Most organizations know what they want to do. Far fewer can say what it costs, who runs it, where the risk sits, or what happens if the assumption fails.
Common Practice answers those questions and builds the systems that follow from the answers.
You have the strategy. You may have the research, the engagement report, the service blueprint, the board's approval in principle.
What you do not have is the answer to the next eight questions:
These are the questions that get handed back to you at the end of an engagement. They are the ones we take.
We do the build that everyone else skips.
It is the discipline of understanding a problem accurately, evaluating the real options, pricing the uncertainty, choosing, and then translating the choice into something that runs.
Five things have to be present at once, or the decision does not hold.
Research, data, institutional knowledge, market conditions, and what the people closest to the work already know.
Financial projections, scenarios, sensitivities, trade-offs, and the alternative structures nobody costed.
Leadership priorities, political reality, values, constraints, and who actually has the authority to approve.
Operating models, governance, delivery structures, workflows, and accountability that survives contact with the organization.
Resources, sequence, ownership, milestones, measures, and the capacity to learn while running.
Most firms are strong in one or two of these and hand off the rest. We work across all five, in the same engagement, with the same team.
LEARN ABOUT DECISION INTELLIGENCE →Not a deck. Not a framework. The things you can finance, staff, govern, and run.
How people, money, systems, and services actually work together on a Tuesday.
Sequenced plans with ownership, dependencies, timelines, and measures attached to named people.
Whether the thing can pay for itself, and under what conditions it stops being able to.
Where functions, risk, assets, intellectual property, and decision authority should sit — including when the answer is a different legal entity.
What each option costs you before you have spent the capital, the capacity, or the political credit.
Dashboards, models, assessments, and workflows that keep working after we leave.
Who does this on Monday, and with what?
We define how an organization, programme, service, or partnership functions in practice — down to the roles, the decision rights, the handoffs, and the capabilities you will need to hire or build.
The strategy is approved. Now what?
We turn an approved direction into coordinated delivery — sequence, workstreams, governance, resourcing, and the accountability structure that makes the plan real rather than aspirational.
Can this actually pay for itself, and for how long?
We build the financial logic underneath strategies, programmes, ventures, services, and institutional models — then we try to break it. If the model only works at an unreachable volume or an unlikely price, it is better to find that out now.
What do we actually know, and how confident should we be?
We produce evidence sized to a decision — not a literature review that arrives after the choice has been made. The output is calibrated to what has to be approved, and by whom.
What does each option cost us if we are wrong?
We compare the paths before you commit resources to one of them, including the paths that were ruled out too early and the ones nobody wanted to raise.
Where can this be faster, and where must a human decide?
We put data and AI to work inside the decision — for analysis, modelling, institutional memory, and monitoring — and we are precise about the boundary where automation stops and judgement starts.
Policy, investment, and modernization priorities that have to become operating and implementation systems inside a budget cycle and a procurement regime.
Funding models, initiatives, partnerships, governance, and the structures that outlive a grant cycle.
Operating models, financial structures, delivery systems, evaluation, and implementation across multiple jurisdictions.
Research, strategy, and institutional priorities translated into structures that can be staffed and financed.
Growth, new ventures, restructuring, governance, and capital decisions with consequences.
The financial, operational, structural, and implementation depth required to carry the work past the recommendation.
Common Practice works alongside firms leading strategy, service design, research, and organizational change — supplying the financial, structural, and implementation depth that turns a strong recommendation into something a client can approve and run.
We strengthen the work. We do not displace the lead firm, and we do not take the relationship.
Bring us into the engagement →Viability, structure, sequence, cost, ownership. The ones that arrive after the recommendation and belong to nobody.
The option we put forward has already been tested against the scenarios where it fails. You see those too.
Board cycles, budget submissions, procurement rules, delegated authority, ministerial and donor timelines. A model that cannot be approved is not a model.
We are not advisory. We remain inside the build until the system is operating and the people responsible for it can run it without us.
The model, the tool, the framework, the structure — built to be inherited, maintained, and used long after the engagement closes.
Tight when the question is sharp. Deep and multi-workstream when the build demands it. The engagement sets the size of the firm.
Every engagement produces method as well as answer. We are consolidating that method into a portfolio of Decision Intelligence products — financial-modelling systems, scenario tools, operating-model frameworks, decision-readiness assessments, implementation diagnostics, benchmark data, licensed methods, and AI-enabled workflows.
Client work solves the problem in front of us. It also builds instruments that work at greater scale.
A new strategy. A new operating model. A major investment. A structural transition. A growth scenario. An implementation that has stopped moving.
Tell us what has to be decided. We will test the options, build the model, and construct the path to execution.