The manual reporting stops being work.
One governed model in your own tenant, refreshed nightly, reconciled against your own numbers before anyone is asked to trust it. Priced by milestone, each phase accepted in writing before the next is quoted.
Time to a defensible number
Weeks to Now
Most analytics work fails at the handover. Ours is built to be handed over from the first week.
Fifteen years in analytics, most of it inside operations, which is why the first thing we do is reconcile against a number you already produce by hand. If the model can't agree with your own arithmetic, nobody should be asked to run the business on it.
Everything is built in your tenant, on your licenses, documented as it goes. The person who scopes the work stays accountable for it start to finish — you are never handed to someone who has to be brought up to speed.
Four ways in
01
Analytics Strategy
What to build, in what order, and what it's worth. A roadmap priced against the decisions it unblocks — not a maturity score.
$30–50K
Project
02
Data Platform & BI
The governed model and the reporting on top of it. Your systems consolidated, refreshed nightly, reconciled before anyone is asked to trust it.
$40–100K
Project
03
Analytics Intelligence
Applied AI and custom software on the governed model: agentic workflows, MCP servers, internal tools. Shipped in weeks, owned by you.
$75–150K
Project
04
Analytics Partner
Your analytics function on retainer, from analyst throughput to sitting in the room when the number matters. Usually how a project ends rather than how one starts.
$5–15K
Per month
How an engagement runs
Each phase is scoped, priced and accepted in writing before the next one is quoted.
You can stop after any phase and keep everything built. No phase depends on us staying.
01Weeks 1–2
Discovery
Every system inventoried and every metric defined in your own words, so there's one written definition before anything is built.
02Weeks 3–6
First system live
One source in production, refreshing nightly, reconciled against a number you already produce by hand.
03Per SOW
Coverage
The rest of the estate, to a coverage figure written into the contract and signed off against.
Then it's yours
Handover
Your tenant, your licenses, documented. Keep us on as your analytics partner, or run it yourself.
PE-backed roll-up · 6 systems + Sage
Corporate KPIs took one person a week per cycle across 19 system instances; fifteen now read from one nightly model the operators audited themselves.
One week → nightly
PE-backed roll-up · 6 systems + Sage
Three phases of build, then a retained contract — chosen by the client as the best fit for what came next, rather than proposed by us.
Build → retainer
Travel-data SaaS · holdco portco
A thirty-year-old platform had never aggregated across its clients; the engagement returned a working proof of concept, not a report about one.
Discovery done by day 10
Medical imaging lessor · 57 units
Finance ran on one spreadsheet and a board metric with four competing definitions; thirty-eight days later a governed warehouse ran in production in their tenant.
38 days to production
On record
19 → 1
System instances across 28 locations, in one governed model
72 nights
Consecutive automated rebuilds, no missed refresh and nobody watching it
13 days
From credentials to production for a newly acquired company's system
$0
Charged for two systems found mid-build that the contract never listed
Every figure traces to a delivery artifact — acceptance documents, refresh logs, or a reconciliation the client ran themselves. Clients are blinded until they've signed off on being named.
Case studies →Before you talk to anyone
Work out what your current reporting costs you.
Eight inputs, no email required, assumptions shown. It produces an annual figure for the hours your team already spends assembling numbers by hand — useful whether or not you ever call us.
What it asks
- Entities or locations that roll up
- Systems of record feeding reporting
- People assembling reports
- Hours per cycle
- Cycles per year
- Blended hourly cost
- Acquisitions planned this year
- Days until the numbers are trusted
Questions
What analytics challenges do newly acquired companies face?
Newly acquired companies typically face three core analytics challenges: inherited systems that tracked what the previous owner needed rather than what new leadership requires, misaligned definitions where different departments measure the same metrics differently, and the “existence vs utility” gap where systems passed diligence but can’t actually support decision-making. These issues typically surface 6–18 months post-close, when the deal team is gone and operators need to run the business.
How do you help PE portfolio companies with analytics?
We position data and analytics as a value creation lever for PE-backed companies. Our approach starts with helping leadership teams figure out what good looks like — aligning on definitions, metrics, and what decisions the data needs to support. We then build one governed model in the client’s own tenant, reconciled against a number they already produce by hand, and the reporting and tools on top of it. Projects range from $30K strategy engagements to $150K builds, plus an Analytics Partner retainer from $5K per month.
What is the “messy middle” in post-acquisition analytics?
The messy middle refers to months 6–18 post-acquisition, when deal assumptions meet operational reality. This is when leadership discovers that inherited systems tracked total revenue and margin, but not the unit economics, channel performance, or cohort behavior their new strategy requires. It’s the period where “everything looked fine in diligence” turns into “we can’t answer basic questions about our business.”
Why do companies have data but still can’t make decisions?
Having data and being able to use it are two different things. Most companies have reporting that exists but isn’t trusted, dashboards that show flawed or outdated information, and leaders who don’t actually use data to make decisions. The root cause is usually the definition problem — different teams measuring the same thing differently. Until leadership aligns on what’s being measured, why it matters, and how it’s used, analytics only amplifies disagreement.
What does analytics diligence miss?
Diligence validates that systems exist and confirms what the numbers are. It rarely validates whether leadership can actually run the business with those systems or how operations produce those numbers. A data warehouse that technically functions but has messy table structures, mismatched data types, and business logic that doesn’t reflect actual operations will pass diligence but fail when the new team tries to pull performance reports.
How long does an analytics implementation take?
Timeline depends on scope. Analytics Strategy typically takes 8–12 weeks and costs $30K–$50K. A Data Platform and BI build typically takes 10–16 weeks and costs $40K–$100K. Analytics Intelligence engagements range from $75K–$150K and ship one workflow at a time, in weeks. The Analytics Partner retainer runs $5K–$15K per month, reviewed quarterly with 30 days’ notice.
What industries do you work with?
We work across industries because leadership transition is the common thread, not sector. Our experience spans sports, media, insurance, automotive, financial services, and SaaS. The pattern is consistent: new leadership inherits systems they didn’t design and needs to figure out what good looks like for their operation. Industry knowledge matters less than understanding how to build analytics that support decisions during transition periods.
Bring the number you don't trust. We'll tell you what it would take to fix it.
Thirty minutes, no deck. If it isn't work we should do, we'll say so on the call.