Results & Case Studies

Operating outcomes,
not advisory theater.

The work spans AI governance, PE operating partnership, and fractional product leadership. The pattern is the same in each case: tighter accountability, faster execution, and measurable operating improvement.

$1.2B
P&L managed directly
as GM at CDW
~50
Organizations advised
from startup to Fortune 100
5
Published works across AI,
product, and strategy
5x
Founder exit return
on initial investment
25+
Years leading product,
AI, and transformation
Case Studies

Selected Engagements

Client identities are kept confidential. Outcomes, timelines, and context are accurate.

AI Governance · PE Portfolio Company
Mid-market SaaS company needed an AI governance framework before a Series C and potential acquisition process
~$90M ARRB2B SaaS
60-day engagementGovernance Assessment

The Situation

The company had deployed six AI initiatives across product and operations over 18 months. None had formal governance. Two had potential GDPR exposure. The board was aware but hadn't acted, because they didn't have a framework for what acting even meant. With an acquisition process likely in 12 months, due diligence risk was real.

What We Built

Full AI Readiness Index across all six initiatives, classified by trust tier and risk surface

Decision rights framework adopted as board policy with clear accountability mapping

Two high-risk AI deployments remediated before due diligence opened

Board AI literacy program with measurable improvement in GP confidence scores

Governance framework cited positively in acquisition due diligence report

PE Operating Partnership · Portfolio Company Leadership
PE-backed business services company needed a product and technology operating partner to execute the investment thesis
$220M RevenueBusiness Services
12-month engagementEmbedded Operating Partner

The Situation

The investment thesis depended on AI-enabled product differentiation that the existing leadership team lacked the capability to execute. The company was 18 months post-acquisition with a stalled product roadmap, unclear technology ownership, and a board that had lost confidence in the CEO's ability to deliver the tech agenda.

What We Built

New product and technology org structure with clear accountability, implemented in 45 days

AI operating model integrated into core service delivery instead of a parallel track

Product roadmap rebuilt and delivered to the board with 18-month visibility

Three senior hires made: VP Engineering, Head of AI, and Head of Product

12-month revenue impact from AI-enabled product features: greater than 15% improvement in retention

Fractional CPO · Technology Company
Growth-stage technology company bridged a CPO departure while rebuilding the product organization for scale
$45M ARRSaaS / Infrastructure
9-month engagementFractional CPO

The Situation

The CPO departed unexpectedly during a critical product cycle. The company was three months from a major launch with a demoralized product team, no clear direction on two contested strategic decisions, and investors watching closely. The CEO needed a senior operator who could step in with authority immediately, not a consultant with a 90-day discovery phase.

What We Built

Product team stabilized within 30 days with no additional attrition during the engagement

Launch delivered on schedule, the first major product release in 18 months to hit target date

Two contested strategic decisions resolved with board alignment

Permanent CPO search run in parallel and hired in month seven with a clean transition

Product operating model rebuilt so the new CPO inherited a functioning structure from day one

What clients say

In their words.

"

The governance framework Joe built gave our board a real basis for AI decisions, not just confidence theater. Two board members specifically cited it in our post-acquisition review as a differentiator in due diligence.

Managing DirectorPE Firm, Mid-Market Focus
"

He doesn't give you a deck and leave. He stays until the thing actually works. That's rare at this level. Most advisors optimize for the relationship, not the outcome. Joe optimizes for the outcome.

CEOPE-Backed Business Services, $220M Revenue
"

We needed someone who could walk into a room of skeptical senior engineers on Monday and have their trust by Friday. Joe did that. The team was better for having him, not just the product.

Founder & CEOGrowth-Stage SaaS Company
The Pattern

What I see across every engagement.

After 20-plus years of product leadership and a growing number of PE and advisory engagements, the failure modes are consistent. They're not random. And they're almost always fixable when you catch them before they become audit findings or missed targets.

This is the pattern I look for in every discovery call. If any of these sound familiar, the engagement is probably worth having.

01
Governance follows investmentCompanies deploy AI first and figure out governance when something breaks. The framework I build reverses that sequence.
02
Accountability is assigned to technology, not people“The AI decided that” is not accountability. Every engagement starts by mapping who actually owns each outcome.
03
The board and the operating team have different mental models of AI maturityThe board thinks they're further along than they are, or they're more skeptical than the data warrants. Either way, the gap costs time and money.
04
The operating model hasn't changed to absorb the AICompanies deploy AI tools into the existing org structure and wonder why adoption is low. The org needs to change, not just the tools.
05
No one is measuring what the AI is actually doing to the businessSpend is tracked. Outcomes aren't. The board reporting template I build solves this in the first engagement deliverable.
Let's talk

Tell me what you're trying to solve.
I'll tell you what I see.

Discovery calls are 30 minutes. No pitch. If I can help, I'll say exactly how. If I can't, I'll tell you that too.