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An opportunities dashboard compares open sales deals by stage, owner, age, and expected close date. This worked example shows the source fields, the calculations, the checks, and the decisions each exception should trigger.
An opportunities dashboard compares open deals by stage, owner, age, and expected close date. Its job is to direct a pipeline review toward specific customer commitments and exceptions. A large total means little until the team can see what is old, overdue, or concentrated in a few deals.
The core measures are open opportunity count, open amount, time since creation, time in the current stage, and expected closing period. Count reveals workload; amount reveals commercial exposure. Age and close dates reveal different timing problems, so show them separately.
Sales stages should reflect the company's own selling process. The Salesforce guide to sales pipelines describes stage sequences as varying by industry or sector and explains how stages help identify next steps. Use that principle to define your stage entry requirements before comparing owners.
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The opportunities view starts after a deal exists. For the earlier question of which conversations became pipeline, use meeting-to-opportunity conversion per rep. A low creation rate and a large but stalled pipeline need different management responses.
An illustrative US equipment supplier takes an open-opportunity snapshot on September 30, 2026. Amounts are USD. Every row represents one distinct opportunity, with the latest owner and stage recorded as of that date.
| Opportunity | Owner | Stage | Amount (USD) | Created | Current stage entered | Expected close |
|---|---|---|---|---|---|---|
| O101 | Mara | Qualified | 60,000 | July 2, 2026 | September 16, 2026 | October 15, 2026 |
| O102 | Mara | Proposal | 100,000 | August 1, 2026 | September 1, 2026 | September 25, 2026 |
| O103 | Deon | Negotiation | 80,000 | June 2, 2026 | September 10, 2026 | October 5, 2026 |
| O104 | Deon | Proposal | 40,000 | September 10, 2026 | September 25, 2026 | October 30, 2026 |
| O105 | Priya | Qualified | 20,000 | September 20, 2026 | September 20, 2026 | November 15, 2026 |
Also retain account ID, currency, status, next action, and next-action date in the source file. These fields let a reviewer identify the customer and test whether a sales step is actually agreed. If stage-entry dates are missing, report that limitation; last-modified date is not a substitute because an unrelated edit can change it.
Choose calendar days or business days and keep that choice stable. This example uses calendar days, excluding the creation or stage-entry day. It also uses the fixed snapshot date for every row rather than a changing current date.
Opportunity age = Snapshot date − Creation date
Stage age = Snapshot date − Current stage-entry date
Days past expected close = Greater of zero or Snapshot date − Expected close date
Applied to the source rows, those definitions give:
| Opportunity | Amount (USD) | Opportunity age (days) | Stage age (days) | Days past expected close |
|---|---|---|---|---|
| O101 | 60,000 | 90 | 14 | 0 |
| O102 | 100,000 | 60 | 29 | 5 |
| O103 | 80,000 | 120 | 20 | 0 |
| O104 | 40,000 | 20 | 5 | 0 |
| O105 | 20,000 | 10 | 10 | 0 |
| Total amount | 300,000 |
The average deal age is (90 + 60 + 120 + 20 + 10) / 5 = 60 days. That average counts every opportunity equally. An amount-weighted age answers a different question: how old is the pipeline dollar? It is (60,000 × 90 + 100,000 × 60 + 80,000 × 120 + 40,000 × 20 + 20,000 × 10) / 300,000 = 73.3 days, rounded to one decimal.
The older deals carry more value, which explains the difference. Neither average identifies a stalled deal by itself. O103 is older than O102, but O102 has spent longer in its current stage and has already missed its expected close date.
Use the same population to produce each view:
| View | Group | Open deals | Open amount (USD) |
|---|---|---|---|
| Stage | Qualified | 2 | 80,000 |
| Stage | Proposal | 2 | 140,000 |
| Stage | Negotiation | 1 | 80,000 |
| Owner | Mara | 2 | 160,000 |
| Owner | Deon | 2 | 120,000 |
| Owner | Priya | 1 | 20,000 |
Each view independently totals five opportunities and $300,000. Do not add the stage and owner sections together; they are different groupings of the same rows.
For this review, management defines an age review flag at 90 calendar days or more. O101 and O103 qualify: 60,000 + 80,000 = $140,000, or 46.7% of pipeline. That is a local review rule, not an industry benchmark. The manager still asks whether those ages are normal for each deal's buying process.
O102 is the only deal past its expected close date. Its $100,000 is 33.3% of pipeline. The remaining $200,000, or 66.7%, has close dates in the next calendar quarter. Percentages here divide the flagged amount by $300,000 and round to one decimal.
Mara should confirm whether O102 has a customer-approved next step and a credible revised date. A date move without new evidence merely pushes the same exception into the next review. The manager decides whether the opportunity remains qualified; the rep records the evidence.
Deon should check what remains before O103 can close and whether the expected date still fits the customer's approval process. Sales operations owns consistent stage definitions and missing-date checks. The sales manager owns escalation and review thresholds. Finance owns any reconciliation between closed bookings and recognized revenue.
Growth from existing customers needs an additional account lens. Expansion pipeline against whitespace tests whether the team is pursuing the identified gaps, while a B2B dashboard places opportunities beside account revenue and service activity. Keep those questions adjacent without crowding the deal review.
Start with the $300,000 open-deal total in the original export. Reconcile the stage and owner views to it, count distinct opportunity IDs, and investigate blanks before reading the averages. If the export contains repeated rows for opportunity products, aggregate those lines to the opportunity before counting deals.
Keep the source export with its extraction date and documented filters. The IRS recordkeeping guidance explains that business transactions generate supporting documents containing information used in the books. The same discipline is useful here: retain the underlying record instead of treating a summary as evidence on its own.
Upload a file or Google Sheet with opportunity IDs, amounts, owners, stages, and dates; Covirage maps the columns, and its tools compute and check the figures. The external AI model explains the results with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data.
See sales intelligence for the wider business review context.
Opportunity age measures elapsed days since the deal was created. Stage age measures elapsed days since it entered its current stage. An older deal can be progressing normally, while a recently created deal may already be stuck at a specific approval step.
Use open deals for the current pipeline view. Closed deals belong in a separately labeled outcome or conversion view with a defined closing period. Combining those populations makes open pipeline totals and current stage comparisons difficult to interpret.
Staleness depends on the sales process, stage, and customer buying cycle. Use a documented review threshold and evidence such as an overdue next step or missing customer commitment. Age alone should trigger investigation rather than an automatic lost-deal classification.
Weighted pipeline multiplies deal amounts by chosen probabilities. A forecast also requires judgment about timing, qualification, and what can close within the period. Keep raw opportunity amounts visible so probability assumptions do not hide a large or delayed deal.