Understanding Simulation / Modeling
In early design stages, researchers spend significant time identifying possible solutions to user problems. This can create bias if a team becomes too attached to a perceived ideal solution. Modeling and simulation help test these assumptions, collect immediate feedback, and explore alternatives before final launch.
This is especially valuable in digital environments, where online models can be accessed by many users at once. User experience data, heat maps, analytics, and other forms of simulation data collection can then be analysed to inform decisions.
A full or partial product or service can be modelled to test design specifications. Model simulation helps bring ideas to life, assess real-world value, and better understand customer experience. It also helps uncover gaps in design thinking that may otherwise remain hidden until launch.
Advantages of Simulation / Modeling
1. Large user participation
If the simulation is online, many users can be involved in testing.
2. Validation of research findings
Testing reveals insights, glitches, and opportunities that early research alone may miss.
3. Wide applicability
The simulation research method can be used across ideas, formats, and stages of design or redesign.
4. Issue and error identification
Modeling and simulation help detect issues, errors, and biases introduced during solution development.
5. End-user engagement
Simulation enables direct feedback from potential users, giving clearer insight into value and experience.
Challenges of Simulation / Modeling
1. Added time and cost
Despite its value, modeling requires recruitment, testing, iteration, and retesting, which increases effort and investment.
2. End-user recruitment challenges
The quality of insights depends heavily on recruiting the right participants. Poor recruitment can lead to missed findings.