A field researcher interviewing a group of young women seated on a verandah

Measure whether people's lives changed - not simply whether activities happened.

program data should do more than fill a final report. We help partners define the outcomes that matter, track progress while a program is running and use the evidence to improve delivery.

Define the outcomes you want to be accountable for

Measure the climb

Start with the question that matters

  • Instead of only asking how many people completed training,ask whether they got jobs and stayed in them.
  • Instead of only asking how many entrepreneurs received support,ask whether revenue or income grew.
  • Instead of only asking how many loans were facilitated,ask whether borrowers used capital productively, repaid successfully and progressed in formal finance.

The rungs we track

What we can measure

A woman taking part in a field survey

Jobs.

Placement, wages, retention and progression.

How we measure

What we do

A field team speaking with a woman on her veranda
  1. Build a theory of change.

  2. Define indicators.

  3. Establish baselines where appropriate.

  4. Build person and program tracking.

  5. Create dashboards.

  6. Conduct surveys and outcome studies.

  7. Analyse results.

  8. Identify what is and is not working.

  9. Feed insights back into implementation.

Evidence that changes decisions

A Samhita principle

Evidence should change decisions. If measurement only tells us what happened after a program has ended, we have used it too late.

Our methods

Program evaluation methods

A field team reviewing survey data with a respondent
  • We run baseline, midline, and endline evaluations on a sample of people, to build a full picture of what an intervention actually changed, not just what it delivered.

  • We match the sampling method to what each cohort allows, random or stratified, since most of our programs run without a formal control group to compare against.

  • We capture composite impact through quantitative measures, so the aggregate effect of an intervention is measurable.

  • We add in-depth interviews, case studies, and focus group discussions with a selected sample, to surface the nuanced processes a number alone can't show.

  • We build indices like the Income Index, Economic Empowerment Index, and Resilience Index, so empowerment and resilience get tracked with the same rigour as income.

Proof of the climb

A field researcher interviewing women seated on the floor

In partnership with Flipkart
5Interventions, each tied to a life outcome
3Measurement rounds on the same people
0Outputs-only indicators

Most CSR reporting stops at outputs: how many people attended a training, how many centres got built. That's useful for tracking delivery. It says little about what actually changed in someone's life.

Flipkart's program is a useful example of how our framework closes that gap, because it runs five interventions at once, and every one of them is tied to a specific outcome in a person’s life.

  • Financial and digital literacy training wasn't tracked as "training completed." We tracked whether people opened a dedicated, goal-based savings account afterward, because that behaviour is what proves the training changed how someone actually manages money.
  • Skilling for employment, delivered through spoken tutorials in multiple languages, was tracked through job placement and income change after the course, not attendance.
  • Healthcare and menstrual hygiene interventions, including sanitary napkin kiosks and affordable diagnostics, were tracked against awareness and actual use of services, since access to a service and a change in health behaviour are two different things.
  • Entrepreneurship training was tracked against the specific skills and mindsets micro-entrepreneurs could demonstrate afterward.
  • Early childhood education, delivered through Anganwadi Bal Vidyalayas, was tracked against something most programs miss entirely: whether it freed up a mother's time to work.

That's what person-first measurement means in practice. It starts from whether the person receiving a service is measurably better off, and picks the indicator that actually proves it, rather than the one that's easiest to count.

It's also continuous. Each of these chains gets revisited at baseline, midline, and endline, on the same people, so we can see whether early gains hold, fade, or compound over the life of the program. A number that looks strong at midline and drops by endline tells a very different story than one that keeps climbing, and only continuous tracking catches that difference.