Effective Strategies for Reaching the Poor
The commitment of the Microcredit Summit a year ago to reach the worlds poorest families, has raised the profile of poverty ? focussed microfinance as a poverty - alleviation tool. The first step is obviously to establish who are �the poorest� which the Summit usefully defined as those people in the bottom fifty percent of the people, living below a country�s nationally defined poverty-line.
This target poses a challenge for microfinance institutions (MFIs), to reach this target group, to demonstrate that they have been reached, and to develop strategies to alleviate poverty amongst this group.
The Small Enterprise Foundation (SEF), workiing in the impoverished former homeland areas of the Northern Province, South Africa, has long made a commitment to reaching the poorest. Over time we have come to realise more and more that this is no easy task. Challenges lie in three main areas:
SEF dose not have all the answers, nor have we thought of many of the questions! However, we are actively pursuing improvements in all of these areas, which we believe are the key to realising the bold objective of the Summit.
- effective targeting mechanisms to ensure that a high number of the target group are reached;
developing effective support mechanisms which provide savings and credit services within a framework which develops the capacity of members to maintain sustainable businesses ;
developing impact monitoring systems which provide a learning environment for all staff and members, which can demonstrate the success or failure of the programe to alleviate poverty.
SEF was set up as a poverty-alleviation program. One of the poorest areas in the country was selected as the operational area, and a credit methodology was designed which offered small loans through group-based lending , following the theory that small loans and high transaction cost in terms of time spent to enter the program and during meetings, would deter all but the very poorest form joining.
In reality SEF found that the need for credit is so great that comparatively wealthy people would join the program, and remain members for a long time in the hope of larger future loans. Not only did this mean that we were not just reaching the poor, but we found that membership of better off members served as an active deterrent for the very poor, and the target population was not being helped.
In response to this, the Tshomisano Program (TCP)1 was set up with the mandate to develop an active targeting system which would allow identification of the poorest people. TCP targets the poorest 30 percent of the population of the province, which more or less corresponds to the bottom fifty percent of those living below the poverty-line.
Work to develop a targeting system, drawing on the experience of Professor Sukor Kasim with CASHPOR, resulted in the Visual Indicator of Poverty test ( VIP ). This involves field workers scoring the external conditions of people�s houses according to a check list. Thus those people living in houses constructed from mud bricks, with poor quality thatch roofing, small windows and in a general state of disrepair, tend to be selected as the poorest. Those with cement bricks, zinc roofing, larger windows, a pit latrine and generally better constructed housing, do not qualify to benefit from the program.
This system was operationalised and used for some years by the program. However, reports of problems by field staff raised concerns.
These mostly centered on people who had been denied access to the program despite obvious signs of poverty and the support of members of the community, on the basis of their housing conditions. There were also reports of people joining the programe who the field staff felt were not poor, but who qualified on the basis of the VIP.
A pilot study was set up to compare Participatory Wealth Ranking (PWR) with the VIP. PWR allows communities to rank themselves according to their own perceptions of poverty. Detailed discussions are held with a large number of people in each community to define poverty, and to rank the community according to their criteria. A map is first drawn by a community group and a household list is then generated from this, and the names written on to individual cards. Reference groups are then set up to assess the relative wealth of the households, by sorting the cards into piles with the poorest in one pile, the next poorest in the next and so on. The results are triangulated by using a minimum of three reference groups-consistency between the groups verifying the results.
The comparison of the VIP with PWR demonstrated the inaccuracy of a system based on static, externally judged criteria, when compared against local judgment of poverty. Many instances were cited of people living in poverty, whilst having reasonable housing conditions, constructed prior to the main earner dying or deserting the family. In addition there are many people who are living in poor quality housing, constructing new homes or having their main home elsewhere who falsely qualified as amongst the poorest under the VIP.
In comparing the VIP and PWR, the VIP was seen to be at best 70% consistent with the PWR results (in some cases below 50%). Perhaps more worryingly, however, was the inclusion of large numbers of households from the richest segments of the community amongst those defined to be the poorest by the VIP. In some cases one - third of the list of households defined as the poorest by the VIP was actually made up of some of the richest in the community, as determined through PWR.
These results convinced SEF of the need to operationalise PWR in place of the VIP. The system has now been operationalised, with staff being trained and assessed, and an operational manual produced.The method has proved to be very reliable in terms of ranking households according to the criteria considered important by the communities with which TCP works. Criteria most commonly used to define poor households are : lack of food and shelter ; unemployment; lack of income ; large numbers of dependents; children not attending school ; and lack of clothes.
The system is not yet perfect. There have been considerable challenges faced in designing a cost-effective operational system based on participatory mapping and wealth ranking, particularly given the size of the target villages (commonly 3-4000 people). However, we believe that the method is effective in identifying the poorest in a way which is transparent and acceptable to the communities with which we work.
Case-Study: Wealth Ranking in Bhungeni
Faced with a village of almost 5,000 people and eight field workers expecting to be trained in PWR and to have the effectiveness of the method demonstrated to them, we realized the challenge facing us in using the method in South Africa. Villages are usually not tightly knit communities, but sprawling areas with several hundred, if not thousand households, with high mobility and differentiation. Wealth Ranking relies on people�s knowledge of each other - could this apply in the South African context?
We commenced the task by mapping the village (on the floor of a church, using chalk). About 30 people arrived for an introductory meeting. After some discussion it was agreed that people should divide themselves into groups according to section. Initially three sections were formed, and the participants easily grasped the concept of mapping and began the task. Quickly it became apparent that there were in fact 6 rather than 3 sections. Some sections were under-represented in the meeting, and there was some difficulty in these sections in drawing the map. Some participants, therefore, left to find people from the other sections to join in. Obtaining good representation from all sections of the village is critical to the successful mapping of a large village.
Mapping proceeded easily (and noisily), and within three hours we had mapped and listed the names of 736 households. Importantly by generating six rather than three sections, the number of households which had to be ranked per section was more or less 100 (approximately the number of cards people can sort before participants become).
Participants assisted with writing a list of household names, the facilitators checking that these were the names commonly used, copying these names on to cards, and making a copy of the map onto flip chart paper. The handing over of these tasks to the participants is essential to enable the facilitators to monitor and facilitate, rather than attempting to undertake three time-consuming tasks in each section.
The mapping was a great success. There were no problems in identifying and naming all the households. In one section for example, six people managed to map and name 211 households. The map was compared with one previously done by SEF under the VIP system and its accuracy was confirmed.
Further experience of mapping even larger village has shown that even 1000 households can be mapped and names listed in 2-3 hours, provided there is good representation from all sections or the village.
The next challenge was how to rank the 736 households. Ranking involves discussing concepts of poverty and wealth, so as to stimulate thinking and to gain a consensus for ranking. The cards are then discussed in turn and thereby sorted into different piles dependent on the wealth of the household. The ranking is repeated for at least three different reference groups so as to ensure triangulation and consistency of the results.
The process is time consuming and strenuous, and once people become tired, the accuracy of the ranking is rapidly lost, therefore to attempt to sort more than 100 cards (ideally much less) is problematic.
Division of the village into sections achieved part of the solution?however, one section numbers over 200 households. The card sorting process, therefore, had to be very carefully monitored so as to stop the process when participants became tired. If a sorting was not completed, then unsorted cards are kept separate and used as the first cards in the next reference group. In the case of a very large section, the sections were divided into two for each ranking and each half treated separately.
At the end of each session all cards were carefully mixed so as to ensure that each reference group received a mixture of cards.
Achieving Consistency within the Village
There is a danger that dividing up the village may make the results between sections not comparable. Consistency between the sections is achieved by comparing information given during the ranking, and taking notes of the information given is essential. Descriptions of the characteristics of people in each ranking pile is the basis by which comparisons can be made between sections of the village and between village.
In Bhungeni by comparing the information given in each section, it was apparent that there were no significant differences in the criteria used to rank the different sections and thus the results were comparable.
Using WR Results to Find a Cut off Point for Selecting the Poor
Information defining the different wealth levels is also useful for deciding the cut off point for inclusion into the program. Rather than choosing an arbitrary point, decisions can be made based on knowledge about poverty and the average ranking score for people at different levels of poverty.
Tshomisano has used information given from a number of different rankings to define common characteristics of the very poor?our target group. During each ranking much information is given about why people are sorted into each group and therefore, the common characteristics for each pile. By using the generalized list it is possible to select those piles which correspond to the target population, and the cut off point is drawn at this level, rather than at a arbitrary point. During the ranking exercise, notes are made for any household where the reference group has a long discussion or has problem placing the card. These are usually the households where there is inconsistency between rankings. The notes provide information which allows for these households to be correctly placed.
Effective identification of the target group is the first step in reaching the poorest. The transparency of the PWR process strengthens the commitment of staff as they can see that they are working with the poorest. The process also builds community support, and reduces the chances of dissatisfaction in the community over the selection process.
The next step is to work with the poor in a way, which ensures the success of the poorest. Too often the poorest are the most likely to fail and drop-out from the programme. The challenges and SEF�s experiences of this are discussed in my next article.
*Development Adviser, The Small Enterprise Foundation, South Africa.