New guidance for measuring gendered impact in private sector development.

Long gone are the days when 'gender' sat at the periphery of private sector development. Now, women’s economic empowerment (WEE) principles and outcomes are front and centre of economic growth programming – from market systems facilitation, to value chains, to business environment reform. And so much the better. 

What’s driving this is a recognition of the disproportionate poverty burden borne by women and the potential multiplier effect of economically empowering them. By reinvesting their income in families and communities, economically empowered women are known to catalyse much broader development outcomes. Clearly, gender equality is also smart economics. 

Of course, for programmes to prove and improve their impact for poor women – monitoring and results management (MRM) systems must be able to capture the different experiences derived by men and women from interventions – the 'gendered impact'. But while guidance on measuring WEE outcomes in market systems is growing, a number of measurement challenges remain. Most pressing, is the lack of guidance on who to count as a beneficiary when measuring changes to income. Crucially, the different ways that this can be approached tell very different stories as to a programme’s gendered impact. 

There are a few reasons why knowing who to count is tricky. 

Identifying who contributes to income increase…

Firstly, households and enterprises often merge within poor communities in developing countries. This is the case with smallholdings, which are both an enterprise generating revenue, and a household consuming the revenue as income. This makes it tough to attribute income increases to one individual, as many people (often of different sexes) might contribute to the income-generating activity. How they contribute is likely to vary – some roles may be considered more ‘meaningful’ than others, further complicating the decision as to who we count, with implications for our understanding of a programme’s gendered impact. 

For example, in the vegetable sector in certain regions of DRC, women carry out much of the planting, nurturing and harvesting with the support of their children, but typically it is their husbands who own the land, manage the transport to market, and deal with the sales. Should we count both the male and female as beneficiaries? What about their children? Does it depend how ‘meaningful’ we judge their contribution to the income-generating activity (and besides, how do we define what is 'meaningful')? Or would it depend on how much time they’ve dedicated to the task? 

…and who benefits from income increase

Secondly, it is difficult to identify beneficiaries of increased income and their sex because those generating the income may not be those who ultimately benefit from it. The distribution of benefits within and outside the household (towards external labourers) might take the form of money or payment in kind, for example the revenue may go into a household budget, which is spent on a range of things, some or all of which benefit the contributing individuals, such as improved nutrition, or access to healthcare and education. 

Individuals may benefit in different ways: some might experience improved access, others increased incomes, and some may notice changes to their decision-making influence or status in the household or community. Sometimes, those contributing to the income-generation receive no benefit or can even be harmed. 

So even where income is clearly earned by a sole individual, in many contexts it would be fed back into a household budget, where other family members serve to benefit. This is a third reason why it is difficult to define and identify beneficiaries of increased income: programmes rarely have a commonly held understanding of whether they are measuring income generation, income receipt, or control over income. 

Approaches to counting 

These complex dynamics and the lack of a widely-held understanding of whether a programme is measuring income generation, income receipt, or control over income makes it difficult to know who to count as a beneficiary, and there is no agreed approach to this challenge among market systems practitioners. 

Some programmes count the head of the household, some count the head of enterprise, and some count all individuals within the family or enterprise. Other programmes count only those who have a ‘meaningful’ influence over income, or seek to understand the distribution of impact based on the different relative inputs of men and women (measured through time or activities) or through their different relative benefit, then using ratios to extrapolate out beneficiary numbers. 

Each of these is likely to give a different idea of programme impact, particularly from a gendered perspective: If we count the head of the household or the enterprise, we’d count only one beneficiary which, owing to entrenched gender norms, almost always favours reporting men and often hides women’s contribution and/or benefits. On the other hand, if we were to count all individuals in the household or enterprise we attribute the same benefits to everyone, irrespective or their contribution or the realities of how an intervention is benefiting them (or not). 

ASI’s new guidance

Responding to this challenge, Adam Smith International (ASI) has developed a Guidance Note that provides recommendations on the process programmes can follow to determine the best counting approach for their particular context; understand the implications of this choice; and pursue additional research to develop a richer understanding of how a programme is impacting poor women. This is broken down into five steps:

  • Step 1: Determine the most appropriate approach for each focal sector (our Guidance Note includes a useful table of different options) and communicate the selected approach(es) to the whole programme team, the donor, and partners
  • Step 2: Develop clear, contextually-driven definitions for key terms and concepts used in the approach(es), for example, how does your programme define ‘headship’? And is the programme measuring the generation, receipt, or control or income?
  • Step 3: Recognise the gendered implications of the chosen approach(es) (listed out in our Guidance Note)
  • Step 4: Adapt existing standard measurement tools (e.g. surveys, FGD methodologies) to incorporate mechanisms designed to collect data that will help unpack intra-unit dynamics as they relate to income increase. Here, we suggest that programmes counting headship incorporate Decision Tables, which can be used to develop a more accurate understanding of who is likely to capture the benefits of a given intervention, and which allows for joint-headed households and enterprises
  • Step 5: Design and deliver qualitative analysis to supplement and add greater nuance to sex-disaggregated beneficiary data

Not only is this new guidance helping ASI to better understand our impact on women during implementation, but it will also be vital for better targeting women in the design of interventions. During sector selection or market systems analysis we try to understand the gender make-up of a typical enterprise, but by assigning men as the head of the enterprise in cases where both men and women are both meaningfully engaged in the income-generating activity and/or decision making, we can miss opportunities to reach poor women. 

But by using measurement tools that more accurately capture intra-unit dynamics, such as the Decision Tables and Jointness Scale proposed in our Guidance Note, programmes can move away from an over-reliance on using 'female-headed households' as a mechanism for quickly and easily targeting female beneficiaries. Instead the tools help to focus on the much higher number of poor women ‘hidden’ in what was conventionally understood to be male headed, mixed-sex households.

ASI’s Measuring Gendered Impact in Private Sector Development are available here: 

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