How cooperative structures can support women’s empowerment

Growing inequalities and persistent social problems are forcing societies around the world to rethink dominant forms of economic organization. Perhaps the most promising solution is a proven solution: cooperatives. Cooperatives are rooted in a set of globally agreed principles: open and voluntary membership; democratic control of members; economic participation of members; autonomy and independence; education, training and information; cooperation between cooperatives; and, above all, concern for the community.

Cooperatives are not a new structure. Cooperative movements accelerated in response to the Industrial Revolution, providing workers with a mechanism to organize economic activity and build collective resilience. The “one member, one vote” cooperative structure ensured that all members had equal weight in decision-making and that benefits were distributed fairly. Cooperatives now play an important role throughout the world in sectors such as agriculture, insurance and housing. They have also played an important role in empowering women, particularly in the Global South, where women’s cooperatives have been key catalysts for income growth among the poor.

As the world enters the “fourth industrial revolution” – the integration of physical, biological and digital systems – the role of cooperatives in helping communities organize data resources becomes more evident. The idea of ​​the “data cooperative” is slowly taking shape globally as a mechanism to rebalance power in the data economy and (re)create collective mechanisms for negotiating with technology companies and navigating the data rights issues. Clearly, data is a relational good: while our digital experiences can be individualized, the value of data derives from the aggregation and insights into the relationships between individuals – and night of data use also occur at the collective or group level. In this context, the cooperative model offers a powerful institutional structure to responsibly manage the data of its members, safeguarding their interests while generating collective value. The previously mentioned cooperative principles highlight collective decision-making, redistribution of value, digital literacy, and prioritization of community interests, all of which are key considerations for effective data governance.

Examples of successful data cooperatives already exist. MiData and Salus Coop allow their members to pool and share health data. Swash aggregates the browsing data of its members. Driver’s Seat is a driver-owned cooperative that aggregates work-related data from on-demand economy workers’ smartphones. Resonate is a data cooperative collectively owned by musicians, labels and fans. These cooperatives also take on fiduciary responsibility: a legal obligation to manage data, provide information and negotiate with service providers in the interests of members (which makes institutions with already existing fiduciary responsibilities – cooperatives of creditfor example-ideal starting points for developing data cooperatives).

Where does the cooperative data movement have the greatest potential for rapid development? We mentioned earlier that women’s cooperatives – and other informally organized women’s collaborations such as self-help groups – play a vital role in promoting gender equality. These cooperatives usually pool labor (as in worker cooperatives), capital (as in micro-credit groups), or both. Data is another valuable asset that can be pooled for the collective good. Individual members of cooperatives already passively or actively generate data, although in many cases the value of this data is only captured by other entities, technology platforms, for example. Data cooperation would divert some of this value to individuals while proactively preventing harm.

Women’s cooperatives are a promising target for the cooperative data movement for three main reasons. First, the “trust infrastructure” is already built. Co-operatives can be complex to manage, not least because collective decision-making requires strong relationships. While women’s cooperatives vary in their quality of governance, the shared experience of building and sustaining a new organization in the face of unequal gender social norms is an encouraging basis for taking the innovative initiative to build a data cooperative. Platforms for governance, decision-making and collective action are already established, and existing cooperatives may consider data rights as a cross-cutting concern in different aspects of their ongoing work. Offline trust mechanisms can be brought online.

Second, data sharing can help overcome gendered socio-economic barriers. For example, access to credit is particularly difficult for women farmers, in part because the lack of data on women’s smallholdings complicates credit scoring by financial service providers (FSPs). A women farmer cooperative we work with in Gujarat, India, aggregates their income and credit history data to present a more complete picture of creditworthiness to FSPs. This more robust digital economic identity can also facilitate access to loans for non-agricultural expenses such as education. Around the world, women are often invisible to market and state actors, in part because of incomplete data systems. Data cooperatives can remedy this situation.

Third, the pooling of data puts women in a stronger position to negotiate for their interests. This facilitates, for example, privacy protection through data aggregation. More broadly, by providing a way to shift power from data controllers and users to individual women and girls, the cooperative data model upholds the tenets of data feminism. In addition, women can exercise greater control over the flow of data to the public sector, supporting policies aimed at enhancing gender equity.

The potential of data cooperatives is immense. They offer a data stewardship model that enables the marginalized to protect themselves from harm while reclaiming the value of their digital lives. However, building data cooperatives is complex and requires significant investments to increase digital literacy, build data architecture, and develop efficient and flexible consent mechanisms. We believe that instead of creating data cooperatives from scratch, it is more prudent to allow existing women’s cooperatives to add a layer of data to their current operation, so that cooperative members sharing lived experiences can pool their data assets to extract more value and avoid harm. Such a strategy would reinforce existing empowerment vehicles. The data revolution is here. The challenge for the global community is to deploy the tools of this revolution within vehicles already known to be powerful instruments of change.

Virginia S. Braud