Are there any placement reports that segregate outcomes by admission category?
No major IIM or top B-school publishes placement data broken down by admission category, and none has signalled plans to change that. Every official placement report aggregates outcomes across the entire batch, regardless of whether a student entered under General, OBC-NCL, SC, ST, or EWS quota.
What Official Reports Do and Don't Disclose
IIM placement reports follow a consistent template. Here is what you will and will not find:
| Disclosed | Not Disclosed |
|---|---|
| Batch size and students placed | Category-wise placement rates |
| Average, median, highest package | Category-wise average compensation |
| Sector and function breakdown | Individual outcomes by admission basis |
| Named recruiter list | Caste or reservation indicators |
| Domestic vs. international split | Performance gaps between categories |
For context, IIM Ahmedabad's 2024 report cited a median domestic CTC of ₹35 LPA with recruiters like McKinsey, BCG, Goldman Sachs, and HUL but offered zero category-level granularity.
Why Institutions Hold This Line
Three reasons are consistently cited. First, student privacy: tying compensation data to admission category effectively identifies individuals in smaller sub-groups.
Second, legal and ethical exposure: publishing disparate-treatment data, even unintentionally, creates discrimination optics that institutions want to avoid. Third, the placement narrative itself.
IIMs market their programmes on a unified merit-post-admission story, and disaggregated data complicates that message.
No IIM has deviated from this publicly. This is not an oversight; it is deliberate institutional policy.
What Academic Research Actually Finds
The closest thing to category-level outcome data comes from academic research, not official reports. Studies examining SC/ST/OBC outcomes at top IIMs generally find that, once admitted and placed, compensation gaps narrow considerably compared to the general-category cohort.
The pattern reported in this literature suggests that post-admission outcomes at IIM Ahmedabad, IIM Bangalore, and IIM Calcutta tend to converge, particularly in consulting and FMCG roles. Treat this as indicative, not definitive: research methodologies vary and sample sizes are often small.
What This Means If You Are a Reservation-Category Aspirant
You are not flying blind. Anecdotal data from alumni networks and forums like PaGaLGuY and MBA Crystal Ball provide a reasonable ground-level picture.
The broad signal from those communities is that Day 1 and Day 2 placements at the older IIMs are not visibly stratified by admission category, and that firms like Bain, Deloitte, and P&G do not filter shortlists by admission basis during campus recruitment.
The honest caveat: self-reported forum data carries selection bias. Students who had poor outcomes are less likely to post publicly. So the rosy picture in alumni communities may not capture the full distribution.
A Note on Small Cohorts
At institutes with smaller batches (under 120 students), combining a placement report with other public data could theoretically allow informal identification of category-wise outcomes. This is uncommon but worth knowing if you are evaluating niche or newer IIMs where sub-group sizes shrink further.
The practical takeaway is this: if category-wise data matters for your decision, official reports will not help you. Reach out directly to alumni from your category through LinkedIn or institute-run diversity networks.
That conversation will be more informative than any published PDF.
Pro Tip: Contact the placement office of your target IIM directly and ask whether they can connect you with alumni from your admission category; most offices will facilitate this informally even if they cannot publish aggregate data.