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CASE STUDY ยท Business Services & Analytics

3ร— Reporting Velocity and 64% Lower Analytics Cost

Facing a PE quarterly board pack that was landing two weeks after quarter-end, KPI dashboards dependent on a single data lead, and a PortfolioCo comparison model built entirely in Excel, the firm built a 6-person remote analytics pod that now owns Snowflake + Looker + dbt inside the firm's existing stack.

3ร—

Reporting velocity

70%

Lower monthly KPI cycle

64%

Lower analytics operating cost

Client Snapshot

IndustryBusiness Services & Analytics
Company Size$110M revenue, 14 operating entities, 900 employees
GeographyUnited States & United Kingdom
StackSnowflake, dbt, Looker, Fivetran, BigQuery, Python, Power BI

The Challenge

The firm's data function was a single-person dependency: one data lead serviced 14 operating entities, board reporting cycles, portfolio-level comparisons, and ad-hoc requests from the PE sponsor. The bottleneck was visible in every delayed board pack and every ad-hoc SQL request that sat in the queue for three weeks.

1

Board reporting was landing after board meetings

Monthly management accounts were arriving 18 business days after month-end โ€” two days after the PE sponsor's monthly call. Board decisions were being made on the previous month's data, and the sponsor had started flagging reporting maturity as a 'value creation' concern in the quarterly investment committee review.

2

KPI dashboards didn't scale past one entity

Looker dashboards existed for the flagship entity only; the other 13 entities reported in Excel with inconsistent metric definitions. The CFO's standard view of 'EBITDA margin by entity' took 11 days to produce manually โ€” too slow to run weekly, too inconsistent to trust.

3

Local data hiring didn't match the spend envelope

A mid-level US analytics engineer cost $130Kโ€“$175K fully loaded with an 8โ€“12 week hiring cycle. To build a real analytics function the firm needed 4โ€“6 hires โ€” roughly $710K annual payroll before benefits โ€” sitting on top of a $4.2M total G&A envelope the sponsor had pre-agreed.

"

Our data lead was a single point of failure for fourteen entities and the board. We weren't short on data โ€” we were short on people who could turn it into decisions. The sponsor flagged it as a value-creation concern, and that told us this couldn't wait another quarter.

Z
CFO PE-Backed Business Services Firm (name withheld โ€” NDA), PE-Backed Business Services Firm (name withheld โ€” NDA)
โ˜…โ˜…โ˜…โ˜…โ˜…

The Solution: A Pre-Vetted Zedtreeo Team

Zedtreeo deployed a 6-person remote analytics pod within 11 business days. The pod was structured to cover the full analytics stack โ€” data engineering, analytics engineering, BI + dashboarding, and operational reporting โ€” all operating inside the firm's Snowflake + dbt + Looker environment with the data lead acting as technical lead.

Team Composition Deployed

A full-stack analytics pod sized to build the portfolio-level KPI model, scale Looker to all 14 entities, and run weekly + monthly reporting without consuming the data lead's capacity.

E
Senior Analytics Engineerdbt models, Snowflake data warehouse design, metric-layer ownership, testing framework, data-quality monitoring.
D
Data EngineerFivetran + BigQuery ingestion pipelines, source-system integration, schema change management, data contract ownership.
B
BI & Dashboard DeveloperLooker LookML, Power BI, entity-level + portfolio-level dashboards, self-serve report design, board pack automation.
A
Operational Reporting AnalystWeekly KPI reporting, ad-hoc SQL, variance analysis, entity-level commentary, self-serve Looker training for business units.

Tools & AI Stack Deployed

The pod operates in the firm's existing stack โ€” Snowflake, dbt, Looker, Fivetran, BigQuery, Python, and Power BI โ€” with NDA, SOC 2 controls, least-privilege data access, and dbt-native pull request review from day one. Delivery runs through the firm's existing dbt repo + Looker LookML workflow.

Execution Timeline

1 2 3 4
1

Week 1

Week 1 โ€” Kickoff & Clearance

Requirements call, NDA + SOC 2, Snowflake / dbt / Looker access provisioning. Shortlisted pod interviewed by CFO + Data Lead in 48 hours.

2

Week 2โ€“4

Weeks 2โ€“4 โ€” Onboarding

5-day free trial on live dbt PR queue. Metric definitions documented, entity-mapping model built, first portfolio-level dashboard shipped.

3

Month 2โ€“3

Month 2 โ€” Reporting Scale

All 14 entities modeled in dbt. Monthly KPI cycle compressed from 18 to 6 business days. Ad-hoc SQL queue cleared.

4

Month 4โ€“6

Months 3โ€“6 โ€” Board-Ready Stack

Monthly cycle hits 5 days. Board pack auto-generated in Looker. 64% cost reduction booked. Pod extended by 1 analyst for M&A diligence support.

The Results

Within one quarter, the analytics function stopped being a single-person dependency and became an operating system for the portfolio. The PE sponsor moved reporting maturity off the value-creation concern list inside the next quarterly investment review.

Performance Before โ†’ After

Measured improvements across 90 days post-onboarding of the engagement.

Monthly KPI cycle +70% faster
Before: Before: 18 daysAfter: After: 5 days
Entities with live dashboards +14ร— coverage
Before: Before: 1After: After: 14
Ad-hoc SQL turnaround +90% faster
Before: Before: 21 daysAfter: After: 2 days
Annual analytics operating cost โˆ’64%
Before: Before: $740KAfter: After: $268K

ROI: Zedtreeo vs In-House Hire

64 Cost Saved

12-Month Cost Breakdown

Line ItemIn-House (United States & United Kingdom)Zedtreeo
Salary + Benefits$660,000$268,000
Recruitment$38,000Included
HR & Compliance$28,000Included
Tools$22,000Included
Total Annual$748,000$268,000

Client Testimonial

"

The Zedtreeo analytics pod built us the portfolio KPI layer we've been trying to staff for two years in under eight weeks. dbt-native PR review, Looker LookML discipline, Snowflake cost controls โ€” it's indistinguishable from a best-in-class internal data team. Reporting velocity 3ร—, cycle 70% faster, cost 64% lower. Our sponsor noticed inside one quarter.

Z
CFO PE-Backed Business Services Firm (name withheld โ€” NDA), PE-Backed Business Services Firm (name withheld โ€” NDA)
โ˜…โ˜…โ˜…โ˜…โ˜…

Roles Deployed on This Engagement

Every role included: AI-tool training, HR management, compliance, and replacement guarantee. Starting from $5 per hour, fully timezone-matched globally.

Build a Team Like PE-Backed Business Services Firm (name withheld โ€” NDA)'s

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Published April 16, 2026