Which undergraduate engineering college in India (non-IIT) offers the best placement outcomes?

Evaluate NITs, IIITs, BITS, VIT, and other top private engineering colleges based on placement statistics, average salary packages, top recruiters, and industry connections.

# Aplly.xyz Case Study Submission

## Title
Which undergraduate engineering college in India (non-IIT) offers the best placement outcomes?

## Type
Multi-Criteria Product Comparison

## Difficulty
Intermediate

## Estimated Time
60 minutes

## Overview
Evaluate NITs, IIITs, BITS, VIT, and other top private engineering colleges based on placement statistics, average salary packages, top recruiters, and industry connections.

## Case Details

Function Focus: Multi-Criteria Product Comparison — manual reasoning, decomposition, and critical judgment (no spreadsheet or AI tool permitted in Phase 1)

Scenario:
You are the analyst at a fictional consultancy ("Praxis Advisors") tasked with answering: Which undergraduate engineering college in India (non-IIT) offers the best placement outcomes?. You have a clean, synthetic dataset described below. You must produce a defensible answer using structured reasoning — no tool-assisted shortcut on the first pass.

Dataset Structure:
- institution
- program
- duration_months
- total_fee_lakhs
- avg_package_lakhs
- placement_pct
- roi_score
- accreditation
- entrance_exam
- faculty_student_ratio
- rank_nirf

Tasks:
1. Define the evaluation criteria for the choice and assign weights to each, justified explicitly.
2. Score each alternative by hand against the criteria using the dataset columns.
3. Compute a weighted total and rank the alternatives; show the arithmetic.
4. Run a sensitivity check: change the top two weights by +/10 points and note whether the winner changes.
5. After the manual scoring, redo it in a spreadsheet and reconcile any ranking differences.

Expected Output:
A one-page recommendation memo: criteria & weights, scorecard table, final ranking, sensitivity result.

Evaluation Criteria:
Explicit and justified weights, arithmetic correctness, meaningful sensitivity analysis, defensible final ranking.

## Data Sources

| institution | program | duration_months | total_fee_lakhs | avg_package_lakhs | placement_pct | roi_score | accreditation | entrance_exam | faculty_student_ratio | rank_nirf |
|---|---|---|---|---|---|---|---|---|---|---|
| IIMA | PGP | 24 | 35 | 34.2 | 98 | 9.5 | AACSB | CAT | 6:1 | 1 |
| IIMB | PGP | 24 | 33 | 32.5 | 97 | 9.2 | AACSB | CAT | 6:1 | 2 |
| IIMC | PGP | 24 | 31 | 30.8 | 96 | 9 | AACSB | CAT | 7:1 | 3 |
| XLRI | BM | 24 | 28 | 28.5 | 97 | 8.8 | AACSB | XAT | 7:1 | 6 |
| FMS | MBA | 24 | 2.5 | 27 | 96 | 9.5 | NBA | CAT | 8:1 | 4 |
| SPJIMR | PGDM | 24 | 27 | 26.5 | 95 | 8.5 | AACSB | CAT | 8:1 | 9 |
| MDI | PGPM | 24 | 25 | 25.2 | 94 | 8.3 | AACSB | CAT | 9:1 | 10 |
| ISB | PGP | 12 | 42 | 35 | 99 | 9 | AACSB | GMAT | 5:1 | 5 |
| IIT Delhi | MBA | 24 | 16 | 22.5 | 92 | 8 | NBA | CAT | 8:1 | 15 |
| UpGrad | Online MBA | 24 | 2.5 | 8.5 | 72 | 5.5 | UGC | None | 15:1 | 999 |


Full dataset: https://github.com/arora200/aplly_case_db/datasets/058-education-career (synthetic, 10 records)

## Solution Frameworks
Multi-criteria weighted scoring, pairwise trade-off analysis, cost-benefit decomposition, sensitivity/robustness check

## Solver Guidance & Tutorials
_Solver guidance added by the pipeline (tutorial links) — see `solver_guidance` field._

## What You'll Learn
- Turn vague preferences into weighted criteria
- Build a transparent scorecard
- Test how fragile your winner is

## Tags
Engineering College, NIT, BITS, Placement, India

## Registration Links
Register as Solver / Register as Evaluator