Forecasts
Forecasts is the Salesforce sales-management feature that projects expected revenue or unit volume from the opportunity pipeline across future periods.
Definition
Forecasts is the Salesforce sales-management feature that projects expected revenue or unit volume from the opportunity pipeline across future periods. The current implementation is Collaborative Forecasts, a Lightning experience where each user sees a grid of forecast periods (monthly or quarterly) broken down by forecast category and rolled up through a forecast hierarchy that mirrors the role tree.
Collaborative Forecasts replaced the legacy Customizable Forecasting product, which Salesforce retired in the Summer '20 release (around July 2020). An org can run up to four active pipeline forecast types at once, mixing revenue and quantity measures off the same opportunity data. Reps and managers can adjust totals inline, load quotas, and overlay an Einstein prediction. It is one of the most-used surfaces in Sales Cloud after the opportunity pipeline itself.
How Collaborative Forecasts reads your pipeline
The grid, the hierarchy, and the rollup
The Forecasts tab renders as a grid. Rows represent each forecast period, and columns represent each forecast category. Every rep sees a grid populated from the opportunities they own. Every manager sees their direct reports listed as rows, and each row expands to reveal that report's own grid. The number in any cell is the sum of a measure, usually Opportunity Amount, across all opportunities that fall in the period and category. Those sums roll up the forecast hierarchy, which by default follows the role hierarchy. The climb stops at the top role, where the senior leader's grid shows the whole company. Because the rollup is built on roles, a rep with no role or a manager missing from the hierarchy produces a gap, and a gap is the most common reason a grid looks empty. Under the hood, each rolled-up cell maps to a ForecastingItem record, so reports and the API can read the same totals the grid shows. Setting the hierarchy correctly is the first configuration step, before forecast types are even switched on.
Forecast categories and the commit decision
Forecast Category is a field on the Opportunity that decides which grid column a deal lands in. The standard values are Pipeline, Best Case, Commit, Omitted, and Closed. Each value defaults from the opportunity stage through a mapping the admin controls, but a rep can override it without touching the stage. That decoupling is the point. Stage tracks where a deal sits in the sales process, while category tracks how confident the rep is that it will close this period. Pipeline includes nearly everything open, Best Case is the optimistic number, and Commit holds only the deals the rep is willing to stand behind. Omitted drops a deal out of the forecast entirely. In Lightning Experience an admin can add a Most Likely category and can rename the standard categories to match the language a team already uses. The commit number is what a manager reads in a forecast call, so training reps to set category by judgment, not just by stage, is what makes the whole feature trustworthy.
Forecast types and parallel views
A forecast type pairs a measure with a source. The measure is revenue or quantity, and the source is Opportunities, Opportunity Splits, Opportunity Product Families, Product Date, Overlay Splits, or a custom currency or number field on the Opportunity. An org can have up to four active pipeline forecast types at one time, and Salesforce Customer Support can raise that ceiling on request. Users switch between active types with a dropdown above the grid. A common setup runs Opportunity Revenue for booked dollars alongside Opportunity Product Quantity for unit volume, so one team forecasts money while another forecasts shipments off the same records. Each type is stored as a ForecastingType record and produces its own independent grid, categories, adjustments, and quotas. Multiple types let a business model several angles without splitting reps into separate processes or cloning the opportunity object. Revenue and quantity forecasts can even run together, and a rep can adjust each one separately when both are enabled.
Single-category and cumulative rollup methods
Collaborative Forecasts offers two ways to total the categories, and the choice changes how every column reads. The single-category rollup method shows each category on its own. The Commit column counts only deals marked Commit, and Best Case counts only deals marked Best Case, with no overlap between them. The cumulative rollup method instead adds the more-confident categories together. A cumulative Commit column shows Commit plus Closed, and a cumulative Best Case column shows Best Case plus Commit plus Closed. Cumulative columns answer a different question, namely the full amount a rep could reasonably land if a category and everything above it comes in. Salesforce lets an admin rename the rollup columns under either method so the labels read naturally for the team. The method is set once for the org and applies to every forecast type. Picking the wrong one quietly skews every conversation, so confirm which mental model your managers use before you flip the switch.
Adjustments and the audit trail
Managers and reps can change a forecast total directly on the grid without editing any opportunity. A manager who thinks a rep is sandbagging can raise the Commit number, and a rep who knows a deal will slip can lower it. Salesforce stores each change as a ForecastingAdjustment record, which is separate from the rolled-up opportunity totals. That separation is deliberate. The grid can show the raw number the pipeline implies, the adjusted number a person committed to, and the difference between them, all at once. Reports can then track how often a manager overrides their team and by how much, which is useful coaching data. Adjustments are tied to a forecast period and do not carry into the next one, so each period starts from the clean pipeline number unless a fresh adjustment is entered. The ForecastingAdjustment object is available through the API for orgs that want to analyze adjustment behavior or feed it into a revenue review outside the standard grid.
Quotas, attainment, and the Einstein overlay
A quota is the target a rep or manager is expected to hit in a period. Quotas live on the ForecastingQuota object, one record per user per period per forecast type, and they appear as their own row on the grid so attainment percentages render automatically next to the live numbers. Teams usually load quotas once a quarter through the Forecasts settings page or with Data Loader, and the Manage Quotas permission gates who can create or change them. Without quotas the grid still functions, but every attainment dashboard reads blank. On top of the human numbers, Einstein Forecasting can overlay a machine-learning prediction. It studies past opportunities, related account records, history, activities, and each owner's annual win rate, then projects a number with a confidence range and the top factors behind it. Einstein Forecasting ships with Sales Cloud Unlimited or as a Sales Cloud Einstein add-on, and a manager reads it next to the rep's commit to judge whether that commit looks conservative or a stretch.
From Customizable Forecasting to today
Forecasts has a long lineage. The original Classic forecasting gave way to Customizable Forecasting, which Salesforce then retired in the Summer '20 release, roughly July 2020. After that retirement, orgs lost access to Customizable Forecasting and its data, and Collaborative Forecasts became the supported path. Collaborative Forecasts added capabilities the old product never had, including custom currency-field forecasts, adjusted amounts, and the parallel forecast types described above. Orgs that had stayed on the legacy product needed a planned migration to map quotas, hierarchies, and category habits onto the new model, and many paired that move with the shift from the old Territory Management to Enterprise Territory Management. Today the conversation has moved on again. Salesforce now positions Pipeline Inspection and Revenue Intelligence as the analytics layer that sits beside the forecast grid, giving managers waterfall views of how the number changed week to week. Collaborative Forecasts remains the engine that produces the committed number, and the newer tools explain how that number moved.
Setting up Collaborative Forecasts
Collaborative Forecasts is turned on and shaped in Setup. An admin enables the feature, sets the period and hierarchy, then activates the forecast types and rollup method the sales team will read. Do these in order, because the grid only populates once the hierarchy and at least one active type line up.
- Enable Forecasts
In Setup, open Forecasts Settings and enable Forecasts. Choose the forecast period, either monthly or quarterly, and the date range users will see. This step also exposes the Forecasts tab to assigned profiles.
- Set the forecast hierarchy
Open the Forecasts Hierarchy page and confirm every manager and rep has a role and a forecast manager above them. Enable each person who should see a forecast. Gaps here are the top cause of an empty grid.
- Activate forecast types
Add up to four pipeline forecast types. Pick a measure (revenue or quantity) and a source (Opportunities, Splits, Product Families, a custom field) for each, then map opportunity stages to forecast categories.
- Choose the rollup method and load quotas
Select single-category or cumulative rollups for the org and rename columns if needed. Then load ForecastingQuota records per user and period so attainment percentages appear on the grid.
Monthly or quarterly buckets, plus how many periods forward and back the grid displays.
Revenue (a currency amount) or Quantity (a unit count) for each active forecast type.
Opportunities, Opportunity Splits, Product Families, Product Date, Overlay Splits, or a custom Opportunity field.
Single-category columns that stand alone, or cumulative columns that add the more-confident categories together.
- An empty grid almost always traces to a hierarchy gap. Confirm every rep has a role and an enabled forecast manager before debugging anything else.
- The four-active-type cap applies per org. Deactivate an unused type before adding a new one, or open a case with Salesforce Customer Support to raise the limit.
- Adjustments do not roll into the next period. A commit you entered this quarter is gone next quarter unless you re-enter it.
- Quotas drive attainment dashboards. If those dashboards read blank, the usual cause is missing ForecastingQuota records, not a reporting bug.
Trust & references
Cross-checked against the following references.
- Collaborative Forecasts OverviewSalesforce
- Pipeline Forecast TypesSalesforce
Straight from the source - Salesforce's reference material on Forecasts.
- Customize Pipeline Forecast CategoriesSalesforce
- ForecastingAdjustment Object ReferenceSalesforce
Hands-on resources to go deeper on Forecasts.
About the Author
Dipojjal Chakrabarti is a B2C Solution Architect with 29 Salesforce certifications and over 13 years in the Salesforce ecosystem. He runs salesforcedictionary.com to help admins, developers, architects, and cert/interview candidates sharpen their fundamentals. More about Dipojjal.
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