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Pioneering Progress Through People-First Data Solutions
It's possible to adopt a people-first approach to data analytics, through the involvement of a community in problem-solving.
4 Min Read
Bill Cheyrou via Alamy Stock
Picture this: It’s 2008, and Google has released Google Flu Trends, their public health tool aimed at predicting flu outbreaks through user search queries related to flu symptoms. The initial findings indicate a surge in flu cases, causing widespread concern. But then, in 2012, it comes to light that the information provided by Flu Trends was inaccurate and that for the last three years, flu cases had been consistently overestimated by more than 50%.
In retrospect, it was evident that the model's reliance on data without analyzing it through the lens of human motivations was a key factor in the flawed outcome. It was clear that understanding not only what people were searching for, but that their motives for doing so, was crucial. Nonetheless, this incident did prove that data alone, devoid of human input, remains mere data.
To address real-world challenges, people need to be involved.
Fast forward to today, and this issue has only gotten worse. Our ability to process and compute data (and use it to prevent unwanted outcomes) has undoubtedly become faster and better. But as the world continues to struggle with complex, wicked problems, instead of using data as part of a solution, data has emerged as the solution.
The Partnership for Inclusive Innovation was founded to prioritize meaningful progress over innovation for the sake of it. By building multi-sector coalitions, the partnership focuses on projects that improve the human condition, support upward mobility, and drive economic growth for communities large and small.
In alignment with this people-centric ethos and with the support of the partnership, The University of Georgia's Digital Literacy and Ag Tech Program launched an initiative to address the resource gap within the agricultural industry. The program began with a survey to assess the current technology use of small to medium-sized farmers in Georgia and their pain points.
Armed with this crucial data, the program developed customized training modules designed to familiarize farmers with technology tools tailored to their specific needs. The program attributes its success to its approach: It began with the farmers and developed the curriculum accordingly -- a paradigm shift that places people at the forefront of innovation, not the other way around.
Several other organizations are undertaking similar data-driven initiatives with the central goal of enriching people’s lives. For example, Current is a Chicago-based organization addressing water challenges exacerbated by climate change through its Upstream IL initiative. The program aims to reposition disadvantaged communities as key players in the water sector. Upstream IL focuses on understanding the barriers these communities face, directly engaging with them to gather insights. This people-first approach informs strategies that promote ownership, entrepreneurship, and employment within the blue economy. By starting with the needs of the community and aligning innovation with their realities, Upstream IL exemplifies how data can be used to foster both economic growth and social equity.
In essence, we’re seeing a welcome pivot where data is viewed as an enabler to enhance the well-being of individuals and not an end in and of itself. But how can we effectively transition toward this approach? Here are some key strategies:
Work together to define the problem. You can identify challenges and create solutions, but if they don’t address actual problems, people won’t care about what you developed because you’re not solving a pain point. Instead, work with diverse sectors in the community as partners from the outset to understand the problem and goals. Building such a coalition has additional benefits of shared risks, leveraged resources, and sustainability of the work.
Don’t make any assumptions. Take a page from UX design principles, the first being user-centricity — putting the end user’s needs first, and then making decisions based on what you know about them. The same goes for problem-solving. There is a range of tools to guide the process, and you must approach the issue with an open mind as to what will work best for those affected by it. Bad data from bias or poor assumptions produces bad outcomes.
Educate and empower people. Provide people with the tools they need to participate throughout the process, including infrastructure access with broadband and hardware, and affordability. Focus on issues that matter to them, because their interest will be more about the problem rather than the data itself. The National Neighborhood Indicators Partnership offers great free online resources, especially for involving students in data services on local issues.
Prioritize informed action. This goes beyond mere data collection; it's about harnessing and securing that data for real impact. The Partnership for Southern Equity took this to heart with the Metro Atlanta Racial Equity Atlas (MAREA). By analyzing demographic and geographic data alongside community input, MAREA crafts strategies that not only foster community trust but also confront and strive to rectify deep-seated inequities.
In the pursuit of creating truly people-centric solutions, it’s clear that the era of top-down, one-size-fits-all problem-solving is behind us and should be replaced by a more inclusive approach. When it comes to data, we don’t have to look at it as an either/or case. We can continue to rely on it so long as we ensure that our data use is enhanced by genuine human connections.
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