VP Sales Operations
Pipeline Command Center
The VP was pulling pipeline analysis from Salesforce by hand. Cross-deal comparisons took her days. I built a system that does it in an hour. Two sessions later, she was building her own tools.
Days → 1 Hour
Pipeline analysis time
The problem
Pipeline analysis meant pulling Salesforce reports by hand, cross-referencing in spreadsheets, and hoping nothing changed by the time you presented it. Week-over-week trend comparisons didn't exist in standard reporting.
What I built
A command center that reads Salesforce data on open, scores every deal for stall risk, detects recycling loops, and ranks weekly priorities by seller. One artifact. Refreshed on open.
What happened
Two sessions in, she built her own tools in her own environment. Seven revisions to the shared data standard in a single week, all driven by her. She opens it every Monday.
Open Pipeline
$109M
Open Deals
123
Win Rate
4.1%
Avg Days in Pipe
187d
Patterns
Sellers
Stall Pattern
81%
of deals die at the Interested stage. They never get past initial engagement.
Silent Loss
46%
of closed-lost deals went quiet. Not product rejection. Just silence.
Slow Death
201 days
average time a dead deal sits open before someone closes it out.
Recycling Loop
3.2x
average times an account gets re-opened. Same account, same result.
| Seller | Pipeline | Deals | Avg Age | Stall Risk | |
|---|---|---|---|---|---|
| Seller A | $14.2M | 18 | 142d | 4 at risk | View deals → |
Acme Health Plan Pacific Payer Group Cascade Regional Mountain West Health | |||||
| Seller B | $9.1M | 12 | 210d | 6 at risk | View deals → |
Heartland Mutual Southern Benefits Corp Great Lakes Health Pinnacle Care Systems | |||||
| Seller C | $7.6M | 9 | 98d | 1 at risk | View deals → |
Coastal Health Network Metro Alliance Plan Frontier Benefits | |||||
"This makes me sad inside, because I have taken like days to do some of this analysis in the past."
VP Sales Operations
2
sessions to self-serve
Account Executives
Deal Command Center
AEs were pulling account context from five different systems. By the time they had something usable, it was stale. This gives them deal-level intelligence in 15 minutes, refreshed daily.
Day 1 Productive
New reps, no walkthrough
Account research was scattered across Salesforce activity logs, Slack threads, call recordings, and PDF downloads. AEs either spent days assembling context or went into calls without it. Two reps picked up the system independently and produced account-specific deliverables on their first day. Nobody walked them through it.
Stall Alerts
Deal Detail
History
Next Actions
Regional Health Plan · 47 days no activity
Last touch: Discovery call Mar 28. VP Clinical Ops attended but no follow-up was sent. Previous opp on this account closed-lost Jun 2024 after going quiet post-demo. Account has been opened 3 times.
National Payer Group · Advancing
Stage moved to Evaluation last week. Technical review Thursday. CTO and VP Digital both confirmed. Prep the integration architecture walkthrough.
Midwest Employer Alliance · 28 days no activity
Champion went on leave. No backup contact identified. $2.1M at risk. Recommend reaching out to VP Benefits directly with a new thread.
Southeast Health Partners · 62 days no activity
Went dark after pricing discussion. CFO raised budget concerns in last call. No executive sponsor identified. This matches the silent loss pattern (46% of losses).
Regional Health Plan · $3.8M
Stage
Interested (47d)
Deal Age
182 days
Prior Opps
2 (both closed-lost)
Times Recycled
3x
Champion
Dir. Member Experience
Exec Sponsor
None identified
Research Time
~15 min
Closed-Lost Intel
23 prior opps org-wide
Regional Health Plan · Interaction History
Mar 28, 2026
Discovery call. VP Clinical Ops + Dir. Member Experience attended. Discussed app fragmentation and member engagement gaps. No follow-up sent.
Feb 12, 2026
Opp re-opened (3rd time). New AE assigned. Initial outreach to Dir. Member Experience via warm intro from partner channel.
Jun 2024
Previous opp closed-lost. Went quiet after demo. No objection logged. Matches silent loss pattern.
Nov 2023
First opp created. Early-stage exploration. Closed after 90 days with no activity past initial meeting.
Urgent
Regional Health Plan: Send VP Clinical Ops a follow-up referencing the app fragmentation discussion from Mar 28. 47 days without contact on a 3x recycled account.
Urgent
Southeast Health Partners: Re-engage above the CFO. Budget objection without an exec sponsor means this deal dies quietly. Find the business owner who feels the pain.
This week
National Payer Group: Prep integration architecture walkthrough for Thursday technical review. CTO + VP Digital confirmed. Best deal in the portfolio right now.
This week
Midwest Employer Alliance: Champion on leave. Reach out to VP Benefits directly. Frame as continuity, not escalation. $2.1M pipeline at risk with no backup thread.
"We don't waste opportunities. We don't waste moments reaching out to people we just talked to six months ago because the person reaching out now doesn't have that context."
VP Sales Operations
15 min
vs. days of research
Account Management
Health Command Center
Customer health lived in a spreadsheet updated when someone remembered. The AM team needed structured scoring that combined data with expert judgment.
10 Pillars · 3 Tiers
19 accounts scored
"In the pre-sales world, 70% of information is enough. In the customer world, if we fundamentally get something wrong, we look really dumb."
AVP Account Management
This changed how I built the system. I put the data foundation layer in place before building any action tools. Different users have different accuracy tolerances, and the system has to know the difference.
Portfolio Health
Click any row to expand
Account
Core Health
Leading Indicators
Environment
Score
National Payer A
G
G
Y
G
Y
G
G
G
8.2
Regional Plan B
Y
Y
R
Y
R
Y
Y
G
4.8
State Medicaid C
R
Y
R
R
Y
Y
R
Y
2.9
Enterprise D
G
G
G
G
G
G
Y
G
9.1
"What I loved most is you built those pillars of data. The data layer. That's the most compelling piece."
AVP Account Management
19
accounts scored
The System
How it works
12 production tools across 5 departments. 30+ documented skills. 150% of Q1 quota while building all of it. No department was pitched. Every one came to me.
5 Departments
organic adoption
Architecture
Pipeline Command Center, Deal Command Center, Health Command Center, and 9 more across Marketing, Product Marketing, and Marketing Ops. Each reads from the shared data layer. Update a skill once and it pushes to every user via the plugin system. No manual setup per person. No version drift between teams.
Each skill does one thing. When they try to do too much, they break. The AVP of Account Management learned this the hard way and rebuilt his from scratch using this architecture. One input, one output, one job. Version-controlled with playbooks so any new user can understand what a skill does without asking the person who built it.
The system tells you when input data is wrong instead of producing output that looks right. Pre-sales users tolerate 70% accuracy. Post-sales users need close to 100%. The quality gates are calibrated per persona. I documented every failure mode I encountered, categorized them, and built checks for each one. If the data isn't trustworthy, the tool says so.
40 foundational documents. Salesforce connector pulling live data. A shared data standard at v7, driven through 7 revisions in one week by the VP who uses it daily. A verified metrics repository (v3) with sourcing rules for every data point, built after I saw teams citing numbers nobody could trace back to a source. Every tool reads from this layer. Everything above it depends on it being right.
How it spread
VP Sales Operations
Built for one person's painful workflow. She used it every Monday. Two sessions later, she was building her own tools in her own environment.
Account Executives
Her team asked for seller-level versions. Two reps productive on day one with no walkthrough.
Account Management
AVP saw the BD data layer and requested his own. Rebuilt his skills from scratch using the architecture I showed him.
Marketing
Demo ran 13 minutes over the scheduled 30 from questions. Product Marketing and Marketing Ops followed up independently.
Executive Leadership
CEO shared the system documentation to the executive leadership channel. I never sent it to him.
The tools were the easy part. Getting the data right was most of the work. Getting people to trust the output was the rest. Every company deploying AI to non-technical teams will run into these same problems in the same order.
Dallas Andrews · 2026 · About