Choose a decision the model can inform.
A useful project starts with a decision: whether to change a handoff, add capacity to a shared function, revise an approval rule or adjust the order of work. Agree the outcome and the constraints before comparing options.
Sales response time, project delivery duration and service completion are possible targets. Define the population, time window and quality requirements for the chosen measure. A faster process may still be unsuitable if it increases rework or shifts an unresolved queue to another team.
Represent the roles and the work between them.
An organization model describes what each role receives, what it needs to decide, the work it can perform and what it passes downstream. Dependencies, availability, capacity and operating rules constrain those actions.
Agents can investigate alternative explanations and explore proposed arrangements within that representation. The scope is the behavior relevant to the task. The model should be checked against observed records before its outputs are used to choose an intervention.
| Model element | Questions to resolve |
|---|---|
| Responsibilities | Who acts, who decides and who owns the handoff? |
| Information | What is available when a decision is made? |
| Capacity | Which people or shared functions limit throughput? |
| Constraints | Which quality, resource and timing conditions must hold? |
Prepare records that explain the process.
An initial evaluation can use authorized exports such as task histories, project milestones, service records and process documents. Choose the fields needed to reconstruct the relevant work, including dates, statuses and links between related events.
Agree the data scope and de-identification treatment with the data owner. Missing records, inconsistent definitions and incomplete time coverage become explicit gaps to resolve. The evaluation cannot establish a mechanism that the supplied evidence does not support.
Compare feasible alternatives on the same basis.
Polaris can use data recomputation, workflow replay, simulation or a code prototype according to the question. Keep the starting conditions and comparison cohort consistent, and define the success and failure conditions before running a candidate.
The R&D sandbox illustrates this approach with a shared certification queue. Its modeled change is an offline estimate using constructed data. Such an estimate helps select what to investigate or pilot; actual operational impact requires a separate observation period.
Give the operating team a decision they can inspect.
An evaluation brings together the baseline, evidence for the bottleneck, competing explanations, candidate changes and results of the available checks. It should also preserve failed attempts, unresolved assumptions and the conditions under which a proposal may stop working.
The next decision may be to gather missing evidence, revise the model or run a limited business pilot. Agree the owner, change scope and measurement plan before introducing a change into everyday work.
Questions before an evaluation
Do we need a complete digital copy of the company?
No. Start with the roles, records and dependencies needed for one business question. Expand the model only when additional context changes the decision.
Can a simulation determine the best organization structure?
It can compare defined alternatives under stated assumptions and constraints. The preferred candidate still needs review and validation in the operating environment.