SAC Predictive Planning — Time-Series Forecasting Inside Planning Models

Predictive planning is Smart Predict on a planning model

SAC predictive planning is time-series forecasting run on a planning model rather than on a generic dataset. There are two ways in. A Smart Predict time-series scenario can take a planning model as its source and write the forecast into a private version of that model, which planners review, adjust and publish like any other plan data. A planner can also run a predictive forecast directly on table cells in a story or analytic application. For Seamless Planning models, SAP documents a further workflow: generating and integrating Automated Predictive Library (APL) forecasts into the model. The engine behind Smart Predict's time-series scenario is APL's automated time-series capability (concept “SAP HANA Automated Predictive Library (APL)”); predictive planning is the same capability pointed at plan data.

Why the distinction from Smart Predict time series matters in a proposal

Predictive planning is not a second engine next to Smart Predict: it is Smart Predict's time-series scenario pointed at a planning model, plus the table-cell forecast. The output lands in a private planning version, inherits its audit trail and enters the normal publish and approval flow. Scope it once, as one capability, and price the model work separately.

Why it matters

• Predictive Planning is not a separate engine from Smart Predict's time-series scenario — SAP documents both as running on APL's Auto Time Series function; pricing or scoping them as unrelated capabilities double-counts the same underlying modeling work.
• The forecast a planner triggers lands as a reviewable, adjustable, lockable planning version through the same approval workflow as any other version — a concrete, demonstrable answer to 'how does AI touch our planning process' rather than an abstract claim.
• A planning model without clean, continuous history for the target measure limits what Predictive Planning can produce regardless of APL's performance — remodeling the planning model is often the larger part of a Predictive Planning engagement, not the forecast call itself.

Key points

• Predictive planning = time-series forecasting run on a planning model: a Smart Predict time-series scenario with a planning model as source, or a forecast on table cells.
• For Seamless Planning models, SAP documents a further workflow: generating and integrating APL forecasts into the model.
• Same engine as Smart Predict's time-series scenario (APL's automated time series), not a planning-specific algorithm.
• Smart Predict can write the forecast into a private planning version, which inherits the audit trail and the normal publish and approval flow.
• Scope it once, as one capability, and price the model work separately.
• Result: a private version a planner reviews against confidence bounds, adjusts and publishes.
• Data bar: enough continuous history to cover the seasonality you expect; SAP's time-series guidance applies.
• SAP-RPT-TS (generally available since SAP TechEd 2026) is a separate time-series route through SAP HANA Cloud, SAP AI Core or IBP; compare on the same history.

Terms used on this page

Planning model

The SAC model type that holds plan data and versions; a Smart Predict time-series scenario can use it as source and write the forecast into a private version.

Predictive Planning

SAP's name for triggering an APL Auto Time Series forecast from inside a planning model, writing the result back as a plan version.

Planning version

A distinct, lockable, auditable set of plan numbers; a predictive forecast is delivered into a private version and published through the same approval flow as any other.

Seasonality bar

Enough continuous history to cover the seasonality you expect before trusting a time-series forecast; SAP's time-series guidance applies to predictive planning and Smart Predict alike.

Confidence bounds

The statistical range APL's Auto Time Series attaches to a generated forecast, letting a planner judge how much to trust it before deciding whether to override it manually.

APL (Automated Predictive Library)

SAP's underlying automated machine-learning library; its Auto Time Series function is the specific capability both Predictive Planning and Smart Predict's time-series scenario call.

Version-category combination

The specific planning-version and category pairing a Predictive Planning forecast can be written into, depending on how the target planning model is structured.

Sources

1. SAP Community (SAP-authored) — Generating and Integrating Automated Predictive Library (APL) Forecasts in a Seamless Planning Model
2. SAP Community (SAP-authored) — One Predictive Planning & Smart Predict Blog to Find Them All!
3. SAP Help Portal — Smart Predict (SAP Analytics Cloud)
4. Run Predictive Forecasts on Table Cells — SAP Analytics Cloud Help
5. Forecasting with Predictive Analytics — SAP Learning (Planning in SAC)
6. xP&A Operational Workforce Planning: Create Predictive Scenario — SAP Developer Center
7. Time Series Forecasting in SAP Analytics Cloud: Smart Predict and Predictive Planning in Detail — SAP Community
8. SAP Analytics Cloud Predictive Planning: Frequently Asked Questions — SAP Community Blogs (2021)
9. Sales Forecasting & Planning using SAP Analytics Cloud — SAP Community
10. Time Series Forecast Prediction Scenario in SAP Analytics Cloud — SAP Community Blogs (2022)
11. SAP Analytics Cloud: Introduction to Predictive Scenarios and their Applications — SAP Community Blogs (2022)
12. Time Series Forecasting — SAP Community Blogs (2017)
13. Understanding Time Series Forecasts with Smart Predict — SAP Community Blogs (2023)
14. Introducing Time Series Models in SAP Analytics Cloud Smart Predict — SAP Learning
15. How to use SAP Analytics Cloud's Smart Predict to discover deep insights — Capgemini
16. SAP News — SAP TechEd 2026 press release, 27 Oct 2026 (SAP-RPT-TS)