How to Use DecisionMind
From your data to a defensible, paper-grounded decision in five steps: including everything you need to prepare your data and read your results.
How it works
Add your decision table as CSV, Excel, JSON or TSV.
Confirm criteria directions (benefit/cost) and weights.
Get a recommendation or choose any of 555 methods.
The engine computes the ranking and every intermediate step.
Export HTML/PDF/Word/Excel with the full transparency record.
DecisionMind reads a simple decision table: alternatives in rows, criteria in columns.
Accepted file formats
- CSV: comma, semicolon, tab or pipe separated (auto-detected)
- Excel (.xlsx)
- JSON
- TSV (tab-separated)
- Turkish character encodings are handled automatically.
Table structure
- First row = criteria (column headers)
- First column = alternative names
- Each cell = the value of that alternative on that criterion
| Alternative | Cost (USD) | Quality | Delivery |
|---|---|---|---|
| Supplier A | 120 | 8 | 7 |
| Supplier B | 95 | 6 | 9 |
Example: 2 alternatives on 3 criteria. “Cost (USD)” is auto-detected as a cost (lower-is-better) criterion.
Criterion direction (benefit / cost)
- A header containing “cost”, “min” or “lower-is-better” is treated as a cost criterion (lower is better).
- Otherwise it defaults to a benefit criterion (higher is better).
- You can override every direction on the variables screen before running.
Data types (crisp & fuzzy)
Besides plain numbers (crisp), DecisionMind accepts uncertain / fuzzy data. The cell format depends on the type:
| Type | Example cell |
|---|---|
| Crisp | 7.5 |
| Intuitionistic (IFS) | (0.6, 0.3) |
| Pythagorean (PFS) | (0.7, 0.4) |
| Fermatean (FFS) | (0.8, 0.5) |
| Neutrosophic (SVN) | (0.6, 0.2, 0.3) |
| Grey / Interval | [4, 7] |
| Hesitant (HFS) | {0.4, 0.6, 0.7} |
Ready to analyze your own decision?
Start an analysis