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Takeaways from the “Data Hub Visioning Workshop”

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Arifu, will be part of the implementing cohort attempting to digitally reach farmers with training content on drought-resistant Irish potatoes and poultry across several Kenyan counties. As part of the launch of the project, The Data Hub Visioning Workshop was organized by KALRO, MercyCorps, the World Bank, and Dalberg.

Attending day long (or multi-day) long conferences and workshops can create a feeling of cautious uncertainty. The promise for such events is often about facilitating thoughtful collaboration and meaningful networking, identifying new knowledge, capabilities, or talent which otherwise may be missed, and, in effect, learn from and get inspired by like-yet-differently-minded individuals from really cool organizations. Rarely in my experience do conferences succeed at fulfilling these promises.

At this workshop however, this experience manifested in spades.

The workshop was engaging, interactive, and highly collaborative in nature. We had the opportunity to meet with and openly debate and discuss ideas with agronomists, digital advisory firms, public data product developers, as well as innovative policy-makers (such as Director Boniface Akuku of KALRO). This helped considerably elucidate the variety of thinking, shared goals, and possible pathways to achieve those goals in a highly productive manner.

The goal of the workshop was to bring in stakeholders under the One Million Farmer project to identify (in my own words):

Vision and possibilities:

  1. What data exists publicly and within institutions?
  2. What data needs exist across institutions?
  3. What data are institutions willing to share and in what format?
  4. How can data-based collaborations drive improvements in operations and, hopefully in effect, improvements in the lives of farmers?

Challenges and the creation of a roadmap

  1. What concerns institutions have in sharing that data?
  2. What are the risks associated with sharing that data to farmers and institutions?
  3. How can those concerns be alleviated?
  4. How can personally identifiable data on farmers be protected?
  5. What is the efficient path forward?

The workshop spoke heavily to what data needs exist, where that data exists, and how to share the data. Several efficiencies in product design and development, as well as hesitations from individual organizations in data-sharing, could be tackled if creative solutions come out of the findings from the workshop. This would only help the ecosystem of players to reach and effectively strengthen farmer capabilities.

Even with that possible success, there was one important question that felt unanswered, which perhaps will shine more in the coming weeks. Why will access to this type of data make the organization more effective for improving farmer lives?

Understanding the why

At Arifu, we’re big fans of data and problem-driven approaches to the design of solutions which can be scaled through the leveraging of market forces. Having access to more types of data is essential to drive the ability of organizations to understand and solve problems. But not all data is of equal relevance or quality, not all solutions are highly effective, and there’s a detailed history of efforts worth taking stock of to ground data demands organizations have. As such, it is worth thinking through how useful a specific data request really would be for organizations and in turn, for farmers. This ask can be stress-tested in at least the following ways:

Continuously listening to farmers: rapidly changing agricultural context due to climate change begs us to be more agile in our design and testing of solutions along planting cycles for crops. In addition, it forces us to think about solutions that can adapt to the annual weather volatility stemming from climate change. Farmer voices across crops and rapid just-in-time data must complement the history of research in the design of solutions.

Taking stock of existing research: findings from reams of academic and non-academic research would add immense value to stakeholders if consumed and understood correctly. There is often much more to these papers than p-values, abstracts, and effect sizes. Papers often highlight intermediary insights through a program’s theory of change (for example, not just yield changes, but behavior changes), the drivers and inhibitors of these measures (for example, what types of knowledge changes were associated with metrics of interest), and what might be ways to improve intended outcomes cost-efficiently at scale. 1

More data is not necessarily better: the two efforts above could inform an organization’s theory of chance and what data, with what quality, at what specificity, and at what frequency is necessary to drive results for farmers. In other words, it is easier to come up with machine learning-driven algorithms by hacking at swathes of data, but it is difficult to create relevant and riskless solutions for the farming household.

Don’t get us wrong, we love data

Arifu believes that access to relevant information is a fundamental freedom for all people and it is a promise that has yet to be fulfilled by the advent of the World Wide Web. Even so, it is technology and lower barriers to information that will drive improvements in decision-making capabilities for households. Data, in many forms, is essential to cater and design solutions that fit the needs of farmers and our partners.

Examples of how we’re pursuing the aforementioned methods include our upcoming Google.org project will involve a battery of diagnostics, A/B Tests, and randomized controlled trials to assess the impact of Arifu 2. This will be done in partnership with several community-based organizations and researchers from the World Bank and Harvard Business School.

In addition, we have been exploring the use of remote sensing technologies to measure crop yield for individual farms. This is more difficult a process than it sounds, but through our conversations with economists and astrophysicists across top universities in the US, NASA, and AtlasAI, we have learned about where the upcoming possibilities and innovations are in the coming year or two.

We’re excited to see how we can further drive quality of life improvements for farmers directly and by amplifying the impact of our public and private sector partners. We believe this can be done effectively through partnerships like those available in the One Million Farmer project, by leveraging existing research, actively listening to farmers to inform our design, and using the right data.

  1. Examples of a great summary of experiments are here and an interesting set of results on weather advice to farmers – and more – are here.
  2. More on this soon!