Concept card

SAC Planning Models

As of 2026-07-24T14:00:00Z

Edited by Cédric-Olivier Mâry, 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.

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.

When to use it — the trade-offs

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: one-direction (replicate Actuals in; never write back).
Performance: ≤ 5 dim × ≤ 1M cells per Model; max 8 active versions.
Audit-trail enabled day-1; never retrofit.
Smart Predict + Joule integration: AI-draft + human review + sign-off.
SAC Planning Models is mastered only when it changes a named buyer decision.
Start with the semantic contract and control model before demonstrating the tool.

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: Datasphere holds Actuals (read-only into Planning); SAC Planning holds Plan/Forecast/Budget; never write back.
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.

Open in the app →

Guides that answer with this page

These guides cite this page as one of the sources their answer rests on.