A practical modeling workflow
Define the question, choose the scope, check a baseline, then compare scenarios one change at a time.
State the decision the model should support. Then choose the outputs that distinguish a good alternative from a bad one, such as waiting time, throughput, cost, failures, or inventory.
A clear question also tells you what the model can leave out.
The question decides what goes into the model and what you need to measure.
- 1Decision
Define the question and required outputs.
- 2Scope
Keep only decision-relevant detail.
- 3Baseline
Represent the reference system.
- 4Check
Test the logic and compare with known behavior.
- 5Experiment
Change an input and compare the results.
Set the system boundary, time horizon, level of detail, and main assumptions. Start simple. Add detail when it changes an output or corrects a known weakness.
The baseline represents the current system or another agreed reference case. Check that it can reproduce behavior you already understand before using it to judge alternatives.
Run simple cases where you know what should happen. Check connections, routes, timing, units, and totals. Then compare the baseline with real observations or ask someone who knows the process to review it. A model can run without errors and still give a misleading answer.
Keep the baseline unchanged and vary only the inputs named by the experiment. If the model contains random variation, run enough replications to see how stable the result is. Save the assumptions and seeds so a surprising run can be repeated.