Built by management consultants, for management consultants. Footprint, location and workforce advisory — in plain English, with the sourcing shown, not another chatbot guessing in the dark.
Real interface, running on labelled demonstration data — every screen tells you exactly what it is and isn't.
Most firms are stuck between two bad options: ignore AI and fall behind, or restructure the model that pays the bills to chase it.
In plain English: you don't have to break your business model to use AI properly. You have to aim it at the right target — and give your analysts a tool, not a replacement.
Same method, every time — sourced, labelled, checkable. Not whoever's turn it is to prompt the chatbot this week.
The philosophy underneath everything we build: if a client can't understand the answer in one read, it's not finished yet. No jargon, no black-box maths — just the logic, said plainly.
Our house rule for AI: every step has a matching manual method sitting behind it. If you ever want to know how a human would've done it by hand, we can show you — and prove both routes land on the same answer.
Every figure on this site has a traceable path back to its source, its transformation, and the rule that produced it — not just a claim, an actual generated trace. Any number, on demand.
We didn't pre-build a flowchart for every figure across all six tools on the off-chance someone would ask. That's exactly the kind of speculative AI spend we built Stonefield to argue against. Instead, the logic lives as a structured recipe, and the trace is generated live, only when someone actually asks the question — a technical reviewer, a data scientist, you.
Three traces are drawn on the Director's Cut page — stills, so you can see what one looks like. The live version, where any figure in any tool draws itself the moment you ask, runs inside our own tooling and can't sit on a web page. We'd rather show you than claim it: see the stills, then book a session and pick any number. The logic framework does the thinking — 250+ engagements' worth. AI just draws the picture.
In plain English: we're transparent. Everything in plain English, nothing off the table, nothing hidden. Stills on the site; the live draw when we meet.
The clearest proof of "generate on demand, not just in case" isn't a client story. It's how we built the thing you just saw.
Not a library of pre-drawn flowcharts. Just the ability to get one, the moment they ask a specific question. That's the whole north star — the output, on demand, nothing more.
We didn't. Building a flowchart for every figure across six tools, whether or not anyone would ever look, is exactly the speculative spend this whole site argues against. So we asked what the smallest real build actually was.
The logic behind each traceable number lives in a single spreadsheet — source, transformation, rule, output, one row per figure. No code. Anyone on the team can read it, extend it, correct it.
When someone actually asks, AI reads that one row and draws the trace — live inside our tooling, in about a minute. It doesn't invent the logic. It executes ours — the same distinction we make about every tool in the suite. The stills on this site were drawn the same way, once.
What it saved: no speculative coding, no pre-rendered library nobody asked for, no engineering time spent on the 90% of figures that might never come up. Just one reference file, and a generation step that runs exactly once per real question.
In plain English: we're not asking you to take our word for how we work. We just showed you, on our own tool, using our own logic, in front of you.
Not a general-purpose AI story. These are the concrete reasons a management consulting firm licenses this.
Pre-trigger signals surface real opportunities before a competitor's scoping call does — not after the RFP is already out.
The eight-line framework tells you which practice owns each signal automatically, so BD time goes into the pitch, not the routing.
Your existing team works faster and covers more ground. Nobody's billable model gets restructured to get there.
One alignment session calibrates the framework to your service lines. No months-long internal build, no new methodology to design.
Reads source material in 10+ European languages directly — no translation step slowing down the first pass.
Starts the discussion with clients on skills, not job titles — exactly the conversation boards are now asking for.
Reaching a real skills starting point on one engagement took two senior consultants six months, full-time, on-site — 233 distinct skills found. That starting point is now an afternoon's work, not the interviews and judgement calls around it, which stay exactly where they belong: with your consultants.
Basic staffing maths: keeping just one function on call 24 hours a day, 7 days a week takes a minimum of 4.2 full-time people, before sick days or holidays. The suite is on call, across every tool, with no rota required.
Use one, use all six. From the first footprint signal to the answer your exec team can actually act on. Click any tool to see what it actually answers.
Key questions it answers: Which of our target accounts is under real pressure right now, and how confident should we be? Is this a footprint story worth raising with the client this quarter?
Every score is sourced and flagged with a confidence range, not presented as a bare number — so you know exactly how much weight to put behind it in the room.
Key questions it answers: Where should this role actually sit — and what does that decision cost, in real labour and regulatory terms, not a rule of thumb? How does one capital city really compare to another once you strip out the guesswork?
Weightings are yours to move — the tool shows the ranking shift live, so the client sees their own priorities driving the answer, not a black box.
Key questions it answers: Which roles in this business are genuinely AI-augmentable, and which aren't? If we planned around skills instead of job titles, where would we actually need to invest first? What does the workforce of the future look like for this specific client, not the market in general?
Coverage runs across 10+ European languages — screening skills and occupation data at a scale we don't publish the source of, since that mapping is proprietary. What we will say: [jobs and skills coverage figures — confirming exact numbers].
Key questions it answers: Has anything material changed in this client's workforce since we last looked — restructuring, hiring freezes, union activity? Do we need to be back in the room before they call us?
Runs as a standing monitor, not a one-off report, so a live signal doesn't sit unnoticed for a quarter.
Key questions it answers: Of everything the suite has flagged, what actually needs an executive decision this week? Where can we honestly say "we don't know yet" instead of guessing to fill a slide?
Every answer is labelled answered, partial, or "cannot tell you" — the gap is named, never quietly estimated around.
Key questions it answers: Where does everything the suite has produced for this client actually live, so the next analyst on the account isn't starting from zero?
One record per engagement, shared across the tools — not six separate exports living in six separate inboxes.
The logic and frameworks behind each tool don't ship because they seem right. They ship because they survived people whose job is to find the hole in them.
David Osborne — Founder & CTO, Stonefield Advisory
Sixteen years in international consulting, thirteen of them in footprint optimisation. Two hundred and fifty-plus location strategy programmes across 40+ countries and 8 sectors, including co-leading a 50-person European hub at a major human capital advisory firm. Stonefield is that methodology, turned into six tools — not a generic AI wrapper guessing at what consultants need.
For strategy consulting firms specifically, that means:
The big platforms have depth but move slowly. Generic AI tools move fast but have no methodology underneath. Stonefield is built to sit in neither camp — enterprise-grade rigor, 250+ engagements deep, delivered with the speed and hands-on attention only a boutique can give.
Copy the block below into ChatGPT, Gemini, or Claude — it's the whole pitch, pre-loaded, so the AI has something real to judge instead of guessing.
In plain English: we're not asking you to trust a tagline. Paste our own pitch into an AI and make it argue with us.
Real research on AI and consulting work — run against what your own numbers actually look like.
In plain English: AI genuinely helps on the repeatable stuff, and genuinely hurts when nobody's checking the complex stuff. That's the whole reason Stonefield has a human in the loop, not just a chatbot.
It's not just hours saved. It's showing up before anyone else does.
Restructuring, lease events, workforce shifts — caught from official sources before it's public. Not discovered in a scoping call.
Every signal already knows which service line it belongs to. No meeting spent working out who owns it.
One workshop calibrates the framework to your own service lines. No months-long build, no methodology from scratch.
Meetings stop being "let's scan the account list" and start being "here's the shortlist."
In plain English: you find out about the opportunity before your competitor does, and you already know which partner should be in the room.
Quick walkthroughs on demo data — nothing client-specific, ever. Each clip says exactly what kind of data it's showing.
Not a black box. Not a six-month build. One session and you're live.
If you're into AI, structured thinking, or just figuring out how the two turn into better business decisions, get in touch. Coffee, a workout, a walk, whatever — happy to talk shop or nothing in particular.