Every company generates mountains of operational data. The patterns are there — the risks, the waste, the early warnings. But no one's looking at it as a whole. Here's what we found when we did.
Three companies. Three industries. All the findings below were sitting in systems those companies already owned. Nobody had connected them. What follows is what surfaced when we did — and what happened next.
Case Study 1 — 160-Person Professional Services Firm
Data ingested: Email archive, project tracker, CRM Time to first findings: 72 hours
Ghost Waste — $24,000/year in software nobody uses. Three subscriptions. Zero logins across all three in the prior 90 days. The licenses had auto-renewed. Nobody had been asked to review them. Nobody knew to ask. The annual cost was less than a rounding error in the budget — which is exactly how it survived three renewal cycles unnoticed.
Bus Factor — One project manager holding four active engagements together. She was running at seven times the average project load across the firm. She was the primary contact, the primary documenter, and in one case the only person who understood the client's integration requirements. None of the four clients had been introduced to a backup. If she'd taken two weeks off, all four projects would have stopped.
Root Cause — One vendor behind delays in four of six behind-schedule projects. The four delays had been tracked as four separate problems in four separate project records. No single system showed all four simultaneously. The vendor had been flagged as a blocker in each — but never as a pattern. It was one problem wearing four masks. We surfaced the co-occurrence. The firm's leadership decided how to act on it.
Revenue Decay — Three accounts, $847K ARR, showing pre-churn behavior. The behavioral footprint matched the two most recently churned accounts — same silence pattern, same contact drift. The last logged contact for each was more than 20 days prior. No flag had been raised internally. The accounts weren't marked at-risk. They looked fine — until you compared them to what the exits looked like 90 days before they happened.
Ghost Waste (invoicing) — $127,000 sitting unbilled. Completed work across seven engagements with no invoice issued. Average days-to-invoice: 34. Industry benchmark: 14. The oldest item was 41 days old. The firm wasn't owed the money yet — because nobody had asked for it.
Dollar-quantified findings reflect operational data at the time of the engagement. They are not audited financial figures.
Case Study 2 — 85-Person SaaS Company
Data ingested: CRM, product usage logs, support ticket history, internal document archive Time to first findings: 72 hours
Root Cause — A support spike that correlated with a help article update. Support ticket volume had risen 34% in Q3. The internal post-mortem attributed it to product complexity and a new enterprise tier. Both were partially right. Cross-referencing the support data against the internal document archive surfaced a more specific correlated event: a help article updated on August 3rd had removed a workflow step that 40% of active users depended on. The update was a minor editorial cleanup. Nobody had connected it to the spike. Once surfaced, the fix took one afternoon. We flagged the co-occurrence; the team made the call on causation.
Revenue Decay — Seven accounts reducing product engagement before their renewal conversations. Combined ARR: $1.2M. Feature usage had been declining for 60 or more days across all seven. Logins were down. API calls were flat. None had filed support tickets or complained. They were just quietly using less. The renewal conversations were 30 to 90 days out. Three had already begun evaluating alternatives.
Ghost Waste — Four unused Salesforce seats at $18,400/year. The seats had been provisioned for a sales expansion in Q1. The headcount plan changed. The seats stayed. They had been active for seven months with no login activity. The renewal was 11 weeks away.
Outcome: The help article was restored within 48 hours of the finding. Proactive outreach was initiated with three of the seven at-risk accounts before their renewal window opened. Two expanded. One churned anyway — but the conversation happened on the company's terms, not the client's.
Case Study 3 — 42-Person Digital Agency
Data ingested: Email archive, project tracker, CRM, time logs Time to first findings: 48 hours
Bus Factor — One account director, eleven clients, zero documentation. She held the primary relationship for 11 of 23 active client accounts — roughly half the firm's revenue base. There were no briefing notes, no meeting summaries, no handoff documentation for any of them. Three clients had never been introduced to a second contact at the agency. When we surfaced the concentration, the leadership team's honest response was: "We'd lose some of those clients if she left."
Root Cause — Two retainer clients quietly shrinking their scope. Both had been reducing their monthly hour allocations for four consecutive months. Neither had said anything. The reductions only became visible when contract terms were compared against hours actually logged. One had reduced scope by 40%. Neither account had been flagged for a check-in. Both were considered stable. The contracts said otherwise.
Ghost Waste — $43,000/year in tools that barely anyone used. Eight subscriptions with fewer than three active users across the agency. Several had been purchased for specific projects that had ended. The tools stayed on. The invoices kept coming.
Outcome: A documentation sprint was initiated across all eleven at-risk accounts. Both scope-reducing clients received proactive conversations within the week — one renewed at full scope, one was lost but the timeline was accelerated to allow for a planned transition. Two accounts that had been invisible as expansion opportunities were identified and contacted. The difference between a client you lose on your terms and one you lose by surprise is about three weeks of visibility.
Case Study 4 — Post-Acquisition: 55-Person Regional Services Company
Data ingested: Legacy accounting export, CRM, email archive, project tracker Time to first findings: 72 hours Context: New owner, 60 days post-acquisition. Previous owner had operated largely on spreadsheets, a CRM used inconsistently, and institutional memory held by a small senior team — most of whom did not stay through the transition.
Ghost Waste — $31,000/year in vendor contracts nobody knew were still running. Three software subscriptions and one service retainer had been set up by the prior owner and auto-renewed through the transition. No one on the new team had visibility into them. Two had no active users. One had been in a "pending migration" state since before the acquisition closed. The contracts were in the prior owner's email. They were not in the handoff documentation.
Bus Factor — The departing owner was the entire institutional memory. The prior owner had served as primary contact for 14 of 21 active clients, sole administrator of the billing system, and the only person with login credentials for two vendor platforms. No documentation existed for any of it. The new owner had 60 days of ownership and no visibility into what they didn't know yet.
Root Cause — A 22% drop in project completion rate correlated with a staffing change mid-transition. The metric was visible. The cause wasn't. Cross-referencing project records against HR data and the email archive surfaced a correlated event: three senior project contributors had departed within a 10-day window during the final month of the acquisition. Project timelines had not been adjusted. The new team had been carrying the gap without knowing what had caused it.
Revenue Decay — Six clients had gone quiet during the ownership transition. Combined ARR: $480K. None had formally canceled. None had filed complaints. Contact logs showed no outreach in 30 or more days across all six — a window that overlapped directly with the ownership handoff period. The behavioral pattern matched the firm's two prior exits. Without a flag, the new owner would not have known to reach out until it was already a retention conversation.
Outcome: Within the first week of the engagement, the new owner had a data-driven 100-day plan — prioritized by dollar exposure, not urgency signals that hadn't yet surfaced. The Ghost Waste was terminated before the next auto-renewal cycle. The six at-risk clients received proactive outreach before any of them had raised a concern. The institutional memory gaps were documented and assigned. Two of the six accounts expanded at renewal. The owner's words: "I didn't know what I didn't know. Now I do."
Dollar-quantified findings reflect operational data at the time of the engagement. They are not audited financial figures.
Your company is already telling you everything. The patterns are in your data. The risks are traceable. The waste is quantifiable. You're just not looking at it as a whole yet — not because you don't care, but because nobody connected the data.
Find Out What's in Your Data
The Operational X-Ray takes 5–10 business days. You send us exports from your core systems. We find the patterns, quantify what the data supports, and deliver a findings report with a prioritized remediation roadmap. $3,500–$7,500. 100% credits toward a Foundation Sprint within 30 days.
Recently acquired a business? The X-Ray is how new owners get visibility into what they bought — fast.
Keep Reading
21 Questions Your Business Should Answer in Seconds — A diagnostic. Count how many you can answer with a source right now.
A Day in the Life: Before and After — One Monday morning, two worlds. Which one does your team live in?
The Monday Morning Brief: A Sample — What it actually looks like when the intelligence lands in your inbox before 7am.
Why Your AI Pilot Failed — 68% of AI projects never reach production. Here's the real reason — and the way out.