This is the last piece in our blog series that details our experience of establishing ‘Data Co-ops in Action’ and our learnings from the process. This piece is a reflection of our work with Enyorata Loviluku, one of the two groups of our first cohort.

Enyorata Loviluku is a women’s group based out of Kisongo, Tanzania. Daniel Elibariki Alphayo, who helped start the group, envisioned it as a self-help group for empowering women belonging to the Maasai community. The ultimate goal is to address gender inequalities by helping women take control of their finances.

The group started as a table banking group in 2019, where Daniel and his team would educate the women about money and managing finances. Initially, the men in the community were not in support of the group. However, over time, the women have been able to create a space which is exclusively theirs. They now pool their finances to help each other when in need of loans for their businesses. An organisational structure, regular meetings and record-keeping have made the functioning of the group more formal.

Having helped the members meet the basic needs of their businesses, the group now intends to expand their finances through bank loans. Daniel believes that establishing the group as a data cooperative would be the key to securing loans from banks for developing the members’ businesses.

Aapti has been working with the group through Daniel to put in place a structure for the data cooperative. The following are the key elements of this project:

• The technology of the data layer
• The governance principles of the data layer
• The legal measures to formalise the data cooperative
• Relations with external stakeholders

The chart below illustrates their model for implementing the data layer.

Over the past few months, the group had initial conversations with banks and has completely digitised all member data on contributions to the group, loans taken, interest paid, penalties incurred and contributions towards community development. The mobile application, through which the data layer would be facilitated is currently being developed by Daniel’s team.

On February 1, 2024, we had an interaction with the members of the group to outline the following:

• The core function of the data cooperative, which was represented as a collection of the various data flows within the cooperative and outside the cooperative
• Data rights of the members under Tanzanian law as well as the commonly accepted data protection principles

The following were the key outcomes from the workshop:

1. Establishing the value of aggregated data: The members voted to send aggregated data to banks and apply for loans as a group. This was a departure from their proposition of applying for loans using personal data at an individual capacity. When highlighted that aggregating data would ensure that individual member details are protected and would enhance bargaining power with the bank (as opposed to when approached individually), the group indicated that they would prefer to aggregate member data and obtain credit as a group.
2. Promoting data rights: The activity on data rights helped the members deepen their understanding of the value of data and the measures they could take individually and collectively to protect it.
3. Formalising group functioning: While the group has been functioning
   systematically, it is yet to be formally registered as a legal entity. With Aapti’s presence on-site, the group was able to decide that it would be beneficial to register as an NGO as it would open up options for funding and would make it easier for other organisations to associate with the group.

Key learnings from engagement

1. The intermediary can take on a crucial role in the process of building a data cooperative: In our experience of working with Enyorata Loviluku Women’s Group, the intermediary has played an invaluable role in setting project context, building trust with the group and mediating the interaction. More importantly, however, Daniel established the base of the data layer by having data from 2019 digitised, recruiting a developer to work on the web app and having initial conversations with various banks.
   
   This highlights that the intermediary can fill gaps in member capacity in building the data layer and the initial stages of its implementation. This is complemented by strong leadership in the group, which ensures that member interest is well represented. Strong leadership also helps steer the group towards making decisions in a timely manner. Overall, this process reiterated the importance of an intermediary who is committed to the group’s interest, and how strong leadership within the group drives the process of building a data cooperative.
2. Trust is crucial while building a data cooperative: While this has been highlighted extensively in the literature on data cooperatives, Aapti’s experience in the field served to further solidify this notion. We understood that trust operates at four levels: trust between members inter se, trust between members and the intermediary (Daniel, in this case), trust between the members and Aapti and the members’ digital trust.
   
   In our experience, trust between the group and an organisation in a position similar to that of Aapti is strongly dependent on the relationship between the group and the intermediary. In this case, Daniel facilitated the trust-building process between Aapti and the women. We envision our role as promoters of digital trust. We intend to support them in navigating digital trust and provide them with the tools to do so. For this, however, we found that longer project periods and regular engagement are necessary. This is especially important when there is a language barrier at play.
3. Identifying incentives for all stakeholders retains an interest in the process: Establishing data cooperatives is often a slow and resource-intensive process. Building a data layer entails preliminary capacity building, collectively building the value proposition for the data cooperative, developing the technological base for the data layer, taking decisions on the governance of the data cooperative, building relationships with vendors and stakeholders, piloting the tech infrastructure, undertaking legal formalities and initiating the implementation of the layer.
   
   Considering that all these activities require the investment of time and effort from the members and the intermediary, they are more likely to stay committed to the project when incentives are in place. This has also been highlighted in our work with Megha Mandli, a women’s farmer cooperative in India.
4. Existing power dynamics are likely to dictate the actions of the data cooperative: It is pertinent to acknowledge that while data cooperatives are rooted in the idea that members exercise control over their data, power dynamics between the group and external institutions such as banks, tech companies and even governments may have a higher influence on how decisions are made regarding data. This is especially true with smaller groups where the bargaining power might not necessarily tilt in their favour.

The way forward

Enoyarata Loviluku Women’s Group will be formally registered as an NGO within this month. Simultaneously, work on the mobile application will continue. Most importantly, the group will continue conversations with banks and explore alternative funding ventures.

For Aapti, this work has reaffirmed our confidence in the data cooperative model. We intend to carry these learnings to our future work on community empowerment in the context of climate data. We also hope that the story of Enyorata Loviluku inspires women’s groups in other parts of the world to explore the data cooperative model as vehicles to achieve group goals.

**Insights from the engagement are a result of joint analysis by Vinay Narayan and Sushmitha Viswanathan