Support for different time-granularity for remote models

Introduction

Support for Different Time-Granularity for Remote Models

MEMBERSET [d/Measures] = “Amount”
MEMBERSET [d/Date] = “202601” TO “202612”
MEMBERSET [d/Entity_D] = “US”
MEMBERSET [d/BusinessUnit] = “BU_SKU”
MEMBERSET [d/ProductGroup_D] = “SKU”

MODEL [Sales Planning]
// Product_Item and Sales_Channel only exist in the linked source model Sales but not in default model Financial. They are used to define the source model scope.
MEMBERSET [d/Product_Item] = (“SKU_001”, “SKU_002”, “SKU_003”, “SKU_004”, “SKU_005”)
MEMBERSET [d/Channel_Sales] = (“Direc”, “Online”, “Retail”)
//Since the Date dimension is not a shared dimension, you need to define the Date scope of the source model.
MEMBERSET [d/Date] = “202601” TO “202652”
ENDMODEL

// 33001000 stands for Account: Revenue Domestic-Product.
// The granularities of the Date dimensions are different, adding syntax ” [d/Date] = PERIOD([Sales Planning].[d/Date] ” to accommodate for the difference.
DATA([d/Account_Fin] = “33001000”, [d/DataSrc] = “DataSrc_Sales”, [d/Date] = PERIOD([Sales Planning].[d/Date]))
= LINK([Sales Planning], [d/Measures] = “S90007000”, [d/Version] = “public.Plan01”)
* LINK([Sales Planning], [d/Measures] = “S90008000”, [d/Version] = “public.Plan01”)

Result: Calculated Monthly Revenue

January (4 weeks): 4,000.00February (4 weeks): 4,000.00March (5 weeks): 5,000.00

Conclusion

​ IntroductionAs planning scenarios become increasingly complex, the need for flexible, high‑performance calculation logic has never been greater. SAP Analytics Cloud (SAC) continues to evolve to meet this demand, and the latest enhancements to Advanced Formulas introduce new levels of power and simplicity to model‑driven planning.In this release, we are excited to introduce a key enhancement that streamlines common calculations, reduces script complexity, and expands what planners can achieve within the Data Action Script step. This blog highlights what’s new, how it works, and how you can begin leveraging it in your planning models. Support for Different Time-Granularity for Remote ModelsOne of the most impactful enhancements in this release is the new Support for Different Time‑Granularity for Remote Models.Previously, remote models were constrained by the time granularity defined in the default model. This meant that the time granularity used in Advanced Formulas had to align precisely with both the source and the default model structure, often limiting planners when business requirements demanded more flexible or diverse time‑based calculations.With this enhancement, Advanced Formulas now supports working seamlessly across multiple time granularities, even when retrieving data directly from remote models. This enables:More flexible planning scenariosRicher time‑series calculationsBetter alignment between operational and financial planning processes Key BenefitsMore Natural Alignment with Business CyclesDifferent planning functions operate at different rhythms. Financial planning typically uses monthly or quarterly cycles, while operational areas, such as Sales or Workforce, may rely heavily on weekly or daily views. Support for different time granularities allows remote models to reflect these variations naturally.Enhanced Advanced Formula LogicAdvanced Formulas can now reference, calculate, and iterate across different time granularities without additional modeling workarounds. This significantly simplifies complex scripting and reduces the need for auxiliary aggregation models. How It WorksThis enhancement introduces the following capabilities:Linked models can expose multiple levels of time granularity.Advanced Formulas can reference time periods with higher or lower granularity than the default model.The LINK() function now works reliably even when time granularities between models differ.This ensures that time‑based calculations behave consistently across remote and planning models. Practical Use Cases: Weekly Sales Data to Monthly Revenue CalculationOne powerful example of using this capability is referencing Weekly Sales data within a Monthly Financial Planning model. This ensures that planners maintain the precision of granular sales data while performing aggregated monthly revenue calculations. Business Scenario OverviewWeekly Sales ModelSales QuantityUnit PriceWeekly date granularityMonthly Financial Planning ModelRequires monthly Revenue values for forecasting and profitability analysis Financial Model(Month) Sales Model(Week)  Date Dimension(Week) Source Data(Sales Model)Weekly Total Revenue = Σ(Quantity × Price) = 1,000.00 Advanced Formulas ScriptMEMBERSET [d/Measures] = “Amount”
MEMBERSET [d/Date] = “202601” TO “202612”
MEMBERSET [d/Entity_D] = “US”
MEMBERSET [d/BusinessUnit] = “BU_SKU”
MEMBERSET [d/ProductGroup_D] = “SKU”

MODEL [Sales Planning]
// Product_Item and Sales_Channel only exist in the linked source model Sales but not in default model Financial. They are used to define the source model scope.
MEMBERSET [d/Product_Item] = (“SKU_001”, “SKU_002”, “SKU_003”, “SKU_004”, “SKU_005”)
MEMBERSET [d/Channel_Sales] = (“Direc”, “Online”, “Retail”)
//Since the Date dimension is not a shared dimension, you need to define the Date scope of the source model.
MEMBERSET [d/Date] = “202601” TO “202652”
ENDMODEL

// 33001000 stands for Account: Revenue Domestic-Product.
// The granularities of the Date dimensions are different, adding syntax ” [d/Date] = PERIOD([Sales Planning].[d/Date] ” to accommodate for the difference.
DATA([d/Account_Fin] = “33001000”, [d/DataSrc] = “DataSrc_Sales”, [d/Date] = PERIOD([Sales Planning].[d/Date]))
= LINK([Sales Planning], [d/Measures] = “S90007000”, [d/Version] = “public.Plan01”)
* LINK([Sales Planning], [d/Measures] = “S90008000”, [d/Version] = “public.Plan01”)When referencing data between models that use different time granularities (for example, weekly source → monthly target), you must explicitly align the time dimension in the DATA() statement. Use the PERIOD() function to map the source model’s time member to the target model’s time context. DATA(.., [d/Date] = PERIOD([Sales Planning].[d/Date]), …) = LINK(…) Result: Calculated Monthly RevenueJanuary (4 weeks): 4,000.00February (4 weeks): 4,000.00March (5 weeks): 5,000.00   ConclusionThis enhancement to time‑granularity handling significantly improves the flexibility and maintainability of planning scenarios in SAP Analytics Cloud. By enabling Advanced Formulas to reference weekly (or daily) data within a monthly model, organizations can plan more accurately and make better‑informed decisions.We hope this new capability helps streamline your planning processes.If you have feedback or want to share your own use cases, we invite you to join the conversation in the SAP Community. Moonjun   Read More Technology Blog Posts by SAP articles 

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