Product Quick Start Guide
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Trovata provides an end-to-end workflow for managing inflows, outflows, property- or fund-level cash availability, and forecasting.

Users can pull data from other TMS modules, bank feeds, ERPs, or other systems; categorize cashflows; model future activity using historical trends; and surface liquidity needs through dashboards or scheduled reports.
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Start by clarifying the outcome needed by the forecast near-term cash positioning vs. longer-range planning) and the audience it services (Treasury, FP&A, etc).

Once the purpose is clear, align on a clean scope: horizon(e.g., 2-week / 13-week / 12-month), key cash flow categories, where inputs come from, and who owns them.

Set expectations that the best path is that the forecasting process will be validated with forecast-to-actual/variance discipline over time.

Categorization for forecasting is built around a Cashflow Category model: forecast “rows” typically map 1:1 to categories, but can also be configured many-to-one (multiple categories roll up into a single reporting stream like “Payroll”) or one-to-many (one category can contribute to multiple rows for different reporting views).

This mapping is the key lever that keeps forecasts aligned to treasury’s reporting structure while ensuring actuals flow in automatically once transactions meet the Cashflow Category criteria.

This workflow is designed to get forecast rows into a shared forecast database quickly, repeatably, and with clear audit ability.

Users can load starting forecast lines through multiple ingestion paths:

In addition to external inputs, forecastable cash flows can also be sourced directly from other TMS modules—for example, scheduled/expected activity coming from Payments and Capital Markets workflows—so treasury can seed the forecast with system-of-record items alongside imported contributor data.

Once loaded, teams can “reset” a cycle by inactivating prior rows and reloading a fresh set, preserve who/when/source traceability, optionally apply forecast modeling adjustments, and lock the forecast type when it’s time to finalize.

The forecasting modeler is built for parameter-driven adjustments on top of system-sourced data.

Teams can choose a source (actuals or forecasts), slice history by dimensions like bank account and calendar patterns (e.g., only Mondays or specific week-of-month behavior), then transform and project those patterns forward using rules like averaging/summarizing, percent increases/decreases, escalators, rounding, and “lift” logic (e.g., reuse last year’s seasonal month).

They can also override and re-map outputs (category/entity/account) and make targeted post-load edits to specific future values.

Scenarios are typically managed as separate forecast types/sets (base/downside/upside), with side-by-side comparison usually handled via the Excel reporting/plugin for reporting-ready layouts. For instance, users can duplicate a base forecast into a downside (or upside) case with 1–2 key assumption changes.

Graph the forecast results in the Trovata TMS UI or export to Excel/CSV to produce custom reports. Establish a cadence (daily / weekly) and owners for updates + review.

Begin a lightweight forecast-to-actual check so the forecast improves over time.

Can you do direct and indirect forecasting?

Yes—teams can forecast using direct inputs (AR/AP/operational detail) and/or incorporate indirect-style inputs (e.g., EBITDA-based adjustments), depending on how your process is run.

Is forecasting “AI-driven” or a black box?

No—forecasting is based on transparent inputs and explainable modeling methods. Your team controls assumptions and can see what changed and why.

Can I customize cashflow categories?

Yes—teams can define cashflow categories (and groupings) that match internal reporting and use them consistently across forecasting, reporting, and reconciliation.

How do we get data into the forecast (manual, import, integrations)?

Forecast inputs can be entered manually, uploaded via Excel/CSV templates, and—where applicable—fed from connected source systems. Many teams mix methods by category and owner.

Can I create multiple scenarios?

Yes—scenarios are typically managed as separate forecast sets (base/downside/upside) so assumptions stay governed.

Can I compare scenarios side-by-side in the app?

Teams typically do side-by-side comparison via export and/or the Excel add-in to produce reporting-ready layouts.

Do you support driver-based models (headcount → payroll, occupancy → revenue)?

In-app forecasting is typically amount-based. Many teams do driver math upstream (often in FP&A tools or Excel) and import the resulting amounts.

How do we reconcile forecast vs actual?

Best practice is to align categories and ensure the right sources feed actuals (e.g., bank/ERP). Then teams establish a forecast-to-actual variance review habit to improve accuracy over time.

Can Trovata support multi-entity / multi-bank structures and distributed contributors?

Yes—teams can organize forecasting by entity/account and support distributed inputs (e.g., tax, FP&A, business owners) with clear ownership and governance.

Can we export forecasts into existing Excel-based workflows?

Yes—forecasts and reports can be exported (e.g., Excel/CSV/PDF), and teams often use Excel-based packs to share and standardize stakeholder reporting.