Sharing some of the lessons learnt on effectively collecting and using data as part of the Arab Women Enterprise Fund.
Are you serious about addressing gender inequalities within your MSD interventions? Are you struggling to plan what data to collect and how to make sense of it? In this post we will briefly explore using data:
- for programme design
- to stimulate crowding-in
- to learn and pivot strategies
- to understand systemic change
Using data during programme design
During the design stage of AWEF we relied on a number of data points that allowed us to select target sectors based on their relevance, growth potential and feasibility. For example in Egypt we selected the ready-made garments (RMG) sector for a number of reasons.
It’s a strategic sector for the national economy, contributing 2.25 per cent of the GDP, with substantial opportunities for further growth. Female workforce participation in the country stands at only 23 per cent (World Bank 2019), with RMG being one of the sectors in the economy that employs a relatively high proportion of women. In Jordan informal employment represents 44 per cent of total employment, with the majority of informal workers concentrated in agriculture and food processing, such as dairy manufacturing. AWEF’s research also showed that up to 90 per cent of locally manufactured dairy products are processed by women informally at home.
We therefore decided to focus on informal, home-based micro-entrepreneurs in the dairy sector, which was prioritised as a whole market segment. We also used the design stage to identify binding constraints to women’s economic empowerment from both the target beneficiary and market actor perspective.
In the Egyptian RMG sector, women’s workforce participation stood only at 45 per cent as compared to the global benchmark of 80 per cent. This was one of the main contributors to the low productivity of the sector, as Egyptian firms were struggling to hire and retain female talent, which is particularly well suited to this type of work. We conducted interviews with RMG factory workers and management realised that women left factories because of poor treatment by supervisors. There was, therefore, a clear rationale for selecting this sector both in terms of the potential impact we could have on women (improving their access to RMG jobs and wellbeing for women already working in the sector) and the business constraint we would help address. In response to this we piloted two sets of interventions in partnership with Arafa, one of the largest RMG exporters and employers in Egypt:
- to focus on creating new formal gender-sensitive recruitment channels for blue-collar workers and link RMG firms with recruitment firms providing these services
- to link RMG firms to trained providers of supervisory skills training to improve supervisors’ treatment of workers
Using data to stimulate crowding-in
Data is also equally important for replication. We have sought to document the commercial results of some of our interventions and use business case data to encourage replication within the market.
In the case of our interventions in the RMG sector, they generated annual savings of USD 120,000 as a result of improvements in turnover rate, reduced absenteeism, time spent managing disputes on the factory floor, and improved performance in business audits performed by buyers. One of the more interesting and unexpected results was that Arafa’s reputation as a good employer significantly increased referral-based recruitment, as more women were likely to recommend the job to other women in their community.
We have used the business case data at sector dissemination events to encourage scaling and replication by other firms by showcasing the very clear commercial benefits of factories adopting these gender-sensitive business practice. You can read more about our approach to business case development, and the experience of 17 other organisations, in our 2019 Practitioner Learning Brief.
Using data to learn and pivot strategies
In implementation we consistently use light touch monitoring to capture data that enables us to test and verify our initial assumptions and intervention logic.
As part of our interventions in the Jordanian dairy sector we worked with municipalities to introduce a new licensing process for home-based businesses. Two months after the launch, AWEF noted that the uptake of the licensing was particularly low. Focus Group Discussions (FGDs) revealed that women were fearful of formalising their business and having to pay taxes and were worried about losing access to their social benefits (generally only distributed to unemployed individuals). Given the lack of women who had successfully licensed their business, women also did not understand the value of the licensing process. In response to these challenges AWEF introduced a number of measures:
- a collaboration with the tax department to raise awareness of the tax exemptions for micro-entrepreneurs
- partnership with five municipalities to cost-share 80 role-model women to sign up for the licensing process and disseminate lessons learnt and success stories
- engagement with the Ministry of Social Development to allow women who apply for a home-based license to still keep the social benefit for up to two years
Using data to understand systemic change
Finally we use data to monitor how our interventions are leading to systemic change. AT AWEF we conceptualise systemic as those intervention that lead to:
- the uptake of new practices at the market actor-level
- impact on our target population
- changes in informal rules.
We particularly see informal rule change as core to the sustainability of our work and most of our interventions aim to influence informal rules as part of their theory of change. For example, when implementing the licensing intervention in Jordan, we observed a shift in expectations from the target population (both female micro-entrepreneurs and private sector) that municipalities should provide gender-friendly services such as business licensing and market linkages. This bottom-up change is important as it ensures that the change in practices at the market actor level is sustained and meets the needs of AWEF’s target population.
Julia Hakspiel, Adriano Scarampi and Professor Stephanie Barrientos (WOW) took part in a BEAM webinar in January 2020 - Women in the workplace: how better data can lead to systemic change
The Arab Women’s Enterprise Fund (AWEF) is a 5-year DFID-funded market systems development project aiming to increase economic opportunities for 150,000 poor women in Egypt, Jordan, and up until March 2018 the Occupied Palestinian Territories (OPTs).