Editor's Choice

The Editor’s Choice blog is a monthly review of a top resource or report in inclusive business.  There are so many resources, documents, tools, reports, videos out there, it can be hard to know where to start.  We choose one that we like and tell you why we like it and who else should find it useful.   Until the end of 2017, Editor’s Choice blogs were written by Caroline Ashley as Hub Editor.   Going forward, they are written by a range of guest editors, both from the core team and from beyond.

July 2014 Editor's Choice: What can we learn from 5,000 organisations about the beneficiaries they reach?

Agricultural and artisanal sector businesses typically source from around 400-500 suppliers, but the fastest growth in the supply base happens after 15-19 years of operation. For businesses selling to consumers, those in South Asia are reaching hundreds times as many clients as those elsewhere. Growth rates of suppliers and clients are typically low - except in the Financial Sector where client growth is well into double digits.

These are just three of the interesting trends that emerges from a review of data supplied by almost 5,000 organisations, and reported in the IRIS Data Brief, Focus on Beneficiaries.

There are almost no rules of thumb or standards in this innovative field of inclusive business. Almost by definition, the field is one of diversity and innovation so there is no ‘normal’. At least, not yet. Nevertheless, trends are beginning to emerge. We all like to know what others businesses are doing, how they are doing in reaching the BoP, what counts as ‘good’ ‘average’ or ‘poor’.

The IRIS Data Brief helps us to move from knowing absolutely nothing about what is normal engagement with beneficiaries, to knowing something, albeit with caveats. (The main caveat is the sample is based on organisational decisions to use and share IRIS metrics and the only data aggregated is in the form of IRIS metrics).

Around 60% of the organisations whose reporting metrics have been aggregated for this report are in the Financial Services sector. So the aggregate figures are obviously not representative of the rest of the inclusive business field. But even so, data from around 2,000 other businesses covers agriculture and artisanal organisations (which source from suppliers), plus energy, health, ICT, environment and several other sectors.

So what did I learn? Looking only at the non-Financial Sector organisations, aggregates and averages indicate that:

  • The median number of clients is 189. However, this hides huge regional variation because in South Asia the median is above 8,000.[i]
  • The median number of suppliers per organisation is 465, though slightly higher in agriculture and lower in artisanal sector. It is higher in Sub-Saharan Africa (800) and lower (350) in Latin America.
  • The median number of employees is 14.
  • Median numbers are consistently and significantly below averages, due to a few outliers with large numbers. Only non-zero entries have been used.

Given the heated debates I have had in recent months about targets and expectations of inclusive business, those results are useful. The supplier numbers sound realistic, but the client numbers suggest that South Asia is further ahead, and the rest of the world even further behind than we may have realised, in realising the promise of reaching the mass BoP market. The low ratio of employees to other beneficiaries confirms what we see elsewhere (and reinforces that donor metrics need to measure not ‘jobs’ but beneficiaries).

In terms of business growth and progress, the trends are positive but modest :

  • The median growth rate of clients is 2% per annum, and the average is 20%.
  • The median growth rate of suppliers is zero per cent, and the average is 13%, with the fastest growth experienced by organisations that are 15-19 years old.
  • The businesses have been in business for an average of 11 years, median revenue p.a. is US$860,000 and 57% are profitable.
  • If grants are ignored, the share that are profitable goes down by 3% points.

We sometimes look to the micro-finance sector as the sector that is a decade or two ahead of the rest of us in inclusive business or impact investment. So it is interesting to note that the Financial Services sector (which the authors point out is bigger than just micro-finance) seems to be clearly out-performing the other sectors. Median client growth is 23% per annum. 86% of organisations are experiencing positive year on year organisational growth compared to 56% in other sectors. In this sector, it’s the youngest organisations that are growing their client base fastest.

The brief also reveals much about the objectives that businesses set and report. Only around a tenth of the full respondent set (including the Financial Services sector) report on their objectives or targeted beneficiaries in the form of an IRIS metric.

  • Around a tenth define their beneficiary demographic. Amongst these, the most common target is ‘minority/previously excluded populations. A quarter of them say they target women.
  • There are vast differences in the propensity to target women. Amongst those that report beneficiary demographics, 70-80% of organisations based in Asia include women as a target group, but the numbers are vastly lower in other regions. In the energy and financial services sector, around 60% target women, next come health and artisanal sectors, while in the agricultural sector, only 5% report targeting women.

Of the 420 organisation that report the socio-economic profile of their target beneficiaries, most report targeting the ‘very poor’ living on a dollar a day, plus the poor, plus low-income. This rather confirms what we are seeing elsewhere: few businesses would actually know (or have reason to know) which specific poor segment they reach or would limit themselves to one segment.

  • Those targeting agricultural suppliers and artisans are more likely to say they target ‘very poor’ beneficiaries, compared to those that target consumer beneficiaries. Organisations in the energy sector are least likely to be targeting poor/low-income beneficiaries.

Agricultural and ICT sectors target overwhelmingly rural populations, as do the majority of energy companies. Other sectors target an urban rural mix.

I have been in innumerable discussions over the last six months (due to that inglorious habit of setting targets) debating how many beneficiaries we can expect a business to reach, and who they are. My view is that it depends on the type of business, its market and most of all on its maturity plus whether numbers are multiplied by household size. As we argued in ‘The 4Ps of inclusive business’ most businesses reach only a few hundred beneficiaries for some years, until they finally scale. So we will never have robust benchmarks for the inclusive business sector. But given the immense dearth of shared information, this IRIS data brief is an invaluable glimpse into a data set of thousands of organisations.

 

It’s a slightly frustrating glimpse, as data for the non-financial services sector is partially presented and it is hard to know the N of respondents when drawing out findings on different topics. Data points which have few respondents are not shown to protect confidentiality. But as more organisations contribute data through the IRIS data initiative, and as the IRIS team develop new ways to cut a larger sample by sector and maturity, our field of vision will expand. So long as we don’t take the results as hard benchmarks, but as indicators of where trends or surprises lie, we can draw value from this and future Data Briefs.

 

Further Information

Editor’s Choice is published monthly. Previous Editor’s Choice selections dating back to December 2010, are listed here.

The IRIS data briefs are published by the Global Impact Investing Network. The brief on beneficiaries was published in March 2014. Contributors were Amit Bouri, Ellen Carey, Melody Meyer, Kimberly Moynihan, Abhilash Mudaliar and Arjun Reddy. The first brief, in 2013, was on employment. See GIIN Publications

 


 

[i] There is no data shown for Sub-Saharan Africa indicating there are less than 10 data points –which in itself is interesting.