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Simulation: Scenarios, Solvers, and Temporal Simulations

Equipe Ontologie
Equipe Ontologie

Modeling your data is valuable. Being able to simulate the impact of your decisions before applying them is even better. The new Simulation module in Ontologie lets you create hypothetical scenarios, run optimization solvers, and simulate how your data evolves over time — all without touching your production data.

Why simulation matters​

Ontologies model the current state of your systems, processes, and data. But business decisions often require answering questions like:

  • What happens if I remove this supplier? Which processes are affected?
  • What is the best allocation of resources to minimize costs?
  • How will the workload evolve if I add 3 clients per month for a year?

Until now, these analyses were done in separate spreadsheets, disconnected from your data model. The Simulation module brings these capabilities directly into Ontologie.

What's new​

Parametric scenarios​

A scenario is an isolated copy of all or part of your ontology in which you can freely modify data without affecting production.

How it works:

  1. Create a scenario from your current ontology or from a selection of entities.
  2. Modify the data: add, delete, or update entities and relations.
  3. Compare: view the differences between the scenario and production (additions, deletions, modifications).
  4. Analyze the impact: the system automatically calculates which entities, relations, and workflows are affected by your changes.
  5. Apply or discard: if the scenario proves successful, merge the changes into production. Otherwise, delete it with no consequences.

Scenarios use a copy-on-write technique: only the modified data is duplicated, making scenario creation fast and storage-efficient.

Practical example: you are considering reorganizing your ontology by merging two entity types ("Prospect" and "Lead") into one ("Contact"). You create a scenario, perform the merge, and the impact analysis shows that 3 workflows and 2 dashboards referencing "Prospect" will need to be updated.

Optimization solvers​

Solvers let you define optimization problems on your data and obtain automatically computed solutions.

A solver is defined by:

  • Variables: the elements the solver can change (e.g., resource assignments, quantities).
  • Constraints: the rules that must be respected (e.g., maximum budget, limited capacity, deadlines).
  • An objective: what you want to minimize or maximize (e.g., total cost, processing time, coverage).

The solver explores possible combinations and returns the optimal solution or the best solutions found.

Practical example: you have 15 projects to assign to 5 teams, each with limited capacity and specific skill sets. The solver calculates the assignment that minimizes total completion time while respecting the skill constraints.

Temporal simulations​

Temporal simulations let you project how your data will evolve in the future based on rules you define.

You configure:

  • A time horizon: how many days, weeks, or months to simulate.
  • A time step: the granularity of the simulation (day, week, month).
  • Evolution rules: how the data changes at each step (e.g., +3 clients/month, -5% attrition, data volume doubling every 6 months).

The simulation generates a time series of your ontology's state at each time step. You can visualize trends, identify tipping points, and adjust your rules.

Practical example: you simulate the growth of your customer base over 12 months with an acquisition rate of 50 clients/month and an attrition rate of 8%. The simulation shows that by month 9, the number of support tickets will exceed your current team's capacity.

Getting started​

  1. Open your workspace and navigate to Simulation in the main menu.
  2. Create a scenario by clicking "New scenario" and selecting the entities to include.
  3. Modify the data within the scenario and review the impact analysis.
  4. For solvers: define your variables, constraints, and objective in the solver editor.
  5. For temporal simulations: configure the time horizon, time step, and evolution rules.

Scenarios are accessible to all workspace members. Solvers and temporal simulations require administrator access for configuration.

Next steps​