Discovery
A short, structured look at the systems, people and constraints already in play.
Service
Data strategy
Audit of what you have, a target operating model, and a roadmap with a business case your CFO will actually read.
What brings people here
A board has asked for an AI plan. Or three teams have each proposed a platform. Or the last two data projects overran and nobody can explain why the third will be different.
The common thread is that the organisation has opinions about data but no agreed picture of what it actually has.
What we do
Four to eight weeks, working with your analysts, engineers and the people who consume the reports. We map the systems, find where figures diverge, and cost the gaps in hours rather than adjectives.
The output is a ranked list of opportunities, each with an owner, a dependency and an estimate — plus the ones we recommend against, and why.
What this is not
It is not a tooling selection exercise. We will tell you if your platform cannot meet a requirement, but platform choice is rarely the constraint and almost never the first thing to change.
How it ends
With a roadmap your CFO can read and your engineers can start on Monday. Most clients move straight into a pilot on the top-ranked item.
What we do
The activities this covers
Design
An approach written in plain language, reviewed with your team before anyone writes code.
Delivery
Built in your cloud and your repository, demonstrated weekly against working software.
Validation
Tests and measurement against the success criteria agreed at the start.
Documentation
Runbooks and decision records written during the work, not reconstructed after.
Handover
Training for the people who will own it, scoped from the first week.
What you get
Deliverables, not slideware
- A repository you ownTransformations, infrastructure and CI configuration, commented and reviewed.
- Test suiteTests running on schedule, with alerts routed to a channel your team reads.
- Cost baselineWhat the work costs to run per team, with a monthly budget alert.
- Architecture diagramCurrent state and target state, kept up to date through the engagement.
- RunbooksWhat to do when something fails at 3am, written for someone who did not build it.
- Two weeks of trainingHands-on sessions with the analysts and engineers who take it over.
Related work
Where this service led the engagement
Ridgeline Bank · Financial services
A month-end close that took eleven days
Finance rebuilt the same figures by hand every cycle. We modelled the ledger in the warehouse, defined forty metrics once, and automated the reconciliation.
11 → 3 days to close
Hollis Logistics · Logistics
A warehouse bill that doubled in a year
Nobody could see which queries cost what. We added cost attribution per team, rewrote the twelve worst models, and set a monthly budget alert.
-46% platform cost
Questions
Questions about data strategy
Still unsure? Call (216) 123 45678 and ask for whoever is on the desk.
Ask a questionNo. Most engagements improve what you already run. We only recommend migration when the current platform cannot meet a requirement you have already committed to.
You do. Everything is written in your repository, under your cloud account, on open tooling. There is nothing to transfer at the end because it was never ours.
That is the normal arrangement. Your engineers review our pull requests and we review theirs. Teams that stay out of the work rarely take it over successfully.
First working increment usually lands inside three weeks. We demo weekly against running software, not plans.
Tell us which number you cannot trust
Send one paragraph about the report that always starts an argument. A data lead, not a salesperson, replies within one business day.