Rolling Forecast Builder

When to use

Use whenever the year is partway through and the full-year view needs updating with real actuals, replacing a forecast that either ignores actuals entirely (still showing the original budget) or quietly assumes an accelerating pace for the remaining months with no stated reason.

What it does

Blends actual results for completed months with a forecast for remaining months via a bundled calculator, computes the resulting full-year view, bridges it against the original plan, and explicitly flags when the forecast run rate for remaining months is meaningfully higher than the actual run rate achieved so far — the most common way rolling forecasts quietly turn optimistic without anyone noticing.

Method

1. Pull actuals for every completed month, not an estimate — the forecast is only as trustworthy as the actuals it's anchored to.
2. Build the forecast for remaining months from real drivers, using the same driver-based-budget-builder discipline, updated with anything learned from the actuals so far (a channel that's underperforming, a cost that's running higher than planned).
3. Run the bundled calculator (scripts/rolling_forecast.py) to get the full monthly view (actual and forecast months together), the resulting full-year total, and the bridge against the original annual plan.
4. Read the run-rate comparison explicitly. If the forecast's monthly run rate for remaining months is more than 15% above the actual run rate achieved in completed months, that's a flag worth resolving before the forecast goes out — either there's a specific, named reason (a signed deal, a seasonal pattern, a planned launch) or the forecast is quietly assuming things get better with no basis.
5. State the bridge to plan in both dollars and percentage, and be explicit about whether the business is tracking ahead, on, or behind the original commitment — a rolling forecast's job is to catch a miss early, not to smooth it into invisibility.
6. Update the forecast on a fixed cadence (monthly or quarterly), not ad hoc — a rolling forecast that only gets refreshed when someone remembers to do it defeats its own purpose.
7. Carry forward the reasons behind material changes from one forecast cycle to the next, so a pattern of consistently over-optimistic remaining-month forecasts becomes visible over time, not just within a single cycle.