Forecast Baselines: Freeze a Version, Then Measure Against It

Most finance teams produce a forecast, present it, and never look at it again until someone asks why the quarter missed. The forecast itself is rarely the problem. The problem is that nobody saved it as a fixed point to measure against, so by the time actuals land, the original assumptions have been quietly re-typed into a dozen spreadsheet versions and there is no clean answer to “how far off were we, and on which line.”

Rexfin’s forecast lab is built around a different habit: freeze a version, then let the model tell you how it held up.

What a baseline actually is

A forecast in Rexfin starts as a set of per-line fits: exact CAGR or OLS-linear projections computed deterministically from your reconciled actuals, with each fitted line carrying the method, the parameters, and the atom IDs it was derived from. That’s the raw material. A baseline is what happens when you save a specific combination of driver assumptions as a named scenario: Base, Best, Worst, or a custom vector you built for a board question. Saving one stores only the assumptions (the driver vector, the horizon, the anchor period), never a frozen set of output numbers.

That distinction matters. Every time you reopen a saved scenario, it recomputes against your current reconciled actuals, not the actuals that existed the day you saved it. If your historical figures were later restated or a new period closed, the baseline reflects that. And if the underlying actuals have moved since you saved the scenario, Rexfin says so directly: a basis fingerprint on the scenario flags “actuals have changed since this was saved,” so you’re never comparing a stale assumption set against a picture that quietly shifted underneath it.

Backtesting: did the model call it right

Before you trust a baseline going forward, you can ask how it would have done looking backward. Rexfin’s backtest holds out the most recent audited year, fits the model on everything before it, and compares the projection against what actually printed, per line, with a median error across the set. The honest caveat here: on a handful of years of history, that error carries real margin, and the tool says so rather than presenting a false-precision number. It’s a sanity check on the fitting method, not a guarantee about next year.

Comparing saved scenarios side by side

Once you have more than one named baseline, Rexfin lets you line up two or three of them together with deltas computed against the first: Base versus Worst versus a custom downside, or last quarter’s plan versus this quarter’s. The comparison view stays clearly marked as unaudited output layered on top of the reconciled model, because that’s what it is: a way to see how assumptions diverge, not a new set of figures competing with your filed numbers.

For businesses on an interim reporting cycle, rolling reforecast takes this further: it anchors a fresh projection to the latest reviewed interim period (a TTM or a nine-month figure) rather than waiting for the next annual filing, and compares that anchor against the prior annual baseline on the same driver vector, with a stale-note if the annual figure it’s being compared to is older than the interim itself.

What Rexfin deliberately keeps out

Statistical baseline models (exponential smoothing, ARIMA-style fits) sit behind this as an optional, on-demand layer, offered as a suggestion with a confidence band, never as something that lands in a board pack. A forecast value is a modelled cell by construction: it can flag a warning if something looks off, but it never blocks an export, and it never carries the citation an actual filing figure carries. That line is not a UI convention: it’s enforced the same way the export gate enforces every other actual-versus-modelled distinction in the product.

Who this is for

This is built for FP&A teams who need to answer “how good was our last forecast” with something more concrete than a shrug, and for anyone managing a rolling forecast cadence who wants last quarter’s plan to stay checkable rather than overwritten. If your current process for tracking forecast accuracy is a saved spreadsheet nobody opens again, a baseline gives you the same comparison as a living, recomputed check against your actual KPI variance.

See how baselines sit inside the wider modeling workflow on the Rexfin product tour, or look at how driver assumptions drive the underlying what-if models a baseline is built from.