This article explains Importing Series for variables in Model Reef.
You will learn:
How imported series become variables.
How to map imported data to types, categories and branches.
How imported series interact with manual edits and forecasts.
Imports are a primary way to populate variables with historical actuals and baseline assumptions.
Series can be imported from:
PDF and Excel financials.
CSV files.
Xero and QuickBooks chart of accounts and actuals.
Stock ticker fundamentals.
Other API or data feeds where supported.
The Import pipeline converts these into Data Library entries and variables.
During import you will:
Model Reef then creates variables that reference the imported series.
Imported series are stored in the Data Library as time series entries.
Variables are created that reference these entries.
Editing the Data Library entry updates all variables that use it.
You can reclassify or rename entries centrally if needed.
This separation keeps imported data and variable behaviour manageable at scale.
Imports usually provide historical actuals for past periods.
Model Reef then:
Uses these actuals directly in P&L, Balance Sheet and Cashflow for those periods.
Applies default or configured forecast rules for future periods, which you can refine using drivers, presets or manual edits.
You can see where history ends and forecast begins in charts and statements.
When source data changes, for example after a new Xero or QuickBooks sync:
The imported series in the Data Library is updated.
Linked variables automatically reflect the new history.
Forecast logic remains unchanged unless you explicitly modify it.
This provides a stable bridge between live actuals and forward looking assumptions.
You may want to override imported values in some cases:
Adjust for restatements or corrections.
Apply pro forma adjustments for transactions.
Smooth noisy series for planning purposes.
Options include:
Editing the Data Library series directly.
Creating separate adjustment variables that sit on top of imported lines.
Using drivers and formulas to build forecast overlays rather than editing history.
Choose the approach that best fits your audit and reporting requirements.
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