When People, Process, Data and Technology fall out of step, money goes into tools nobody adopts, decisions rest on numbers nobody trusts, and the change quietly unwinds.
We bring the four back into balance. And we show you where you stand before you spend anything.
Some areas strengthen while others quietly fall behind. The gap between your strongest and your weakest is where the money and the risk collect.
Pull the four around and watch what imbalance does.
Drag a dimension down, or pick a common pattern:
Free, self-serve, no card and no call.
You'll get your balance profile across the four elements — where you're strong, and where the gaps are quietly costing you.
Then five days of guidance, written for whichever element came out lowest. Not a brochure. The first piece of the work.
No card. No commitment.
You can stop after day one.
The four we score are the four we rebalance. Each has a finished state — that's what we work towards, and what the second score measures.
The people who drive the change, equipped to.
Workflows built for resilience, not heroics.
Structured and governed, so the numbers can be trusted.
Technology that amplifies people rather than replacing them.
Define data. Enhance digital. Optimise processes. Empower people.That's the Datavation Way. One belief underneath all of it: culture controls data.
A Japanese idea, a Toyota discipline, and a British practice's way of working.
調和 is two characters. 和 is harmony. 調 means to adjust, to harmonise — to tune. Chowa isn't stillness. It's the work of keeping things in tune while they move.
Which is exactly what a business needs and almost never gets: not one part optimised, but the whole thing pulled level.
Don't just optimise parts — align the whole. Don't just fix — flow. Don't just act — balance.
Underneath the method is a working rhythm we apply to every piece of work. Four of the six steps are Toyota's, from the production system that Lean, Six Sigma and Agile all descend from. Two are ours.
| Step | What it means | From |
|---|---|---|
| Find the BalanceChōwa 調和 | Where are we now, across the whole system? | Ours |
| Go and SeeGenchi Genbutsu 現地現物 | Go to where the work happens. Don't theorise from a distance. | Toyota |
| Show Me the EvidenceShōme 証明 | What does the data actually say? Evidence, not opinion. | Ours |
| Small StepsKaizen 改善 | The smallest useful improvement. Progress over perfection. | Toyota |
| Build It InJidoka 自働化 | Quality built in, not inspected later. | Toyota |
| Pause and ReflectHansei 反省 | What did we learn? What do we do differently next time? | Toyota |
We take the Agile Manifesto seriously too — working results over documentation, people over process for its own sake, and feedback loops short enough to act on.
Why the Japanese? Because that's what they're called. The discipline came from the Toyota Production System, and renaming its principles to make them sound like ours would be the first dishonest thing on this page.
Five stages and one constant. The same shape every time, at whatever size fits.
The Scorecard. Four numbers and an honest read of where you're out of step — before anyone quotes for anything.
Time inside the business. How the work actually happens, not how the org chart says it does.
Findings turned into one shared picture and a priority order. Plain English. Agreement on what's true, before any argument about what to do.
The playbook applied, hands-on. Embedded first, then clinics, then only when you call. Built with you, not for you.
A named owner inside your business, a group that meets without us, and the Scorecard run again on the same four axes.
The sixth S isn't a stage — it's the hand that stays on it. Every stage is run by the team and overseen by one person: the same person you met. Nothing reaches you unreviewed, and the senior relationship never gets handed down to an account manager.
It starts before Signal, when we work out whether we're the right fit at all. It carries on after Sustain, because a handover nobody checks isn't a handover.
Five stages. One steer.
That isn't a nice sentiment. It's how the engagement is built.
A large firm is staffed to stay — a pyramid has to be fed. We're built the other way round. Support starts embedded and steps down deliberately: alongside you, then open clinics, then only when you call, then a group inside your business that meets without us at all.
Every step out is earned, not scheduled. You move on when your team can do the work to an agreed standard — and we prove it by running the Scorecard again, on the same four axes. The before and the after sit on one instrument. You can argue with the number.
The person you meet is the person who does the work. No bench, no pyramid, no graduate learning on your budget.
The data model sketched in 2008 is recognisably the one running a live business today.
A multi-tenant data model, audited from the first table. Specified, built and sold.
The same model shipped as a field-operations platform — web, iOS and Android — before the category had a name.
The same model again, running a live business — this time operated by governed AI agents.
We've worked alongside the large firms, not just against them. Accenture on delivery and Gartner on strategy at a global law firm. Deloitte inside the Metropolitan Police. We've been the client — we've bought what they sell, watched it land, and kept the parts that worked.
Most people deploying AI agents for small businesses have never had to pass an audit. We have.
The career behind all of this is on austenking.com — the events, the institutions, and what we did about them.
Senior data leadership used to mean building a department. It doesn't have to any more — and the way we staff ourselves is the same principle we'd apply inside your business.
Every role in a business sits in one of three states. Knowing which one you're looking at is most of the decision.
Someone already does this well and has the time to do it. Leave it alone. Adding technology to a role that works is a cost, not a gain — and it's the most common way money gets wasted.
Someone owns the role and is good at it, but there aren't enough hours. A specialist works alongside them — doing the groundwork, the research and the first draft, so the person spends their time on judgement instead of admin.
Nobody does this at all, and a hire can't be justified yet. The specialist covers it under supervision — not as a replacement for a person you were going to hire, but as work that was otherwise never getting done.
Our own team is built exactly that way. You get a named human who is accountable, and a set of specialists who make one person's capacity go a great deal further.
They're staff, not software. Nothing reaches you unreviewed, and every figure comes with a source you can check.
And this is the offer in miniature. Map the same three states onto your own team — what's covered, what's stretched, what's missing — and you have the shape of an augmented team. Building those for other businesses is what datavation.ai does.
Large firms don't publish prices. We do — because the first thing you want to know is whether this is for a business your size.
The Balance Scorecard, and five days of guidance keyed to your weakest element. No card, no call.
Start freeYour playbook, live and updating. Monthly re-score, a roadmap that moves as you move, guidance by email. No meetings.
Everything in Solo, plus online workshops where we turn up. Discovery done properly, and the hands-on stage a playbook can't do for you.
Every month: one working session, one thing built or automated and handed over, and a re-scored roadmap.
On site. Real discovery, real hands-on delivery, and a production build of your own agent fleet.
The difference between the tiers isn't features. It's how much of the practice you get, and how much of it is us in the room.
Monthly. No minimum term, no notice period. Move up, move down, or stop — we'd rather you stayed because it's working.
Take the Scorecard, or talk to us about where your business is out of step.
No hype, no bench, no Big Four day rate. Senior data leadership that does the work — and then hands it back.
Enterprise-grade thinking for organisations that were never going to build a data department — and larger ones that need it done properly. Every engagement runs Signal to Sustain: balance first, evidence before spend.
Senior data leadership on the days you need it — strategy, governance, team build, board translation, interim cover.
Explore →A strategy your board can act on, and the ownership, standards and controls that make it stick.
Explore →Where AI earns its keep and where it doesn't — governed, evidenced, audit-ready.
Explore →Off the on-premise past onto a modern, governed cloud foundation — without dropping the reporting. Detail page in preparation
Master data and quality frameworks that take error rates down and trust up. Detail page in preparation
A phased engagement that brings People, Process, Data and Technology into balance. Detail page in preparation
Most mid-size organisations need senior data leadership long before they can justify a full-time hire. We provide it — fractional for the ongoing steer, interim to hold the seat through a gap or a transformation — and the person you speak to is the person who does the work.
Data decisions are being made by committee or not at all. A strategy exists on a slide but nothing moves. A transformation needs a senior hand but not a permanent headcount. You need judgement and accountability now, sized to your budget.
We start with the Balance Scorecard and a Sense diagnostic, agree the one or two moves that pay for themselves first, then embed — Signal, Sense, See, Shape, Sustain. Design big, build small, deploy often.
Mid-size to large organisations in professional services, financial services and the public sector — and ambitious smaller firms that want enterprise discipline without the enterprise overhead.
The free Balance Scorecard is the honest place to start.
Most data strategies fail not because they're wrong but because nothing holds them up: no ownership, no standards, no controls. We build the strategy and the scaffolding together, so the direction survives contact with the business.
Reports nobody trusts, definitions that differ by department, governance that lives in a policy document no one follows. The result is slow, contested decisions and transformation that quietly unwinds.
The Chowa Method keeps People and Process in the frame, not just Data and Technology — because culture controls data. We rebalance all four, and embed governance into the daily process rather than bolting it on.
The same discipline took validation errors from 12% to under 3% inside a global bank, and stood up enterprise data platforms across 60+ offices at a global law firm. See the provenance →
Start with the free Balance Scorecard.
We're not here to sell you AI. We're here to tell you, honestly, where it will pay for itself, where it won't, and how to adopt it without creating risk you can't see. Governed from day one — because we've had to pass the audit.
Pressure to "do something with AI", a pile of pilots that never reach production, and a nagging worry about data, governance and what the tools are actually doing. You want the upside without betting the business.
The same governance we build into our own agent team — enterprise DevOps and data standards designed in, not bolted on. We took an AI legal-analytics platform to production that cut claims processing by 80%, handling client data safely.
Domain ownership, data as a product, federated governance and interoperability — Data Mesh principles applied in practice, not recited. Implemented across 60+ offices with Microsoft Purview as the computational governance layer.
The Balance Scorecard shows whether your foundations can carry AI yet.
Free, self-serve, no card and no call. You'll get your balance profile across People, Process, Data and Technology — where you're strong, and where the gaps are quietly costing you.