Forecasting

Forecasting Overview

Forecasting is the process of predicting future revenue based on current pipeline, historical conversion data, and qualitative inputs from the sales team. It answers the core question for any revenue organization: how much will we close this period?

Forecasting Methods

1. Bottom-up (rep call)

Each rep commits to a number based on their deals. Managers roll these up and adjust. This method is simple but vulnerable to:

• Sandbagging: Reps under-commit so they can over-deliver.
• Happy ears: Over-optimism about deals that are not truly qualified.

1. Weighted pipeline

Each deal’s value is multiplied by a stage-based probability. Deals in later stages get higher weights. This is more structured than pure gut feel, but it assumes all deals in the same stage have the same likelihood of closing, which is often not true.

1. Historical conversion

Uses historical stage-to-close conversion rates to estimate what percentage of the current pipeline will convert. This is more data-driven but depends heavily on clean, consistent historical data and stable processes.

1. AI-assisted

Machine learning models analyze deal attributes, activity patterns, and engagement signals to predict outcomes. This can be the most accurate approach, but it requires:

• Sufficient data volume
• High data quality
• Robust model training and monitoring

Forecast Categories

Most organizations structure their forecast into layers:

• Commit: Deals the rep is highly confident will close this period.
• Best Case: Deals that could close if things go well (e.g., no major slippage or surprises).
• Pipeline: Deals that are active and possible but unlikely to close in the current period.
• Closed: Deals already closed-won and booked.

These categories help leadership understand both the baseline expectation (Commit) and the upside potential (Best Case, Pipeline).

Why Forecasting Matters

The forecast effectively serves as the company’s operating plan. It influences decisions such as:

• Hiring and headcount planning
• Marketing and sales investment levels
• Product and capacity planning
• Fundraising, cash management, and capital allocation

Accurate forecasting is the bridge between what sales is doing today and what the broader business can safely plan for tomorrow.

RevOps Application

Revenue Operations (RevOps) is typically responsible for:

• Designing the forecasting methodology (which methods, definitions, and rules to use)
• Building and maintaining the data models and reporting infrastructure
• Running the forecast cadence (weekly calls, submissions, rollups, and adjustments)
• Measuring and improving forecast accuracy over time

The strongest RevOps teams combine:

• Quantitative analysis: Pipeline metrics, conversion rates, trend analysis, model outputs
• Qualitative inspection: Deal reviews, rep and manager input, risk and slippage assessment

This blend of data and judgment produces forecasts that leadership can rely on for strategic and operational decisions.