How to measure microfinance impact on poverty alleviation: what does available evidence tell us? Some Lessons Emerging from Buusaa Gonofaa’s System of Tracking Improvements in Clients’ Livelihood By Teshome Dayesso, General Manager

Buusaa Gonofaa MFI - Introduction Started by a local NGO, HUNDEE, later transformed into NBFI in 1999, regulated by the central bank of Ethiopia Provides micro credit and savings services through joint liability groups of members; Short term general-purpose loans (8 – 12 months) for income generating activities, microenterprises, farm inputs, productive assets (ox, cow), housing improvements, consumption smoothening Community managed saving and credit facilities in hard- to-reach remote rural areas Current outreach >50,000 active clients; total assets of >US $6 million; outstanding portfolio of US$5 million

Buusaa Gonofaa MFI: Our Intentions Mission:- To provide flexible & efficient microfinance service on a sustainable basis to improve the livelihood of the resource poor, particularly women, landless youth & smallholder farmers Progress overtime Outreach to target group – the poor Improved livelihood Flexible & efficient Financial performance Sustainable/profitable Client satisfaction Client profile, poverty level

Why BG Wanted Client Assessment Scorecard (or ‘Social Ledger’) Double-bottom line: standardized measurement of financial sustainability; but tracking social goals relied on simple success stories, and intuitive decision making; but this was not enough and we wanted data ‘evidence’ to describe it. With financial maturity, we wanted a more systematic way to understanding what is happening out there,  Whom do we reach? How poor are they?  Is there a change (+ve, -ve) in our clients’ livelihood?  Where do we succeed in changing client’s livelihood? Where do we fail? Why?  Who benefits from BG most? Does our loan assist either survivalists or entrepreneurial poor? Or both?

Poverty as ‘lack’ and how the poor measure their progress (or improvements) in overcoming it What the poor ‘lack’ in comparison to the not-so-poor Food security Clothing Shelter Income Education Health Housing ownership Access to electricity, water Land Capital/savings What the poor consider as progress or improvement 25% - Expanding the business (ox/cow fattening, more inputs for farming) 16% - Improvements to the house or house construction 14% - Buying ox, cow, sheep 13% Acquire basic household furniture, utensils 13% Buying “luxuries” (radio- cassette, TV, jewellery, etc)

6 Measurable Indicators Weight Year/Round of Scoring Date of scoring as Month/Year: m1/yrm2/yrm3/yrm4/yrm5/yr o Roofing material:- T=thatch; I=iron; P=plastic, O=other TTTII O Number of rooms/huts o Housing/improvement o # Oxen o # Cows o # Sheep/goats (shoats) o # Bed type – Metal o # Bed type - Wood/Mosvold o # Tape recorder o # TV Total Score of HH Assets: % Change in Asset score 21%44%14%-12% BG’s Poverty Indicators & Score Weight

Poverty category & cut-off points A person with total score of 5 is poorer than a person with score of 15, and vice versa Collection of data (scoring) from clients by LO as part of routine loan application on every cycle – baseline at Intake, wealth Scoring on each loan cycle Approximate Income range Score rangePoverty category ≤ $1/day 0 – 16Very poor $1 – $2/day17 – 60Poor ≥ $2/day > 60 Not so poor 7

Improvements in the poverty status of clients between the 1 st and 3 rd Scoring (N=2,113)

Mean Score Growth by Components 9 Very PoorPoorNot so poor Asset score-1 st scoring Asset score-3 rd scoring Biz score-1 st scoring Biz score-3 rd scoring Total wealth-1 st scoring Total wealth-3 rd scoring Asset score growth (%)1,005%8%-14% Biz score growth (%)24%15%35% Wealth score growth (%)71%12%4%

What contributed towards assets score growth? Asset Score Growth Pearson CorrelationSig. (2-tailed) Ox score growth.683 (**).000 Cow score growth.638 (**).000 Shoat score growth.153 (**).001 Bed score growth.107 (**).000 Tape score growth.093 (**).003 TV score growth.439 (**).000 Asset score growth1 ** Correlation is significant at the 0.01 level (2-tailed)

Some Emerging Lessons and conclusion It is very important to know what matters most for our target groups – identification of indicators from the bottom up, thus relevant ‘evidence’ The system provided us with good insight about what is happening ‘out there’ – more informed decision to better serve the very poor and poor; ‘evidence’ to refine our services and refocus on improvement areas that matter most for the target group It would not tell us what loan size or mix of financial services are most likely to keep the poor healthy or enable them send their children to school; but it may help us in understanding how the poor might progress overtime towards those ideals of dignified living. Our intention is to improve livelihoods; the target groups have diverse priorities and hence there is no single goal that can be measured with a single indicators. But the system complements our judgments and decisions and helps us to be mindful of our promises.