Scenarios / Assumptions Studio¶
Status: Partial¶
Domain: Scenario Modelling Linear Projects: None yet
What It Does¶
Palm will enable treasury teams to create and manage forecast scenarios - alternative views of the future that model different assumptions. Instead of maintaining separate spreadsheets for "base case," "conservative," and "aggressive" scenarios, users will be able to apply adjustments on top of their base forecast while preserving underlying patterns.
The key insight from customer research is that simple percentage-based adjustments (e.g., "-5% on collections") are more valuable than complex scenario modeling. Treasury teams need to quickly answer "what if?" questions without rebuilding entire forecasts.
Planned Capabilities¶
| Capability | Status | Notes |
|---|---|---|
| Percentage-based adjustments | Planned | Apply +/- % to categories |
| Pattern-preserving adjustments | Planned | Keep weekly patterns when adjusting totals |
| Named scenarios | Planned | Save and compare multiple scenarios |
| Scenario comparison | Planned | Side-by-side view of scenarios |
| Forecast version tracking | Planned | Save and recall past forecasts |
| Investment planning scenarios | Planned | Model impact of investment decisions |
| Assumptions backend | Shipped | Backend service for base forecast assumptions + Treasury API service |
Jobs to Fulfill¶
From scenario-modelling/jobs.md
1. Apply percentage-based assumptions to forecasts while preserving underlying patterns¶
Desired Outcomes: - [ ] Minimize the risk of overestimating collections or underestimating outflows - [ ] Increase the ability to model scenarios quickly (e.g., -5% on collections) - [ ] Reduce manual effort in creating multiple forecast scenarios - [ ] Minimize the loss of weekly/daily patterns when adjusting forecast totals
2. Validate indirect P&L budget assumptions using direct cash forecast as independent sense check¶
Desired Outcomes: - [ ] Minimize the time required to sense-check controlling's budget against direct cash data - [ ] Increase confidence that FP&A's 5-year plan is realistic by cross-referencing with cash flow patterns - [ ] Reduce reliance on mental calculations when assessing whether budget assumptions hold - [ ] Increase ability to feed budget-level assumptions (e.g., +40% inventory) into the direct forecast and see the cash impact
3. Compose multiple assumptions into named event scenarios (e.g., store opening, acquisition)¶
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
4. Define worst/best case scenarios from historical extremes¶
Desired Outcomes: - [ ] Minimize the effort to calculate worst-case cash position from historical min/max by category group - [ ] Increase the ability to layer multiple severity levels by toggling category groups on/off - [ ] Reduce dependency on manual spreadsheet analysis for stress testing
5. Model the cash impact of timing shifts in payments and collections¶
Desired Outcomes: - [ ] Minimize the manual effort to model 'what if payments are delayed by N days' scenarios - [ ] Increase the ability to quantify the cash impact of intercompany payment term changes - [ ] Reduce the time to model the impact of collection slowdowns on entity-level cash
6. Save and compare forecast versions to track how assumptions changed over time (Emerging)¶
Desired Outcomes: - [ ] Minimize the difficulty of remembering past forecast assumptions - [ ] Increase ability to attribute variance to assumption changes vs actuals variance - [ ] Reduce unexplained variance by tracking all assumption changes systematically
7. Make quick operational decisions when plans change (Emerging)¶
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 - [ ] Increase confidence that scenario impact is accurately calculated
8. Create scenario plans for investment activity (Emerging)¶
Desired Outcomes: - [ ] Minimize the ad-hoc nature of investment decisions - [ ] Increase ability to track planned vs actual investment activity - [ ] Reduce the cognitive load of making investment decisions on a rolling basis
Pain Points to Address¶
| Pain Point | Priority | Notes |
|---|---|---|
| Duplicating forecasts for each scenario is time-consuming | High | Core problem to solve |
| No way to apply systematic percentage adjustments | High | Key customer request |
| Keeping multiple scenarios in sync | High | Scenario management |
| Blanket adjustments destroy patterns | High | Pattern preservation essential |
| TMS inflexibility drives Excel usage | High | Must be easier than Excel |
| Making overly conservative investment decisions | Medium | Requires forecast integration |
Design Considerations¶
Based on customer feedback:
- Simplicity over complexity - Users want percentage adjustments, not complex scenario trees
- Pattern preservation - Adjusting a monthly total should distribute across days intelligently
- Transparency - Clear visibility into what adjustments are applied
- Speed - Must be faster than doing it in Excel
- Reusability - Save scenarios and adjustment templates
How It Will Work (Technical)¶
TODO: Define architecture
| Component | Technology | Notes |
|---|---|---|
| Scenario storage | ||
| Adjustment engine | ||
| Pattern distribution | ||
| Version tracking | ||
| API endpoints |
Related¶
- Domain knowledge: docs/knowledge/scenario-modelling/
- Related features: forecasting.md, investments-visibility.md
- Roadmap: Apply percentage-based assumptions to forecasts (Skateboard)
- Planned roadmap: Composable assumptions, Timing shifts, Worst/best case scenarios
Last updated: 2026-03-10