What is a rolling forecast? How to create one, challenges, and best practices

If you built your 2026 plan in Q4 2025, here is what was happening while the ink was drying. Tariffs, the highest in 90 years, were still being announced, paused, and revised week by week. Supply chains were still reconfiguring from the shockwaves. A few months earlier, a blog post from an AI startup erased $300 billion in software stock market value in a single day. And somewhere in a different time zone, another conflict was adding a new variable to energy prices and logistics costs. By the time your board approved that budget, chunks of it were already wrong.

A static annual budget is built for a world where conditions hold steady for 12 months. In 2026, that world does not exist. According to Gartner, 81% of organizations take too long to remediate performance issues once they are identified. A rolling forecast will not shield you from disruption, but it will mean you see it coming weeks or months sooner, giving you more time to actually prepare an effective response.

In this guide, we cover what a rolling forecast is, how it works step by step, how it stacks up against a static budget, and the best practices that separate teams that implement rolling forecasts successfully.

What is a rolling forecast?

A rolling forecast is a dynamic financial planning tool updated at a predefined frequency, say, monthly, quarterly, or biannually, based on the most recent business performance data for the previous period.

For instance, in a 12-month rolling forecast that's refreshed monthly, the forecast is revised at each month's end, reflecting the performance of the preceding month. This ongoing update cycle guarantees that the latest data (actual results) always informs your operations.

“The right horizon depends on your business. A 12-month rolling forecast suits stable companies with predictable revenue. High-growth or capital-intensive companies, such as SaaS businesses burning through runway or manufacturers with long procurement cycles, tend to run 18 or 24-month horizons to maintain adequate forward visibility.” - Kirk Kappelhoff, Senior Director of Strategic Finance, Drivetrain

Rolling forecast vs. static budget

A budget is a fixed commitment set once a year. A rolling forecast is a continuously updated estimate of where the business is heading. They serve different purposes and work best together.

The key distinction is that budgets answer "What did we plan?" while rolling forecasts answer "What do we now expect?"

Most companies still run both: the annual budget for targets and accountability, and a rolling forecast to maintain an up-to-date view of where the business is heading.

CFO tip: Rolling forecasts do not make budgets obsolete. In our experience, finance teams that try to replace the annual budget entirely with a rolling forecast lose an important aspect of accountability in the process. The budget is where teams commit to targets, where compensation is anchored, and where variance from plan gets explained. 

If you want to improve your budgeting processes, we have a specific guide on budgeting best practices.

Benefits of a rolling forecast

Only 19% of companies use rolling forecasts, according to FSN Research's global survey of over 500 finance professionals. That gap represents a real competitive disadvantage for the 81% still relying on static plans. Here are a few benefits of a rolling forecast:

• Greater forecast accuracy: Businesses are never navigating with an outdated map. When a mid-year macro shock hits, a new competitor enters, or a distribution channel goes cold, the forecast reflects reality within one cycle.
• Faster response to change: Leaders get earlier warnings of performance shifts and more lead time to adjust plans. For example, if weekly sales meetings booked data shows a downward trend, the rolling forecast incorporates the latest actuals and updates revenue and cash projections for the coming months. Finance can surface the emerging gap early and work with sales leaders to adjust hiring plans, marketing spend, or pipeline targets before the shortfall compounds.
• Smarter resource allocation: Capital and headcount follow where the business is actually headed. If a product line is outperforming, finance can model the case for accelerating investment by the next forecast cycle.
• Better board and investor conversations: CFOs with rolling forecasts walk into board meetings with a forward view of the business. This helps investors understand how the business is equipped to deal with macro changes. According to IBM research, organizations that use the agility that rolling forecasts provide see a 10% improvement in profitability. 

How to create a rolling forecast?

A rolling forecast works by combining actuals-to-date with forward projections across a fixed horizon, updating it at regular intervals. Here is what the process looks like in practice.

Step 1: Identify your business drivers

A rolling forecast works best when it is built around key business drivers rather than static assumptions. Drivers are the operational factors that influence financial outcomes. For example, SaaS companies may use pipeline, deal size, and churn as revenue drivers, while professional services firms rely on billable hours and utilization.

Identifying these drivers ensures the forecast reflects how the business actually generates revenue. It makes sense to start with revenue because it’s a key driver for many other line items in your forecast, especially for the expense and headcount-related items. So if you get revenue right, you've automatically got a variety of other items in your model right. Once you get the revenue accounted for, then you can add in any other drivers.

Historical data will help you identify which drivers matter most. Look for patterns such as seasonality, growth trends, and usage spikes. For example, if you are in retail, your sales probably peak during the festive season, or if you are in education SaaS, product usage peaks during the student admission months. 

Step 2: Gather and prepare your data

Once you know your key drivers, you’re ready to start pulling data from your various source systems (e.g., ERP, CRM, HRIS, billing, and payment systems). The data you need will depend on your industry and driver context. For example, professional services might need to get data from time tracking tools, or manufacturing might need data from their warehouse management systems. 

Identify and resolve anomalies before you incorporate the data into your forecast to avoid corrupting it. This step is time-intensive with spreadsheets because it involves manually aggregating all the data into a single spreadsheet and cross-system reconciliation. This can be largely automated with FP&A software, which saves a lot of time and can significantly reduce errors. Regardless of the tool, data quality at this step determines forecast accuracy downstream.

Step 3: Define your forecast horizon and cadence

Many organizations set their forecast horizon at 12–18 months ahead and update the forecast data quarterly or monthly. Given the ever-changing nature of business and markets, the idea is that this period should be long enough to provide a strategic view but short enough to stay relevant.

The specific period can vary based on the unique aspects of each business. For example, high-growth companies burning through runway and those operating with tight liquidity often opt for a rolling, 13-week cash flow forecasting as it offers the visibility they need to identify cash flow gaps earlier, before they become a crisis.

Before deciding on the forecasting period, remember to consider your industry's seasonality, sales cycle, product development cycle, and relevant stakeholder preferences. 

Step 4: Build the initial forecast with scenarios 

Apply the chosen forecasting model to the cleaned historical data and then add best-case and worst-case scenarios. With scenario planning, your forecast will have accounted for all levels of uncertainty.

Scenario planning involves running best-case, worst-case, and baseline scenarios along with a variety of what-if scenarios to understand the impact a certain event or possibility might have on the company’s future growth and revenue. In short, scenario analysis makes your forecasts as accurate as possible, given that you are able to play out various possibilities.

Step 5: Measure forecast accuracy

Anytime you create a forecast, it’s a good idea to evaluate its accuracy if you can find the time to do it. Below are a couple of ways to keep tabs on your forecast accuracy.

Mean absolute percentage error (MAPE)

The MAPE measures the average magnitude of errors in a set of forecasts. It is expressed as a percentage thereby providing a clear picture of forecast accuracy relative to actual figures.

Mean absolute deviation (MAD)

The MAD measures the average absolute deviation from a central point (usually the mean or median) in units. This helps compare the actual number and projected forecasts for a specific item. For example, you could use the MAD to gauge the average deviation of actual subscription counts from your forecasted numbers.

Step 6: Make updates & monitoring a part of your process

Since the forecast is rolling, it needs to be regularly rolled forward by adding a new period as the latest one closes, so the planning horizon remains constant. It increases investor confidence, helps you stay nimble, allocate resources better, respond swiftly to customer needs, and be better prepared to handle the unexpected and adapt to changing market dynamics.

Challenges in implementing rolling forecasts and best practices to beat them

According to FP&A trends, one out of five organizations that implement rolling forecasts end up abandoning them. Here are common challenges that teams encounter with rolling forecasts and how to overcome them with best practices.

Rolling forecasts made easy with Drivetrain

Most rolling forecast implementations that stall do so because spreadsheets, one of the common systems that people use, are not built for continuous planning. Manual data pulls create latency. Scenario planning and version control become unwieldy. And without a shared platform, the monthly review becomes a reconciliation exercise instead of a planning conversation.

Drivetrain is built for exactly the kind of driver-based, continuously updated planning that makes rolling forecasts work. Here is how its core capabilities map to the rolling forecast process:

• 800+ native integrations: Actuals flow in automatically from your ERP, CRM, and HRIS, and other source systems, eliminating data latency and the manual effort that slows most processes.
• Multi-dimensional modeling: Build forecasts across unlimited dimensions such as business units, geographies, and cost centers without rebuilding your model each month. Changes to one dimension propagate correctly across all related views.
• Scenario and what-if planning: Toggle between base, upside, and downside scenarios in real time. When actuals close and the picture shifts, you can model the implications of multiple responses before the next board meeting.

Final thoughts

Annual budgets are not going away, nor should they. They are still the right instrument for setting targets, allocating resources, and anchoring accountability. But the business intelligence that drives day-to-day decisions, which bets to make, which risks to hedge, where to redirect investment, needs to be current. Rolling forecasts are how you get there.

The goal is to shorten the lag between what is happening in your business and when your finance team knows about it. Every week spent navigating with a stale plan is a week your competitors with better visibility are making sharper decisions.

If you are ready to move from annual planning to continuous planning, see how Drivetrain makes rolling forecasts scalable.