Case Study
SaaS Ecosystem
Discovery & Triage
Engagement Duration
30 Days

Engagement Type
Discovery & Advisory

Industry
Delivery Management SaaS
Company
PE-backed SaaS3-product ecosystem
Annual Revenue
~$2.5M ARRPrimary product · 78 clients
Presenting Problem
Unclear product strategy, cost pressure, team in flux
01 The Situation

A PE-backed software company operating three complementary SaaS products had reached an inflection point. A key engineering team had just been offboarded, a new CEO was in seat, and the business was spending $1.55M annually to run its core product — at a gross margin 11 points below industry standard. Leadership had no clear view of which product warranted investment, where costs were leaking, or what the path to profitability looked like.

A 30-day discovery was scoped to assess the commercial and technical state of the business, surface what was actually broken, and provide a prioritized path forward.

02 What Was Found
Revenue Concentration

One product drove 2/3 of total ecosystem revenue. Engineering resources were spread roughly equally across all three.

Infrastructure Bleed

$53K/month in EC2 spend. A viable migration path existed that would reduce costs 20–60% — unidentified and unscoped.

Technical Debt Compounding

The core product ran on ~24 single-tenant instances — each a copy of the last. Every release made the problem worse.

Live Security Exposure

100+ fraudulent accounts created in 48 hours. No mitigation in place. A 1-month fix existed; no one had flagged the risk.

Knowledge Hostage Risk

Siloed teams held critical product knowledge with no documentation or cross-training. One departure away from a crisis.

Misallocated Talent

A former PM who had previously consolidated the product from 100 to 24 instances was available to rehire — unknown to leadership.

"The analysis confirmed what no one had quantified: one product was carrying the business. The rest was a resource drain with a roadmap attached."
03 Documented Impact

The following figures represent value created or preserved through recommendations made during the engagement. None required implementation to realize — they were the direct result of identifying what the business didn't know.

Value Driver Basis Estimated Value
Infrastructure cost reduction
EC2 migration scoped and recommended
$53K/month spend; 20–60% reduction projected upon .NET Core migration $127K–$381K/yr
Engineering reallocation
Resources redirected to revenue-generating product
$709K annual staffing cost; ~20% previously misallocated to low-revenue products ~$142K/yr
Avoided hosting overhead
Multi-tenant migration path identified
$836K annual hosting; 15% reduction from consolidation roadmap ~$125K/yr
Talent risk averted
Former PM re-engaged; zero ramp time
Avoided mis-hire or vacancy at senior PM level; 1.5–2x salary in avoided cost $150K–$260K
Security exposure mitigated
Live breach risk flagged and remediation scoped
Active fraud in production; breach cost at this company scale estimated $500K+ Risk avoided
Total identified value $544K–$908K
04 What Was Delivered

A 50-page discovery report covering: financial model and GPM analysis by product, competitive landscape, full risk and assumptions register, product roadmap assessment, org structure recommendations, technical architecture path, and a prioritized set of next steps for the 30/60/90-day horizon.

The report created stakeholder alignment where none had existed — giving the new CEO and the PE sponsor a shared, evidence-based view of what to fix first and why.

March 2023

This engagement was completed one month after ChatGPT's public launch — before AI-assisted research, synthesis, or document generation was a practical reality. The competitive analysis, financial modeling, risk mapping, and architectural assessment were done by hand, at speed, across a globally distributed team and three codebases simultaneously.

The work holds up not because the tools have changed, but because the tools were never the point. Triage is a judgment call. It always has been.