Finance · Analytics ·

Monthly close

Manage your close: time to finalize, pending entries, variance vs PY and account accuracy.

Illustrative preview of the SAP Analytics Cloud dashboard Monthly close for the Finance industry: metrics Close time (days), Pending entries, Actual revenue/EBITDA, Variance vs PY, analyzed by Entity, Month, Account.
Illustrative preview of a possible rendering in SAC. Brand colors and structure; synthetic figures.

KPIs included

  • Close time (days)
  • Pending entries
  • Actual revenue/EBITDA
  • Variance vs PY

Analysis dimensions

  • Entity
  • Month
  • Account

About this template

Manage your close: time to finalize, pending entries, variance vs PY and account accuracy. Designed for teams in the Finance industry, the model pre-wires 4 key metrics — including Close time (days) and Pending entries — analyzable across 3 analysis axes (Entity, Month, Account). You start from an already-bounded base (units, aggregations and business labels defined) rather than a blank sheet.

After downloading, import Monthly close into SAC Modeler (Files → New Model → Import data from a file), map the 3 dimensions and 4 measures, then build your Story. The provided dataset contains 720 to 960 rows with realistic values for the Finance industry, available as .xlsx (multi-sheet workbook), .csv (flat table) and .package (ZIP bundle with model.json, data.csv and README).

FAQ

What is the "Monthly close" template for?

It provides a ready-to-use SAC structure to drive analytics in the Finance industry. The standard business KPIs and dimensions are already defined, saving you the modeling phase.

Which KPIs are included?

The template includes 4 metrics: Close time (days), Pending entries, Actual revenue/EBITDA, Variance vs PY. Each is computed across the dimensions Entity, Month, Account.

How do I import it into SAP Analytics Cloud?

Download the .csv or .xlsx format, then in SAC: Files → New Model → Import data from a file. Map the columns (Dimensions then Measures), validate the types and build your Story. Allow 5 to 10 minutes for an operational model.