Proof

Proof from real post-sale operating work.

A few examples of the kinds of systems, frameworks, and operating improvements I build with SaaS teams.

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Example 01

Onboarding visibility across 100+ accounts

Situation

A SaaS post-sale team was managing a large onboarding portfolio without a consistent way to see which accounts were at risk, which were stalling, and where leadership attention was most needed. Visibility was reactive. Intervention happened after problems surfaced, not before.

What Was Built

An onboarding visibility layer designed to surface ARR-weighted risk, overdue action items, and intervention priorities across the full portfolio. The system gave leadership a structured view of where each account stood and what needed to happen next. The system was designed to support weekly portfolio reviews, making it easier to decide where leadership attention was needed first.

Why It Mattered

The team was flying blind on a large book of business. Without a consistent risk model, high-ARR accounts could stall quietly while lower-priority accounts consumed disproportionate attention.

Operating Impact

Leadership gained a reliable weekly view of onboarding health, enabling proactive intervention instead of reactive firefighting. The visibility layer became the operating foundation for team reviews and escalation decisions. Work like this supported broader efforts to reduce average time to launch and improve leadership visibility into onboarding risk.

Onboarding visibility across 100+ accounts illustration
Example 02

Fixing handoff quality and first-value measurement

Situation

A post-sale team was experiencing consistent delays between contract close and customer first value. The handoff from Sales to CS was inconsistent, missing key context, and creating rework. There was no shared definition of what first value meant or how to measure it.

What Was Built

A handoff quality scoring model that evaluated each handoff against a binary checklist of required inputs. A first-value and full-value milestone framework that gave the team a shared language for measuring progress and identifying where delays were occurring. The scoring model made handoff quality visible before kickoff, so weak inputs could be corrected earlier instead of creating downstream rework.

Why It Mattered

Without a consistent handoff standard, CS teams were starting every engagement from scratch. Without a milestone model, there was no way to know whether delays were happening in onboarding, adoption, or somewhere in between.

Operating Impact

Handoff quality became measurable and improvable. The team could identify which sales reps were producing weak handoffs and address the root cause. First-value measurement gave leadership a leading indicator of onboarding health instead of waiting for churn signals. In practice, this kind of operating discipline helped reduce lag between close and kickoff from 5 days to under 3.

Example 03

Services margin visibility and premium-hours control

Situation

A Professional Services team was struggling to understand where team time was going, which accounts were consuming disproportionate capacity, and whether premium services hours were being used as contracted. Margin leakage was suspected but not quantified.

What Was Built

A services reporting system that tracked utilization by workstream, flagged customer concentration risk, and surfaced contract-hours overrun signals before they became billing or margin problems. The system included a governance model for premium services hours.

Why It Mattered

Without visibility into utilization and concentration, the team could not make informed decisions about staffing, account prioritization, or premium services enforcement. Margin problems were discovered after the fact. This work builds on the same operational thinking used to reduce onboarding-related costs and create better control over delivery efficiency.

Operating Impact

The team gained early warning signals for margin leakage and capacity pressure. Leadership could see which accounts were consuming outsized resources and act before the situation became a delivery or financial problem. Managers could use the reporting to spot overrun risk earlier, rebalance attention across accounts, and make cleaner capacity decisions before the problem spread.

Services margin visibility and premium-hours control illustration
Example 04

Partner enablement without LMS bloat

Situation

A SaaS company needed partners to deliver onboarding and implementation work consistently, but lacked a structured way to certify partner readiness or enforce delivery standards. Internal teams were spending significant time cleaning up inconsistent partner work.

What Was Built

A gated certification and enablement system designed to improve partner readiness and reduce internal cleanup work. The system included a curriculum structure, role clarity model, assessment framework, and governance guidance, without requiring a full LMS implementation. This approach is grounded in real partner enablement work that reduced delivery costs by 15% while expanding implementation team capacity.

Why It Mattered

Inconsistent partner delivery was creating customer experience problems and consuming internal capacity. Without a certification structure, there was no way to enforce readiness standards or hold partners accountable.

Operating Impact

Partners had a clear path to certification. Internal teams had a consistent standard to reference when evaluating partner readiness. The system reduced the ambiguity that was driving cleanup work and created a foundation for scaling the partner channel. The result was not just a portal. It was a clearer partner readiness standard and less internal cleanup work after partner-led delivery began.

What This Work Has in Common

What all of this work has in common

Built from real post-sale operating experience inside SaaS

Designed for operator use, not presentation value

Focused on speed, visibility, and better decision-making

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Need this kind of clarity in your own post-sale motion?

The first step is getting clear on what the real bottleneck is. That is what the fit call is for.