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Pipeline Analytics

How to Run a Pipeline Gap Analysis Mid-Quarter

Pete Furseth 7 min read
pipeline gap analysispipeline coveragesales pipelinerevenue operations
How to Run a Pipeline Gap Analysis Mid-Quarter
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A pipeline gap analysis answers two questions that most revenue teams conflate: how large is my pipeline shortfall relative to quota, and why. The first question is arithmetic. The second is diagnostic. Teams that only answer the first question respond to every pipeline shortfall the same way, by generating more pipeline, when the real problem is often pipeline quality, not quantity. Running a structured pipeline gap analysis separates the two.

Step 1: Calculate the Precise Pipeline Deficit

Start with the arithmetic. You need three numbers:

Remaining quota. Take your full-quarter quota and subtract closed-won revenue to date. This is the revenue you still need to close before quarter end. Expected close from current pipeline. Multiply each deal in your pipeline by its stage-based close probability. Do not use rep estimates; use your historical close rate by stage. Sum the results to get your weighted pipeline value. The gap. Subtract expected close from remaining quota.

``` Pipeline deficit = Remaining quota - (Sum of deal value × Stage close rate for all open deals) ```

If remaining quota is $500,000 and your weighted pipeline produces an expected close of $320,000, your deficit is $180,000.

This tells you the scale of the problem. It does not tell you the cause.

Put this to work on your numbers
Run your own numbers with the free Pipeline Velocity Calculator, then see how ORM builds it into a custom model.

Step 2: Calculate Your Effective Pipeline Coverage

Pipeline coverage tells you how much total pipeline you need to reliably hit quota given your historical close rates. It is the ratio of pipeline value to quota.

``` Pipeline coverage = Total open pipeline value ÷ Remaining quota ```

If you need a certain coverage ratio to be on track (typically calculated from your historical win rate), you can immediately identify whether you are above or below that threshold. See pipeline coverage for a detailed breakdown of how to set the right coverage target for your business.

A coverage ratio below your historical requirement is a volume problem. You do not have enough deals regardless of their quality. A coverage ratio above your historical requirement but with a persistent deficit is a quality problem. The math says the pipeline should be enough, but something about those specific deals is not converting at historical rates.

This distinction determines your recovery path.

Step 3: Diagnose Volume Gap vs. Quality Gap

Run four diagnostic checks to determine whether the gap is volume, quality, or both.

Check 1: Pipeline age distribution. Pull all open deals and look at their age in the current stage. Deals that have been sitting in the same stage for significantly longer than your average time-in-stage are unlikely to close this quarter at their assigned probability. Adjust their expected close down or remove them from the near-term forecast. Check 2: Next step completeness. What share of your pipeline deals have a logged next step with a date in the next 14 days? Deals without a concrete next step are not active deals. They are wishful entries. Remove them from your coverage calculation. Check 3: Champion and stakeholder engagement. For deals in late stages, when was the last documented engagement with the economic buyer, separate from the champion? Late-stage deals without economic buyer engagement in the last 30 days have a materially lower close probability than their stage suggests. Check 4: Single-threading. How many of your late-stage deals involve only one contact at the buying company? Single-threaded deals are fragile. If the contact goes dark or leaves, the deal stalls. High single-threading in your late-stage pipeline is a quality signal.

After these four checks, recalculate your adjusted coverage. The adjusted number, which strips out stale, unengaged, and single-threaded deals, is your real pipeline coverage.

Step 4: Determine the True Gap Type and Recovery Action

ScenarioDiagnosisRecovery Action
Adjusted coverage below thresholdVolume gapNew pipeline creation: targeted outbound, accelerated inbound, partner referrals
Adjusted coverage above threshold, gap persistsQuality gapDeal inspection and acceleration: multi-thread existing deals, advance stalled ones, prune and replace unrealistic ones
Both below threshold and quality issuesCombined gapPrioritize quality fixes in existing pipeline first; parallel new pipeline creation
For a volume gap, the recovery actions are pipeline creation: targeted outbound campaigns to high-fit accounts, acceleration of inbound response times, referral activation, or engaging existing customers for expansion opportunities. The question is whether you can generate enough new pipeline in the remaining weeks to make up the shortfall given your average sales cycle length. If your average cycle is longer than the remaining quarter, new pipeline creation will not close this quarter. You need to accelerate existing deals or accept the miss.

For a quality gap, the recovery actions are inspection and acceleration of existing deals. Multi-thread by introducing additional contacts at stalled accounts. Ask reps to run a mutual action plan with every deal over a threshold value. Prune deals that are genuinely not real and redirect rep time to higher-probability opportunities. The sales capacity gap framework is relevant here when the quality issue is also connected to rep bandwidth and prioritization.

Step 5: Build and Communicate the Recovery Plan

A gap analysis without a recovery plan is a diagnostic report, not an action. The recovery plan has three components:

Specific actions with owners and deadlines. Not "generate more pipeline" but "outbound sequence to 40 named accounts in the enterprise segment, owned by SDR team, first email by day 2, review by day 7." Each action should have a single owner and a specific completion date. Expected impact per action. Estimate the pipeline value each action is expected to generate or recover, using conservative assumptions. This allows you to assess whether the plan, if executed, closes the gap or only partially closes it. Weekly checkpoint. A mid-quarter gap analysis should produce a weekly check-in to track whether recovery actions are executing and whether the gap is narrowing. If actions are not executing on schedule, adjust the plan, not the forecast.

Common Mistakes

Using rep-estimated close probabilities instead of stage-based rates. Reps are optimistic by default. Stage-based historical rates produce a more accurate expected close figure. Failing to separate volume from quality. Responding to a quality gap with pipeline creation events adds more low-quality deals to an already unreliable pipeline. Diagnose first. Running the analysis too late to act. A gap identified in week 11 of a 13-week quarter cannot be recovered through new pipeline. Run the analysis at week 4 to 6 when recovery actions still have time to work. Not stripping stale deals from the coverage calculation. Coverage that includes obviously dead deals is false comfort. Adjusted coverage, which removes stale and unengaged deals, is the number worth acting on.

Frequently Asked Questions

What is a pipeline gap analysis?

A pipeline gap analysis is a structured diagnostic that compares your current pipeline to what you need to hit your quota, then isolates the root cause of any shortfall. It answers two sequential questions: how large is the gap, and is that gap caused by insufficient pipeline volume, insufficient pipeline quality, or both. The distinction matters because the recovery actions are different.

When should you run a pipeline gap analysis?

Run a pipeline gap analysis at the start of each quarter to establish a baseline, and again at the midpoint of the quarter when you still have time to take meaningful action. A gap identified in the final month of a quarter can rarely be recovered through new pipeline creation. Identifying it at week four or five gives you enough runway to accelerate existing deals or close coverage gaps through targeted outbound.

What is the difference between a volume gap and a quality gap in pipeline?

A volume gap means you do not have enough deals in the pipeline to hit quota even if everything converts at historical rates. A quality gap means you have enough deals by count or value, but the conversion rates on those deals are lower than historical norms, often because the pipeline contains stale, low-fit, or uncommitted deals. Volume gaps require more pipeline creation. Quality gaps require deal inspection and pruning.

Frequently Asked Questions

What is a pipeline gap analysis?

A pipeline gap analysis is a structured diagnostic that compares your current pipeline to what you need to hit your quota, then isolates the root cause of any shortfall. It answers two sequential questions: how large is the gap, and is that gap caused by insufficient pipeline volume, insufficient pipeline quality, or both. The distinction matters because the recovery actions are different.

When should you run a pipeline gap analysis?

Run a pipeline gap analysis at the start of each quarter to establish a baseline, and again at the midpoint of the quarter when you still have time to take meaningful action. A gap identified in the final month of a quarter can rarely be recovered through new pipeline creation. Identifying it at week four or five gives you enough runway to accelerate existing deals or close coverage gaps through targeted outbound.

What is the difference between a volume gap and a quality gap in pipeline?

A volume gap means you do not have enough deals in the pipeline to hit quota even if everything converts at historical rates. A quality gap means you have enough deals by count or value, but the conversion rates on those deals are lower than historical norms, often because the pipeline contains stale, low-fit, or uncommitted deals. Volume gaps require more pipeline creation. Quality gaps require deal inspection and pruning.

PF
Pete Furseth
ORM Technologies
Pete has built custom revenue forecast models for B2B SaaS companies for over a decade.

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