How we work
Four stages. One accountable party across all four.
Diagnose, recommend, deploy, adopt. Most partners stop when the roadmap is handed over. That handover is the point where value usually leaks out, so it is not where we stop.
Diagnose
Read the function along both cuts and score every task, in two weeks.
Recommend
Turn the evidence into resolved decisions, with value in ranges.
Deploy
Build and roll out the redesigned workflow against the design.
Adopt
Make the redesigned work how the organization operates, and track it.
The claim is one accountable party through all four stages, not that we perform every specialist task ourselves. The evidence behind diagnose and recommend is strong today. The evidence behind deploy and adopt is structural — it is how the engagement is built, not a delivery record.
Structure tells you what the organization is. Flow tells you how work moves through it. Together they tell you what to change first.
The method
Two passes, one system.
Structure tells you what the organization is. Flow tells you how work moves through it. Together they tell you what to change first.
We call the methodology the Helix: two strands twisted together, and four artifacts that compose it. A function under AI cannot be read through one lens, so we read it along two.
Two strands, four artifacts. Where they cross is where a decision can be made.
Structure
How the function is organized to deploy capacity. The function decomposes into teams, teams into roles. This tells you which teams are still viable as AI changes the volume and nature of the work, and where capability investment should go.
Flow
How work actually gets produced. Critical workflows, often crossing several teams. This tells you what the future-state workflow looks like, where humans hold decision authority, and where exceptions route.
The two cuts cross-check each other. If the structural view says a team is core but its workflow evidence shows the work is mostly AI-handled, that contradiction surfaces instead of being averaged away. That cross-check is the reason both cuts exist.
A workflow crosses teams. A team sits across workflows. The role is the square where both meet.
The four blueprints
What we actually produce.
Four structured artifacts, produced in a defined order. Together they are the evidence every decision traces back to.
The four artifacts as they are actually built. Values shown are from a sample engagement.
FunctionDNA
The function as a portfolio of teams: cross-team value flows, the operating model, where capability sits, and a viability verdict for each team.
TeamDNA
The team as a work system: what it owns, how work moves through it, what it can deliver, and where AI changes the load.
FlowDNA
One workflow end to end: every step, current and future state side by side, where the hours go, who decides what, and the ROI band with its assumptions.
RoleDNA
A role at task grain: outcomes owned, decisions made, every task scored, the capability profile that follows. The proof drawer behind a number, not the pitch.
The scale
Every task is scored on the Stanford Human Agency Scale.
The scale is Stanford's, from the WORKBank research — not ours. What is ours is applying it at task grain across four levels of an organization and driving decisions with it. Higher always means more human agency, not less.
Nor human nor machine
The more AI carries at the low end, the more valuable the fully human work becomes. That is what makes the scale a design tool rather than a scoreboard: it shows you which work to move, and which work to invest in.
The five levels, and the question that places a task on each one
In practice
What actually changes, step by step.
This is the output the whole method exists to produce: a workflow as it runs today, and the same workflow after the redesign, with every step scored. Press run and watch where AI takes the load — and where it does not.
Four workflows from our sample engagements. The score is the Stanford Human Agency Scale — the fuller the mark, the more of the step is human.
The entry point
A pilot, on one function, in two weeks.
One function. One executive sponsor. At the end of it the sponsor can make a real decision about what comes next, on evidence rather than on a proposal.
- A full structural assessment of the function, with a viability verdict for every team in it.
- One or two of the most critical workflows mapped end to end, current state and future state.
- Three to five role blueprints for the people who operate those workflows.
- Function head and senior leader interviews.
- The starting picture of the function, team by team.
- The one or two workflows you cannot afford to get wrong, named.
- Preliminary verdict on every team.
- Interviews with the people who actually run those workflows.
- Current state and future state, step by step, scored.
- Team verdicts finalised in the last two or three days, after the workflow evidence lands.
- Role blueprints started only once the verdicts hold.
A decision the sponsor can actually make about what comes next — on evidence, not on a proposal.
The structural picture is finished last, not first. That order is deliberate: it stops the role work resting on assumptions the workflow evidence would have revised.
The first pass starts with a scaffold of the function from leadership interviews — a starting picture, not a verdict. The workflow and team evidence is produced in parallel and revises the scaffold. Only then are the team verdicts and the future operating model locked. The second pass produces role-level detail, and only for roles on teams confirmed viable or transitional. That rule keeps the analysis pointed at work that will still exist.
Scope and timing for the full engagement follow the pilot, because they are a function of what the pilot surfaces.
The output
What lands on the table at the end.
Meridian is a sample engagement for a commercial bank, built end to end with the same method we run with a client. The first screen is the leadership table: every decision with one owner, a status, and the trigger that moves it. Every row opens onto the evidence behind it. Read the whole readout.
The first screen of the readout. Every row opens onto the evidence behind it.
What to look at first
Four things worth your attention.
- The leadership table. Ten decisions, each with one owner, a status, and the trigger that moves it. Ordered by what depends on what, not by department.
- The same picture, cut four ways. Operating model, value and capital, work redesign, workforce. Everyone reads the same evidence from where they sit.
- The workflow atlas. The work as it runs today, where AI takes the load, the redesigned future state, and the human work each redesign grows.
- The numbers and what they rest on. ROI in ranges, assumptions on the surface, upside kept separate from the base case.
What it demonstrates
A decision you could defend in a board meeting.
The sequence in the sample is the point. Structured capture in operations makes covenant automation possible. Covenant automation sets the data quality for early-warning signals. Clean signals make the renewal redesign possible. The renewal redesign is what frees analyst capacity. Nothing moves out of order because nothing can.
And the credit sanction stays human, permanently and on purpose. That is a design decision with a reason behind it, not an omission.
Data
A redesigned workflow that depends on information you cannot produce reliably will not run.
So data is a named part of the work and we own it: we assess what each redesigned workflow needs from your data, we tell you what blocks it and what that block is costing you, and we close the gaps — bringing in specialist capability on a specification we wrote, supervised by us. One counterparty, the same as everywhere else in the engagement.
We are accountable for
- Whether the information each workflow depends on exists, connects, and is reliable enough to act on.
- The data each future-state workflow rests on, specified.
- Gaps ranked by the workflow they block and what that workflow is worth.
- Those gaps closed, tested against criteria we set.
Executed by specialists we bring
- Pipeline build, integration, migration, data engineering.
- Data governance design, model risk management, security.
Our resource, on our specification. Not a handover.
What is different about this
Three things a buyer can check.
Read at task grain, not at framework grain
Most diagnostics sample a few interviews and map the result onto a framework. We decompose the work itself — every task in the roles that run the workflow, scored — so the finding survives someone senior pulling on it.
A resolved decision, not a map
A live map never resolves. What you get is a small set of decisions in the order they have to be made, each carrying its verdict, the bets it rests on, and the evidence path down to the task it came from.
One accountable party across all four stages
Not the most people in the building — the one who carries the consequence. Where specialists do the building, they work to our specification and under our accountability; you are not handed to them. And we do not ask for a fee we have not first quantified against a loss you are already carrying.
Deploy and adopt
- The roadmap was delivered and nothing moved after it?
- The redesign works in the deck, but nobody can say who owns it on Monday?
- You have adoption numbers that count logins rather than work?
The value is not created when the analysis is finished.
It is created months later, when the redesigned work is simply how the place operates. That is several handovers past where a diagnostic engagement ends, and every handover is where the value leaks. So we do not hand over.
The change is communicated from the evidence
The change narrative for the function, briefing material at team and role level drawn from the same analysis, and honest answers to the questions people will actually ask — including whether their role survives it. We are not writing reassurance. We are telling people what the work becomes.
Capability is built where the work moved
The role blueprints already say which human capabilities become more valuable as AI absorbs the routine volume. Learning is designed against that, for the people on teams that are staying, delivered through training partners.
Adoption is tracked, not assumed
Whether the redesigned workflow is actually being run the way it was designed, where it is drifting back, and what that costs. A feedback route from the manager conversations back into the work.
Why this sits with us rather than a communications agency or a training vendor: the answers are only as good as the task-level evidence behind them, and we hold that evidence.
The diagnosis is where you start. Staying through adoption is why it is worth starting with us.
Common questions
The questions we actually get asked.
Q01How is this different from hiring a consulting firm?
Q02How long does it take?
Q03What does it cost?
Q04Do we need our data in order before you start?
Q05What happens to people in this?
Q06Who owns what you produce?
Q07How do you keep from inventing numbers?
Bring one workflow you already know is painful.
Not a sales meeting. A conversation about whether this addresses a problem you recognize in your organization, and what you would need to see to hold the answer under scrutiny from your CFO and your board.
Rajeev, who runs the engagement. Not a qualifier.
Bring one workflow you already know is painful. We trace it one or two layers out loud with you, tell you what we would need to see to answer it properly, and say what we could not answer.