LogoSACplans
Technical Reference

SAC Planning Technical Architecture

Reference architecture for SAP Analytics Cloud Planning deployments — covering system integration, planning data flow, model layers, and the connection between S/4HANA, SAP Datasphere, and SAC.

Reference Architecture

SAC Planning Architecture Layers

The six architectural layers of a SAC Planning deployment — from source systems through to planning governance.

01Source Systems
S/4HANA (Finance)S/4HANA (Sales)S/4HANA (MM/PP)Non-SAP ERPExternal Data Sources
02Data Foundation Layer
SAP Datasphere — Business LayerSAP Datasphere — Replication LayerData Quality & Validation
03SAC Planning Models
Financial Planning ModelSales Planning ModelSupply Chain ModelDriver / Allocation Models
04Planning Logic Engine
Data ActionsAdvanced Formula ScriptsAllocation EngineScenario Logic
05Planning Experience
Planning StoriesInput FormsVariance DashboardsWorkflow Tasks
06Governance & Security
Role-Based AccessVersion ManagementAudit TrailPlanning Calendars
▼
Data flows from source systems downward through each layer
Integration Reference

Integration Patterns for SAC Planning

Integration design is one of the most consequential architectural decisions in a SAC Planning program. The right pattern depends on data volume, transformation complexity, and latency requirements.

Source
S/4HANA Finance
Live Connection / Import
▶
Target
SAC Planning
Data Types
GL ActualsCost Centre DataProfit Centre DataCompany Code Structure
Architecture Notes

Live connection for real-time actuals; import for large datasets. Consider Datasphere for transformation.

Source
S/4HANA Sales & Distribution
Datasphere → SAC
▶
Target
SAC Planning
Data Types
Sales OrdersBilling DataCustomer MasterMaterial Master
Architecture Notes

Recommended to route through Datasphere for harmonisation with financial planning dimensions.

Source
S/4HANA Materials Management
Datasphere → SAC
▶
Target
SAC Planning
Data Types
Purchase OrdersInventory LevelsVendor DataMaterial Movements
Architecture Notes

Supply chain planning data typically requires significant transformation before use in planning models.

Source
SAP Datasphere
Native Integration
▶
Target
SAC Planning
Data Types
Harmonised ActualsMaster DataHierarchiesReference Data
Architecture Notes

Primary recommended integration pattern for complex data landscapes. Provides transformation, harmonisation, and data quality management.

Source
Non-SAP / External Systems
Flat File / API
▶
Target
SAC Planning
Data Types
Workforce Data (HR)Market DataCRM PipelineCommodity Prices
Architecture Notes

Flat file integration via SAC import jobs. API integration via OData for automated pipelines.

End-to-End Flow

SAC Planning Data Flow

From source system extraction through to approved plan reporting — the six stages of a SAC Planning data flow.

01

Source Data Extraction

Actuals, master data, and hierarchies extracted from source systems on defined schedules.

S/4HANA GLSD/MM ModulesHR SystemsCRM / External
02

Data Foundation (Datasphere)

Data harmonised, validated, and structured to match SAC Planning dimension design.

Replication LayerTransformation LayerBusiness LayerData Quality
03

SAC Planning Model Load

Approved data loaded into SAC Planning models. Versioned as Actual, locked for planning reference.

Dimension MembersHierarchy SyncActuals LoadReference Data
04

Planning Input & Calculation

Planners enter assumptions. Data actions and script logic derive the plan from drivers.

Planner InputData ActionsDriver FormulasAllocations
05

Review & Approval

Submitted plans reviewed against targets. Approved plans locked and published.

Workflow TasksVariance ReviewApproval Sign-offVersion Lock
06

Reporting & Distribution

Approved plan data available for reporting, comparison to actuals, and operational use.

Planning StoriesExecutive DashboardsVariance ReportsExport / Write-back
Model Architecture

Planning Model Layer Design

A well-designed SAC Planning deployment separates models by function — avoiding the monolithic model anti-pattern that causes performance and maintenance problems.

01
Planning Input Models

Where planners enter data — typically one per planning domain.

02
Driver / Reference Models

Store planning assumptions and drivers referenced by calculation logic.

03
Allocation Models

Dedicated models for cost allocation calculations — separate from input models.

04
Reporting / Output Models

Aggregated planning output optimised for reporting and dashboard performance.

Key Design Principle

Separate planning input models from reporting models. Input models are optimised for write performance. Reporting models are optimised for read and aggregation performance. Allocation models are isolated to prevent calculation logic from polluting input models.

Recommended Integration Architecture
Source
S/4HANA
  • ·Finance (FI/CO)
  • ·Sales (SD)
  • ·Procurement (MM)
  • ·HR / Payroll
▼
Foundation
SAP Datasphere
  • ·Data Replication
  • ·Transformation
  • ·Harmonisation
  • ·Data Quality
▼
Planning
SAC Planning
  • ·Planning Models
  • ·Data Actions
  • ·Planning Stories
  • ·Governance

Recommended pattern: Route all source system data through SAP Datasphere before loading to SAC Planning models. This provides a clean separation between integration complexity and planning model design, and enables data quality validation before data enters the planning environment.

Advisory

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