SAP Analytics Cloud (SAC)
Stories, dashboards and planning on live SAP data.
- Stories & Dashboards
- SAC Planning
- Live connections
- Import connections
- Predictive Scenarios
- Smart Insights
SAP · Analytics & Planning
Analytics on the same data that runs.
Real-time analytics on the SAP transaction layer plus integrated planning: SAP Analytics Cloud, BW/4HANA, Datasphere, PaPM, Group Reporting.
SAP Analytics & Planning is the layer that turns SAP transactional data into decision surfaces: dashboards, plans, forecasts and consolidations grounded in the live estate rather than yesterday's export.
Phoenix designs this layer around a simple rule: if the number can't be traced back to the source transaction, it's a shadow number and shouldn't leave finance's spreadsheet. SAC live connections, BW/4HANA data marts, Datasphere for cross-source governance, and PaPM where allocations get complex, all tied back to S/4HANA.
What's in scope.
Data platforms
The governed data layer under every report.
- SAP Datasphere
- BW/4HANA
- BW on HANA
- S/4 Embedded Analytics
- HANA views
Planning & Costing
Integrated planning and allocation engines tied to the ledger.
- PaPM (Profitability & Performance)
- SAC Planning
- Integrated Financial Planning
- Cost Allocations
Consolidation & Reporting
Statutory and management reporting from one model.
- Group Reporting
- BPC
- Statutory reporting
- Management reporting
Legacy & Migration
Sequenced modernisation off BW and BOBJ estates.
- BW on HANA → BW/4HANA
- SAP BOBJ decommission
- Universe migration
- Report rationalisation
What actually moves.
One version of the truth
Live connections mean the KPI on the dashboard is the same number booked in the ledger: no reconciliation between report and source.
Integrated finance + operations planning
Sales plan, production plan, financial plan and headcount plan sit in one SAC model, driven by shared drivers instead of independent spreadsheets.
Faster forecast cycles
Rolling forecast at driver level rather than budget-locked annuals: SAC + SAP data + predictive delivering weekly refresh where the business needs it.
BW/BOBJ modernisation without the mess
Sequenced migration from BW on HANA to BW/4HANA and retirement of BOBJ into SAC, with report rationalisation, not lift-and-shift of legacy noise.
The approach.
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01
Frame
Decision map: who consumes what, at what cadence, to make which call. Kills the useless reports on day one.
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02
Model
Semantic model on Datasphere or BW/4HANA. Live connection where possible, extract only when necessary.
-
03
Publish
SAC stories built for the specific consumer: CFO pack, plant manager view, procurement scorecard.
-
04
Adopt
The report only counts if the business uses it. Hyper-care + KPI-owner sessions until adoption is real.
Named deliverables.
Every engagement lands specific artefacts, not slides.
- Decision-map artefact: every KPI mapped to consumer, cadence and decision
- Semantic model on Datasphere or BW/4HANA with lineage documented
- SAC stories + dashboards for CFO / operations / commercial teams
- SAC Planning model with integrated finance + operations drivers
- PaPM model where allocations warrant it (cost-to-serve, profitability)
- Retirement plan for redundant legacy reports (BOBJ, BEx, custom Fiori)
- Adoption playbook + KPI-owner handover
The wider SAP practice.
Finance & Controlling
One source of financial truth: statutory, management and consolidation on S/4HANA.
Supply Chain & Operations
Plan, procure, produce, deliver, maintain: one integrated backbone on S/4HANA.
Technology, Integration & Experience
Clean core, BTP extensions, CPI integrations and Fiori-first UX.
Frequently asked
SAP Datasphere or BW/4HANA: which do you recommend?
Both, and often together. BW/4HANA is the right choice when the customer has heavy SAP data-warehousing investment and needs stable, governed data marts. Datasphere is our default for greenfield or where cross-source (SAP + non-SAP) semantic modelling and business-user data products are important. Datasphere and BW/4HANA integrate; the choice isn't binary.
Live connection or import into SAC?
Live where the underlying source can serve query performance: S/4HANA embedded analytics, BW/4HANA, Datasphere live. Import when acceleration, blended sources or offline access matter. Both patterns are supported in the same SAC tenant; we design per story.
How do you handle the BOBJ retirement?
Sequenced retirement plan starting with report rationalisation (usually 40 to 60% of BOBJ reports are dead or duplicative). Surviving reports are re-platformed to SAC stories or Fiori Elements analytical apps. Universes migrate to Datasphere or BW/4HANA data models. Not lift-and-shift: noise doesn't get carried forward.
SAC Planning vs a separate EPM tool?
SAC Planning integrates finance, sales and operations planning in one model directly connected to SAP transactional data; that alignment is hard to beat when SAP is your system of record. Standalone EPM tools remain valid where highly specialised planning use cases (e.g. complex trade promotion planning) require them, but SAC Planning is our default.
Predictive and ML: SAP or bring your own?
SAC Predictive covers descriptive predictive scenarios (classification, regression, time-series) without leaving SAP. For heavier ML work (deep learning, custom models, larger-scale training) Phoenix runs those on AWS SageMaker or Bedrock and integrates the results back into SAC or S/4HANA. Best-fit-for-purpose, not tool ideology.
The earliest conversations are usually the most useful.
Whether you're scoping an SAP move to cloud, restarting a stalled programme, or just trying to figure out where data and AI fit, start with a conversation.
