Decision Support Systems (DSS): simulating scenarios by changing parameters and assumptions is commonly called what?

Introduction / Context:
Managers often want to understand how outcomes change if key drivers move up or down. Decision Support Systems include interactive tools to vary inputs and immediately see projected impacts on KPIs such as profit, service levels, or risk. This capability underpins planning, budgeting, and sensitivity analysis across industries.

Given Data / Assumptions:

• We are discussing scenario exploration using models.
• Users manipulate parameters and observe recalculated results.
• The goal is insight, not automated learning.

Concept / Approach:
“What-if analysis” refers to varying inputs to a model to see effects on outputs. It differs from exception reporting (flagging out-of-range values) and from artificial intelligence (learning or optimization). While the activity could be described as computer-assisted experimentation, the standard term in DSS and spreadsheet modeling is “what-if analysis.”

Step-by-Step Solution:

Verification / Alternative check:
Business analytics texts and spreadsheet software (e.g., goal seek, data tables, scenarios) label this capability as what-if analysis.

Why Other Options Are Wrong:

• Artificial intelligence: focuses on learning/heuristics, not simple parameter sweeps.
• Exception report: monitoring deviations, not scenario modeling.
• Computer assisted experimenting: descriptive phrase, but not the standard term.

Common Pitfalls:
Confusing what-if with optimization; what-if explores, while optimization searches for the best set of inputs.

Final Answer:
What if analysis