Concept card

BARC — Resilient Planning in Volatile Markets

As of 2026-10-06

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

What is BARC?

The annual budget built on a single base-case forecast breaks within weeks of a shock — BARC's fix is four structural capabilities (rolling forecasts, driver-based models, live multi-scenario planning, near-real-time signal integration), not a faster reforecast cycle.

What it is

BARC's 'Resilient Planning in Volatile Markets' is a topical research brief addressing how finance functions adapt their planning processes when macro volatility — inflation, supply chain shocks, geopolitical risk, commodity swings, tariff regimes — breaks the core assumptions of traditional annual budgeting.

The problem it names: the annual budget is built on a single base-case forecast completed 3–4 months before the fiscal year starts. When that base case is invalidated within weeks — as happened repeatedly in 2022–2024 — the FP&A team is left managing a plan that no longer reflects the business. The manual workaround is a mid-year reforecast, which typically takes 6–8 weeks and produces a new single-scenario plan just as vulnerable to the next shock. BARC's thesis is that organisations need structural planning capabilities — rolling forecasts, driver-based models, and multiple live scenarios — not just faster reforecast cycles.

Four capabilities BARC identifies as the foundation of resilient planning: (1) Rolling forecasts that re-project 12–18 months on a monthly or quarterly cadence rather than freezing the annual plan. (2) Driver-based models that link operational inputs (volume, headcount, price) directly to financial outcomes, so a change in one driver propagates automatically rather than requiring manual analyst intervention. (3) Scenario planning that maintains at least three live scenarios — base, downside, upside — with pre-modelled management responses for each. (4) Integration of operational signals from source systems (ERP, CRM, supply chain) into the financial model in near-real time rather than via monthly data dumps.

Why it matters

The problem is named precisely: the manual workaround (a mid-year reforecast) takes 6-8 weeks and produces a new single-scenario plan just as vulnerable to the next shock — the fix has to be structural, not faster.
The three-scenario minimum is specific: base, downside, upside, each with pre-modelled management responses — not just a wider forecast range.
For SAP analytics, the architecture translation is concrete: a SAC Planning model with driver-based Analytic Models, Datasphere live federation from S/4HANA, and three versioned scenarios refreshed nightly.

Key points

Topical BARC study on planning-process resilience under macro volatility.
Implied content: rolling forecasts, scenario / driver-based planning, fast re-baselining.
Boardroom framing the CFO buys — pairs with SAC Planning + Datasphere project shape.
Specific cases, vendor capabilities, adoption rates paywalled.
BARC's fix is structural (rolling forecasts, driver models, live scenarios, near-real-time signals), not a faster version of the same manual mid-year reforecast.
Joule's 'just ask' insights in SAC can answer driver-level questions against a live model, but only when the client's tenant meets the SAC 2506 SAP Build Work Zone prerequisite.
There is no GA, SAP-shipped 'generate the scenario' agent as of September 2026 — scenario logic design remains a human driver-modelling exercise.
The live-federation architecture only pays for itself at a meaningful volatility frequency; a stable business unit is often better served by a simpler, slower model.

Terms used on this page

Rolling forecast: Planning method that re-projects 12-18 months from the current period on a recurring (monthly/quarterly) cadence, replacing or supplementing the annual budget.
Reusable IP: An artifact, checklist, or model that can be reused across clients without copying client-specific data.
Driver-based model: A planning model where financial outcomes are formulas of observable operational drivers (volume, price, market index) rather than manually entered cell values, so a driver change propagates automatically.
Live federation: A Datasphere connection pattern that queries source data (e.g. S/4HANA) at run time rather than replicating it, so a planning model reflects near-current actuals without a batch extract.
Base / downside / upside scenario: BARC's three-scenario minimum for resilient planning — each pre-modelled with its own driver assumptions and a management response, not just a wider forecast range around a single base case.
Task chain: SAP Datasphere's scheduling mechanism for recurring data operations (e.g. nightly refresh of a live-federated planning model or scenario version).
FP&A: Financial Planning & Analysis — the finance function responsible for budgeting, forecasting and management reporting, and the primary buyer of the resilience capabilities this card describes.

Sources

Full card available to members. What the full card adds: the full decision framework · the SAP vs Snowflake / Databricks / Fabric comparison · the common pitfalls and their fix · the cheat sheet · the architecture schemas · the code blocks · the facts worth quoting.

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