Marden
A fictional company.
270 people in European technology and business services. Every figure and sentence on this page is precomputed for it.
Set a restructuring on Marden, a synthetic 270-person company, then change the pace or the support and see where the modeled load travels.
Real engagements go far deeper. This public view is a simplified read on a synthetic company. Full work adds scenario sensitivity, role-level network structure and decision alternatives, on your own organization.
Full engagements use masked, role-coded positions, never names.
Explore a real decisionHow the Decision Room is built.
Marden
A fictional company.
270 people in European technology and business services. Every figure and sentence on this page is precomputed for it.
Reading the numbers
A range, not a point.
Each headline figure spans the middle half of the modeled outcomes, 25th to 75th percentile. A trajectory shows how the change is expected to unfold over 26 weeks.
Subject
Roles, never people.
Demand load and delivery trajectory are read per department under the plan. The model projects how work is allocated.
Changeprint
A pattern, not a score.
The whole picture of one WhatIF: four headline ranges, an executive read, what changed and where load traveled.
Calibration
4,500+ studies behind the model.
Its response parameters draw on published research into how people responded to organizational change. That sets the bounds; it does not turn any single run into a forecast.
Security
Your data stays yours.
Every simulation runs offline, on an engine we built, and no outside AI ever reads what you share. It never leaves the EU, stays encrypted in transit and at rest, and each client can open only its own results.
Engine
200+ calibrated coefficients.
In a full engagement they span the whole state model: structure, dependencies between departments and how concentrated they are, demand load on roles, delivery effects, and how all of it moves over time. Every run records its version and scenario.
Loadpath
A route, not a verdict.
Where added coordination, dependency or transition load travels between departments over the simulated window. One to three are shown, most consequential first.
Depth
1,500 runs per decision.
The current level for a full engagement, and what makes every output a distribution of outcomes.
Switchpoint
A position in the network.
A role that links functions otherwise weakly connected. It follows from the structure of this Base State and says nothing about the person in it.
Purpose-built
Made for one job: simulating how organizations behave.
Chat-based AI writes one likely word after another, so a question asked twice can get two different answers. Ours has no language model inside; it computes how roles, teams and departments respond to a decision. It is deterministic: pick the same tiles and the figures never change.
These figures
Each range rests on 100 runs.
Every one is paired with a Base State run on the same random seed. Pace spreads an equal total change over a 30, 60 or 90-day window. Demand load, delivery and recovery are measured on the roles a decision reaches; Loadpaths trace what travels beyond them. Not modeled: span-of-control workload, or how people anticipate an announcement. This is a demonstration: the model is calibrated on published research and has not been compared with a real organization's outcomes.