automation, lineage tracking, and how it accelerates scenario planning.
- Technical Documentation (Anapedia) – Anaplan Data Orchestrator Documentation
Provides in-depth guidance—getting started, managing data integrations, transformation views, data lineage mapping, connections, and orchestrating workflow.
Questions? Leave a comment!
