geekfest-d47647.jpg Welcome to GeekFest 2017, a series of interviews featuring ICT4D thought leaders. Our goals for our #geekfest2017 interviews are 1. to highlight the people and organizations who are pushing the field in new directions, 2. feature their work and show how it’s different or new, and 3. to support the overall growth of the ICT4D community.

AlexTyers_Headshot_May2017.jpg This week I chat with Alexandra “Alex” Tyers, Co-Founder and Director at Panoply Digital. Alex is a mobiles for development (M4D) professional, specializing in monitoring and evaluation for innovation, mobile learning in emerging markets, and women’s mobile and ICT access and use. Alex recently spoke at our Frontiers in Digital Inclusion Event in London on the importance of gender-disaggregated data for digital access and inclusion.

1. Why does gender-disaggregated data matter?

Well, we all know that there is global gender inequality, and that inequalities in the physical world are being replicated in the digital world. Globally, a woman is 14 percent less likely to own a mobile phone than a man, but this is much higher in certain regions: 38 percent in South Asia, 45 percent in a country such as Niger. We also see similar trends in access to the internet. A woman is 50 percent less likely to be online than a man in the same education and income group. There is also a growing gender gap in usage. Even if a woman does have access to a mobile phone or the internet, she tends to use them differently than men—less frequently, more use of basic services such as voice, and less use of complex services such as mobile internet or mobile money.

With the international development sector’s increasing use of mobile and ICT as a vehicle to deliver services, we run the risk of exacerbating this global inequality, particularly if we use mobile services without understanding and addressing the digital gender divide.

The first step towards closing this gender digital divide is understanding it. To do this, I would argue that we need more gender-disaggregated geographic data to help us get a better understanding of (and evidence of) women’s access to and use of ICT. This data can identify barriers to access and use of technology and inform development programming.

2. How can gender-disaggregated data help us design better programs?

This gender data gap is an issue, and it does affect program design if people don’t understand how women use and experience ICT from the beginning and at a community level.

Say, for example, we have an education program in Chad and we want to include a mobile money component to either encourage people to save money for school fees or to reduce corruption and theft by removing physical currency from the transaction. In this case, it would be important to know how many women in the community have access to a mobile phone, and which types they use. Do we know how many women have a mobile money account, or what they use their mobile money account for? Do we know whether women make transactions by themselves, or with the help of an agent? What cultural practices in their community might affect their access to mobile or their use?

We may know a little bit about the women in general, but if we don’t know about their mobile access and use, we run the risk of designing a digital component of a program that doesn’t meet the needs of female users as well as men. Having this gender-disaggregated data and insights at a community or subnational level can help us anticipate barriers women face, and work towards overcoming them to ensure they are included in any digital component.

3. Is there a lot of gender-disaggregated data out there?

Unfortunately, no. There is a general lack of reliable gender-disaggregated data, a lack of standardised data, and the data sets that do exist are often fragmented. Although this is slowly changing, thanks to excellent reports and data from people such as the Web Foundation and GSMA Connected Women. However, this can be time consuming and expensive to collect, and a lot of the larger studies on this topic are already outdated. In addition, the limited gender-disaggregated national statistics that exist are not indicative of every community. We really do need to know how people, especially women, interact with technology at a community level.

4. How can we go about getting this data then?

I’m glad you asked! In an effort to address this gap USAID Digital Inclusion recently commissioned the Gender and ICT Survey Toolkit, which I co-authored alongside Katie Highet and Hannah Skelly from FHI360.

The Toolkit facilitates the collection of gender-disaggregated information with a series of resources, including survey questions, focus group discussion guides, and technical competence tests, as well as instruction on research design and data sorting. It’s designed to be user-friendly, practical, and to be used by everyone—not just academics and monitoring and evaluation experts.

Through this resource, we’re hoping to enable a more data-driven (and gender disaggregated data-driven) approach to ICT4D implementation, and in doing so, help to close the digital gender divide.

To find out more about the work that Alex and Panoply Digital do, check out: their website and Twitter @Panoply_Digital and @alex_tyers