If we’re aiming to not simply alleviate poverty but eliminate it altogether, we need to understand its causes. But we also need to know what non-poverty looks like.

Until recently, this has not been easy. Now, technological innovation is helping us achieve things that were once impossible, and the effects are far-reaching.

At Fundación Paraguaya, we have developed a methodology called Poverty Stoplight. To assess levels of poverty, we show people a series of three photographs and ask them to choose the one that best describes their situation. We do this in each of 50 “critical indicators”, such as access to water, levels of nutrition, dental care and so on. These pictures are colour-coded to represent degrees of poverty: red is critical, yellow is poor and green is non-poor.

This method is based on the Anna Karenina principle: “Happy families are all alike; every unhappy family is unhappy in its own way”. The same is true of poverty.

Previously we collected this data using traditional pen and paper, which meant the assessment of a household could take an entire afternoon. But then we partnered with Hewlett Packard to convert the process into an app displayed on a tablet device, and now people can simply tap on the appropriate photograph.

But what is taking place here is more subtle than that. The personalized strategy reveals critical data about the particular poverty of each family. More than that, families are able to self-diagnose their level of poverty and, by glimpsing alternative photographs, visualize potential solutions.

The technique allows us to ask unusual questions. For example: do you feel the capacity to plan your future? An illiterate woman in a rural village has probably never considered such a question. She may tap the red or yellow picture, but in considering the green she sees what non-poverty looks like. The result is that she may well say: “I can achieve that.” Often, the proof that she can is there in her village – someone is already doing it.

There are variations in every poverty indicator in every slum in the world: there is a family who, by virtue of their income, should not be able to vaccinate all their kids, but they do. There is a family who have enough money for a latrine, but they don’t buy one. The solutions to poverty, then, often come from within.

This change in the way we collect data is affecting public policy. Governments are interested in Poverty Stoplight because it tells them who needs what, from the viewpoint of those in need, rather than the officials. 

We are also seeing another change: we’re moving away from the measurement of outputs and towards the assessment of outcomes. This is a very powerful distinction. Now that we are able to plot the specific results of government spending, measurements of budgetary outlay alone have become redundant.

A government may report that they have provided 93% access to health clinics, but if there is only 53% participation, the 93% means little; there is something fundamentally wrong. A training centre may boast that it has delivered 180 hours of training, but that is not the point – do people have the skills or don’t they?

Because we can map territorial visualizations, this allows us here in Paraguay to work with perhaps 30 different agencies and 15 NGOs, entering a village of 2,000 homes. Every agency is able to focus on their specialization: they know who needs vaccines and which houses are not connected to safe water, and so on.

Looking at poverty in communities and households means that data is no longer aimed at policy-makers alone, for aggregated indices; it can be shared with the poor in a participatory process that empowers them, and offers them a peek – often for the first time – at what non-poverty looks like.

Author: Martin Burt is Founder and CEO of the NGO Fundación Paraguaya.

Image: A sister of the Franciscan order plays with children in Lambare city, near Asuncion, April 2, 2014. REUTERS/Jorge Adorno