NGO programme managers, monitoring and evaluation officers, and executive directors in India responsible for specially-abled placement programmes who want to move from activity-based reporting to outcome-based accountability.
Most NGOs report placements as the final metric — but placements without retention, salary data, and post-placement outcomes are incomplete. Donors, corporate partners, and the candidates themselves deserve better data.
A complete placement metrics framework: which KPIs to track at each stage, how to build a simple data collection system, how to analyse trends, and how to use data to improve placement quality — not just placement quantity.
The most effective NGOs in India's specially-abled employment ecosystem share one characteristic: they are relentlessly data-driven. They don't just know how many candidates they placed. They know how many stayed. They know what they earn. They know which employers produce successful outcomes and which don't. And they use that knowledge to continuously improve.
This guide gives you the complete measurement framework to build that capability — starting with the metrics that matter, and ending with a reporting system that serves your candidates, your funders, and your own programme decisions.
The Three Levels of Placement Measurement
Level 1: Activity Metrics (What You're Doing)
Activity metrics measure the volume and reach of your programme. They're easy to collect but insufficient alone:
- Number of candidates enrolled in the programme
- Number of training hours delivered per candidate
- Number of employers engaged (meetings held, MoUs signed)
- Number of job applications submitted on behalf of candidates
- Number of interview opportunities generated
Level 2: Output Metrics (What You're Producing)
Outputs are the direct results of your activities — closer to impact but still not the full story:
- Number of placements (first job secured)
- Placement rate (placements ÷ candidates who completed programme)
- Time to placement (days from programme completion to first placement)
- Salary at placement (range and median across placements)
- Employment type (full-time, part-time, contract, apprenticeship)
- Sector and function distribution of placements
Level 3: Outcome Metrics (What's Actually Changing)
Outcomes measure real change in the candidate's life — and in employer behaviour. These are the hardest to collect and the most valuable:
- 3-month retention rate: Percentage of placed candidates still employed at 90 days
- 6-month retention rate: Industry benchmark for sustainable employment
- 12-month retention rate: The gold standard metric for placement quality
- Salary progression: Salary at 12 months vs salary at placement
- Job satisfaction score: Candidate-reported satisfaction at 3, 6, and 12 months (simple 1–10 scale)
- Accommodation adequacy score: Whether workplace accommodations were provided and effective
- Employer satisfaction score: Employer-reported satisfaction with the placement and programme
- Career progression rate: Percentage promoted or moved to better roles within 2 years
The Metrics You Should Disaggregate (Always)
Aggregate data hides important patterns. Every metric should be disaggregated by:
- Ability profile type: Visual impairment, hearing impairment, locomotor, intellectual, multiple — outcomes often vary significantly by type
- Gender: Specially-abled women face compounded barriers; their placement and retention data deserves separate analysis
- Education level: Graduate vs below-graduate placements may show very different trajectories
- City/geography: Mumbai, Bengaluru, Delhi placements often perform differently from Tier 2 and Tier 3 city placements
- Employer type: Large corporate vs SME vs government placement outcomes often differ substantially
- Sector: IT vs BFSI vs manufacturing vs NGO sector — retention and progression rates vary
Building a Simple Data Collection System
You don't need enterprise software to track placement data effectively. A well-structured Google Sheets or Airtable system can manage 200+ candidates and produce dashboard-quality reporting.
Core data tables to maintain:
Candidate Master Table: Candidate ID, name (for internal use), ability profile, education, location, programme enrolment date, programme completion date, skills assessed, job-readiness score at completion.
Placement Table: Candidate ID, employer ID, placement date, role title, function, salary at placement, employment type, whether accommodation was provided, placement officer ID.
Follow-up Table: Candidate ID, 30-day check-in date and status, 90-day check-in date and status, 6-month check-in and status, 12-month check-in and status, salary at 12 months, satisfaction score, exit reason (if no longer employed).
Employer Table: Employer ID, company name, contact person, sector, accessible locations, total placements, total active employees, employer satisfaction score, MoU status.
The Follow-Up System: Where Most NGOs Lose Data
Post-placement data is the most valuable and most commonly lost. Candidates move, change phones, and lose contact. Employers don't proactively report. Without a systematic follow-up process, your outcome data disappears.
Best practice follow-up system:
- Collect three contact points from every candidate at placement: personal phone, family emergency contact, and personal email
- Schedule automated reminders for follow-up calls at 30, 90, 180, and 365 days from placement
- Maintain a WhatsApp group for all placed candidates by cohort — regular check-ins, support resources, peer connection
- Assign each placed candidate to a placement support officer with accountability for follow-up completion
- Set a target: 80%+ follow-up response rate at 6 months. Below this, your outcome data is not reliable.
Using Your Data to Improve Programme Quality
Data collection is only valuable if it drives decisions. Establish a quarterly data review process:
- Employer performance review: Which employers have the highest 6-month retention rates? Which have the lowest? What explains the difference? Concentrate future placements with high-retention employers. Investigate or disengage from low-retention employers.
- Skill gap analysis: What skills do placed candidates report needing that they didn't have at placement? Update your training curriculum to address these gaps.
- Accommodation gap analysis: What percentage of placed candidates report that promised accommodations were not provided? Use this data in employer conversations and MoU negotiations.
- Salary benchmarking: Are your placements at or below market salary for the roles? If below, why? Is this a negotiation training gap or an employer behaviour issue?
Reporting That Wins Funding and Partnerships
Your placement metrics are also your fundraising and partnership development assets. Funders and corporate CSR partners make decisions based on evidence of impact. An annual impact report that includes:
- 12-month retention rate (not just placement count)
- Average salary at placement and at 12 months (showing progression)
- Disaggregated data by ability profile, gender, and city
- Case studies alongside the numbers
- Year-on-year improvement across all key metrics
...is dramatically more compelling than a report that says "we placed X candidates this year." The second number is easy to inflate. The first set of metrics is hard to fake — and that's why funders trust it.
Your Action Step
Audit your current data collection this week. Can you answer these three questions with confidence: What is your 6-month retention rate for the last cohort? What is the average salary at placement vs 12 months? What is the employer satisfaction score across your top 10 partners? If you can't, your data infrastructure needs work — and this guide gives you the framework to build it.
