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Academy module

SAC Stories & Dashboards

Senior 3-act SAC story structure — purpose-driven, decision-anchored — architecture diagram for SAC Stories & Dashboards, Analytics Legends Academy module M018

As of 2026-10-04

Edited by , sole editor and publication director — 27 years in the SAP ecosystem. How these pages are produced, and where automation is used.

Stories = decision-driven consumption layer. Senior 3-act structure: Headline KPI · Drivers · Action. ≤ 7 widgets per page (47 = 47 AM queries). Use Optimized Design (modern + mobile); Classic only for legacy until migration. Mobile-first or ship dies in 3 months. Every story has documented purpose: 'answers Q for persona P at decision D'.

What you will learn

  • Work through a realistic scenario: Industrial group, finance team wants 'monthly business review' story. 4-week build.
  • Recognize and avoid the anti-pattern: 47 widgets on one page — Perf collapse + cognitive overload.
  • Apply the module's core decision: Story type — choose Optimized Design for new; Analytic Application if custom scripting needed, not Classic Design for new builds.
  • Track mastery with the KPI: Widget count per page (target: ≤ 7; red flag: > 12 = redesign).

Module overview

SAP Analytics Cloud Stories = the consumption surface where governed Datasphere data becomes business decisions. A senior consultant designs stories around the decision the user is making, not the data the team has. Junior failure: 47 charts on one page. Senior craft: 3-7 charts per page, each answering one question, with a clear narrative arc.

The 3-act structure every senior story follows:

  1. Headline KPI (1-2 widgets) — the metric that matters this period.
  2. Drivers (3-5 widgets) — what's pushing the headline up or down.
  3. Action (1-2 widgets) — what should the user do next.

Story types and when to use each.

  • Optimized Design Experience — modern, mobile-friendly, recommended for new builds.
  • Classic Design Experience — legacy, only for existing stories until migration window.
  • Analytic Application — when scripting + custom interactivity are needed (M023).

Performance reality. Story performance is dominated by (a) underlying analytic model query cost and (b) widget count + data volume per widget. A 47-widget story queries the AM 47 times. Senior pattern: ≤ 7 widgets per page, hierarchy + filter linkage to limit widget cardinality, server-side aggregation pushed to DSP analytic model.

Prerequisites

  • Review core concepts first: C018, C019, C021

Outcomes

  • Work through a realistic scenario: Industrial group, finance team wants 'monthly business review' story. 4-week build.
  • Recognize and avoid the anti-pattern: 47 widgets on one page — Perf collapse + cognitive overload.
  • Apply the module's core decision: Story type — choose Optimized Design for new; Analytic Application if custom scripting needed, not Classic Design for new builds.
  • Track mastery with the KPI: Widget count per page (target: ≤ 7; red flag: > 12 = redesign).
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