SAP Analytics Cloud Executive Planning Training Course

Participants can configure a planning model structure suitable for controlled budgeting, forecasting and scenario management.

• Designing planning models with public dimensions, measures and account structures
• Time dimensions configured for fiscal calendars, periods, quarters and rolling forecasts
• Private versus public versions selected for scenarios, submissions and controlled publication
• Master data properties used for ownership, currency, allocation drivers and validation
• Hierarchies maintained for cost centres, products, entities and management rollups
• Data locking states applied by version, period, entity and planning responsibility

Participants can define controlled data flows and reconciliation checks for planning models and executive reporting.

• Source-to-target mapping for actuals, budgets, master data and reference rates
• Import jobs scheduled with transformation rules, error handling and load monitoring
• Live connection constraints distinguished from acquired-model planning requirements
• Currency conversion tables maintained for local, group and constant-currency reporting
• Data quality controls reconcile source balances, record counts and dimensional completeness
• Planning model refresh procedures protect approved versions and auditability

Participants can specify calculation logic and automated planning actions that produce auditable model outputs.

• Calculated accounts separate reporting logic from editable planning assumptions
• Advanced Formulas syntax creates scoped calculations using MEMBERSET, DATA and RESULTLOOKUP
• FOREACH loops and IF conditions handle exceptions without widespread recalculation
• Allocation logic distributes shared costs through activity, revenue or headcount drivers
• Currency translation calculations distinguish transaction, closing and average exchange rates
• Performance tuning limits calculation scope, unnecessary loops and cross-model reads

Participants can construct driver-based plans and rolling forecasts for executive scenario decisions.

• Driver-based revenue plans combine volumes, prices, mix and conversion assumptions
• Workforce plans model headcount, vacancies, salaries, benefits and start dates
• Capital expenditure schedules calculate depreciation, cash timing and asset additions
• Rolling forecasts update planning horizons, actuals cutovers and forecast versions
• Scenario design compares base, upside and downside cases using controlled assumptions
• Goal-seeking logic identifies drivers required to meet profit or cash targets

Participants can design a controlled planning cycle with assigned tasks, approvals, access controls and audit evidence.

• Calendar processes sequence planning tasks, dependencies, deadlines and responsible owners
• Input tasks, review tasks and composite tasks coordinate submission cycles
• Data locking prevents unauthorised changes after review, approval or close
• Commenting, discussions and audit trails document assumptions, challenges and decisions
• Role-based security separates model administration, planning input, review and read access
• Submission governance defines escalation paths, exception thresholds and sign-off evidence

Participants can define executive planning stories that explain performance, scenarios and required management actions.

• Executive stories combine KPIs, variance analysis, trends and management commentary
• Input tables expose approved drivers while protecting calculated and locked cells
• Variance bridges explain actual-to-plan movements through price, volume and mix
• Threshold-based alerts flag material deviations requiring management intervention
• Linked analysis filters executive views by entity, product, region and period
• Presentation design applies exception focus, consistent scales and decision-oriented labels

Participants can assess predictive forecasts and combine statistical outputs with documented management judgement.

• Time-series forecasting methods assess trend, seasonality, outliers and confidence intervals
• Smart Predict scenarios generate forecasts from historical drivers and target measures
• Predictive outputs tested against finance judgement, known events and business constraints
• Regression drivers assessed for relevance, stability and explainability before adoption
• Forecast accuracy measures compare bias, mean absolute error and variance
• Human overrides documented with rationale, ownership, expiry dates and approval controls

Participants can structure an annual planning and reforecast cycle around material executive decisions.

• Annual operating plan calendar coordinates strategy, target setting, budgeting and approvals
• Target cascades translate enterprise objectives into entity, function and cost-centre commitments
• Materiality thresholds focus executive review on risks, opportunities and decision requests
• Management review packs connect financial outcomes, operational drivers and corrective actions
• Scenario triggers define when to reforecast after demand, cost or policy changes
• Board-level narratives distinguish facts, assumptions, uncertainties and recommended decisions

Participants can prepare a practical plan for deploying or improving an SAP Analytics Cloud executive planning process.

• Planning operating model assigns model owners, process owners and decision rights
• Release management controls model changes, testing, documentation and production promotion
• Planning performance metrics track cycle time, submission quality, forecast accuracy and adoption
• Control checklist covers access reviews, data reconciliation, locking and audit evidence
• Stakeholder communication plan addresses planners, executives, finance partners and technology teams
• Personal application plan prioritises a planning use case, milestones and sponsors