Concept card

SAC Planning Models

As of 2026-09-27

Edited by Cédric Mary, sole editor and publication director — 27 years in the SAP ecosystem. How these pages are produced, and where automation is used.

What is SAC Planning Models?

SAC Planning is read-write where a BI dashboard is read-only — the write-back and audit-trailed versioning is the differentiator no BI-only tool matches without a separate paid product like Anaplan or OneStream.

SAC model?

Short answer above

SAC planning?

SAC Planning is the planning capability of SAP Analytics Cloud: planning models that users can write to, versions and categories for budget, forecast and actuals, data actions and allocations for calculations, input forms and workflows for collection, and predictive forecasting on the same model the stories read. It replaces spreadsheet budgeting and, for many SAP customers, SAP BPC — on the same tenant as the reporting.

What it is and why it matters

SAC Planning Models are the write-back planning primitive inside SAP Analytics Cloud: multi-version, time-bounded, audit-trailed datasets where finance and operations users type in forecasts, budgets, and drivers, and the platform computes derived values in real time. This is the fundamental difference from a BI dashboard, which only ever reads. A Planning Model is read-write — analysts enter cell-level updates, planners run what-if scenarios, finance closes a version and that version becomes permanent, auditable history. It is also the one capability in the SAC family with no equivalent in Power BI or Tableau unless the organisation buys a separate, dedicated planning product such as Anaplan, Pigment, or OneStream.

How it works

Four building blocks make up every planning deployment. The model is the schema — dimensions, measures, time, and version — stored in HANA with a full audit log. A version is a named state of that model: Actuals, Budget, Forecast Q3, What-If Pessimistic — and side-by-side blending of multiple versions in one view is native, not a workaround. A public dimension is shared across models, such as Cost Centre, Product, Time, or Currency, so a change to the dimension structure propagates everywhere it is used rather than needing to be repeated per model. An allocation is the algorithm that distributes a value across a dimension — top-down, bottom-up, or driver-based — which is how a single corporate target becomes a thousand cost-centre-level numbers, or how a thousand bottom-up inputs roll up into one board number.

Why it matters

Planning licenses run 2-3x the BI per-user cost — scoping Planning for the whole user base instead of just finance/planning teams inflates cost unnecessarily.
Multi-version side-by-side blending (Actuals, Budget, Forecast, What-If) is native — a differentiator that avoids building parallel scenario tooling.
Consultants advising on SAC Planning command a 15-25% rate premium over BI-only work because the skill is rarer and engagement value per project is larger.

Key points

Write-back planning primitive: read-write, multi-version, audit-trailed.
Four artefacts: Model · Version · Public Dimension · Allocation.
Five use cases: annual budget · rolling forecast · what-if · sales planning · workforce.
License: 2-3× per-user cost of SAC BI; 50-200 users typical Tier-1.
Datasphere ↔ SAC Planning, classic model: one-direction (replicate Actuals in; do not write the plan back). Seamless Planning (C020) persists the plan in Datasphere by construction.
Sizing, as SAP publishes it: an overall ceiling of 100 M records for planning (SAC System Sizing, Tuning and Limits) and 8-12 dimensions per model as the recommended range (SAP Planning modelling checklist); SAP publishes no cap on active versions — version retirement is a governance policy.
Audit-trail enabled day-1; never retrofit.
Smart Predict + Joule integration: AI-draft + human review + sign-off.

Terms used on this page

SAC Planning Model: Write-back planning primitive: multi-version, time-bounded, audit-trailed dataset for budgets, forecasts, drivers.
Version: Named state of a model (Actuals, Budget, Forecast Q3, What-If). Multi-version blending is native.
Public Dimension: Dimension shared across multiple Planning Models (Cost Centre, Product, Time, Currency).
Allocation: Algorithm distributing values across dimensions: top-down · bottom-up · driver-based.
Audit-trail: Cell-level change history with who-when-what. Enable at Model creation; cannot retrofit.
One-direction discipline: Classic model: Datasphere holds Actuals (read-only into Planning), SAC Planning holds Plan/Forecast/Budget, no write-back. Seamless Planning (C020) persists the plan in Datasphere instead.
Smart Predict: SAC's predictive forecast engine integrated into Planning Models. AI-draft + human review + sign-off.
Multi-currency consolidation: Statutory translation rules per Article L.123-12 (FR Code de commerce) for cross-entity reporting.

Sources

Full card available to members. What the full card adds: the full decision framework · the SAP vs Snowflake / Databricks / Fabric comparison · the common pitfalls and their fix · the cheat sheet · the architecture schemas · the code blocks · the facts worth quoting.

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