Scenario Modelling¶

Overview¶

Scenario planning in treasury involves creating multiple versions of cash flow forecasts based on different assumptions to prepare for uncertainty. Treasury teams use scenarios to stress-test their liquidity positions, model best/worst case outcomes, and make more robust financial decisions.

This matters because treasury must maintain adequate liquidity even when actual results differ significantly from base forecasts. By modeling scenarios like reduced collections, delayed payments, or economic downturns, teams can identify potential shortfalls before they occur and plan appropriate responses.

Key challenges include the manual effort required to create and maintain multiple scenarios, difficulty in applying systematic assumptions across forecast categories, and lack of tools that make scenario comparison intuitive.

For detailed ICP context and terminology, see fundamentals.md

Top Jobs & Desired Outcomes¶

Full history: jobs.md

1. Apply percentage-based assumptions while preserving patterns ✓¶

Desired Outcomes: - Minimize the risk of overestimating collections or underestimating outflows - Increase the ability to model scenarios quickly (e.g., -5% collections, +10% for seasonality) - Reduce manual effort in creating multiple forecast scenarios - Minimize the loss of weekly/daily patterns when adjusting forecast totals

Sources: Personio (2025-10-21, 2025-12-04, 2026-02-18), ON (2026-02-18) - Confirmed (4 sources, 8-9/10 excitement from ON, Tom validated prototype)

2. Compose multiple assumptions into named event scenarios ⚡¶

Desired Outcomes: - Minimize the effort to model multi-faceted business events as coherent scenarios - Increase reusability of individual assumptions across different scenario combinations - Reduce the complexity of understanding combined impacts from multiple simultaneous changes

Source: ON (2026-02-18) - Lego-piece mental model resonated, Swedish store opening example

3. Track fixed-point scenarios against rolling actuals over time ⚡¶

Desired Outcomes: - Minimize the loss of scenario baselines when forecasts re-baseline to actuals - Increase ability to see whether actuals are tracking best case, baseline, or worst case

Source: ON (2026-02-18) - Jennifer raised, ON team validated

4. Plan investment decisions using forward cash visibility ⚡¶

Desired Outcomes: - Minimize the uncertainty when deciding investment duration - Increase confidence to lock cash in for longer periods when forecasts show adequate liquidity

Source: Personio (2026-01-28) - Emerging, needs corroboration

5. Make quick operational decisions when plans change ⚡¶

Desired Outcomes: - Minimize the time to model a "what if this payment doesn't happen" scenario - Reduce the need to use Excel for ad-hoc calculations

Source: ON (2024-11-19) - "If the tool is not flexible or intuitive to make scenarios, you end up doing it in Excel"

Key Pain Points¶

Full history: pain-points.md

Manual scenario creation - Creating multiple forecast versions requires duplicating data and manually adjusting values (Source: Personio)
No systematic assumption application - Can't easily apply percentage-based adjustments across categories (Source: Personio)
Rolling forecast re-baselines wipe out scenario comparison - Can't compare original scenarios against actuals over time (Source: ON 2026-02-18)
Cannot forecast for new entities with no history - New markets/stores have no ML baseline (Source: ON 2026-02-18)
TMS inflexibility drives Excel usage - If tool isn't easy for quick scenarios, people go back to Excel (Source: ON)
Overly conservative investment decisions - Without forward visibility, teams default to shorter-term, lower-yield investments (Source: Personio)

Key Opportunities¶

Assumption-based modeling - Allow users to define assumptions (e.g., -5% collections) that automatically adjust forecasts
Scenario comparison views - Side-by-side comparison of base vs. conservative vs. aggressive scenarios
Quick scenario generation - One-click creation of standard scenarios (best/worst/base case)
Investment scenario planning - Monthly planning view showing planned investment activity against forecasted cash positions

Open Questions¶

[x] How do teams typically define their scenario assumptions? → Percentage-based adjustments on categories (Personio, ON validated) + one-off manual assumptions (Tom at Personio)
[x] Do teams need to scenario-plan at the category level or overall forecast level? → Both — category-level adjustments compose into scenario-level views (ON 2026-02-18)
[ ] What's the typical number of scenarios teams maintain?
[ ] How should fixed-point scenarios interact with rolling forecasts? (snapshot vs continuous overlay)
[ ] How to handle scenario modelling for entities with no historical data? (manual input, template from similar entity?)

Last updated: 2026-02-18 | Sources: 10 transcripts (view all)