You are doing enough work. You are not reaching enough decision-makers.
Your call volume is 104% of benchmark, but decision-maker reach is 9.8% versus an 18% benchmark. Once you reach the right person, your meeting conversion is healthy.
Observed1,040 calls · 102 decision-makersCalculated9.8% reach rateInterpretedFirst material deviationRecommendedTest timing first
Cost of leaving it unfixed
92 calls/dayrequired to book 3 meetings at your current rates
50 calls/dayrequired at benchmark
Your revenue production line
Every stage, actual versus benchmark
Select a stage to audit the evidence
What this means
The first meaningful gap is decision-maker reach. Every downstream conversion is near or above benchmark, so asking you to “close harder” would attack the wrong part of the system.
Next controlled experiment
Test timing before changing your script
01
Move 20 comparable calls per day into the 3–5 PM block for five selling days. Hold the account list, message, and total volume constant.
ChangeCall window
Hold constantList · script · volume
Decision point100 attempts
Why timing is the first hypothesis
Reach rate by call window
8–10 AM6.2%
10–12 PM8.5%
1–3 PM10.8%
3–5 PM15.4%
This pattern is strong enough to test, not strong enough to call causal. Account mix and sample size still matter.
Data through Oct 8, 202650,000+ synthetic CRM activities analyzed · Salesforce-style export · 97% model readiness
Primary constraintHigh confidence
Proposal turnaround is restricting revenue
Qualified opportunity volume is healthy, but complex automation proposals now take more than twice as long to deliver. Activity is not the problem.
11.6days
Proposal cycle4.8-day historical baseline
Sales system
Where revenue is getting stuck
Rolling 90 days
!
More prospecting would increase congestion. Meetings are entering the funnel faster than technical proposals are leaving it.
Forecast
Revenue trajectory
+8.4% YoY
ActualTarget
Cause concentration
Where the delay lives
Activity health
Inputs remain strong
Healthy
Diagnostic brief
What to do next
✦
Add proposal capacity before asking the team for more pipeline. Start with automation packages in the Western territory.
Constraint analysis
Every stage has a number and a clock
Volume, conversion, and time are evaluated together. The constraint is the stage that most limits total revenue—not necessarily the metric that looks worst.
Full system
Revenue production line
Evidence
Constraint timeline
July 15Automation package launch increased engineering review demand.
Diagnostic logic
Why this—not activity
Individual diagnostics
One team does not have one problem
Each representative is measured against comparable work, personal history, and the revenue math—not a generic activity leaderboard.
Personal funnel
Maya Chen
Targeting constraint
Coaching brief
One constraint, one experiment
✦
Team comparison
Throughput by representative
Comparable rolling period
Representative
Territory
Activity
Meetings
Qualified
Wins
Revenue
Current constraint
Cohort analysis
Find where performance actually changes
Separate territory, product, source, and customer segment before prescribing a company-wide solution.
Comparative performance
Product family throughput
Selected finding
Automation packages
Constraint hotspot
Detail
Segment scorecard
Product family
Qualified
Proposals
Wins
Win rate
Cycle time
Revenue
Signal
Constraint economics
Model the fix before prescribing it
Change one operating assumption at a time and see its effect on annual wins, revenue, and required pipeline.
Assumptions
Operating levers
Modeled annual impact
+$552,000
Restoring proposal turnaround to five days creates more value than increasing outbound activity by 20%.
Recommended move
Add technical proposal capacity and simplify the automation-package approval path before adding more top-of-funnel volume.
CRM onboarding
Map any sales process into one diagnostic model
Start with a CSV export. Sales Throughput proposes field and stage mappings while raw records remain local to the browser.
No cloud upload
⇧
Drop a CRM export here
Activities, opportunities, or combined pipeline CSV
Mapping status
Waiting for a file
0 fields
↔
Load the sample export to see the configurable mapping workflow.
⌾
Designed for confidential sales data
The prototype analyzes files in the browser. A production AI layer would receive aggregate metrics—not customer names, pricing, transcripts, or raw opportunity records—unless an organization explicitly approved otherwise.
Raw CRM export→Local calculation→Sanitized metrics→Diagnostic narrative
1 of 4
Start with the output
Revenue is behind plan, but the cause is upstream.