When organizations training and support their power users, they typically focus primarily on individuals – even if they are training staff by department. But organizations aren’t just composed of individuals. Humans are social creatures who are often part of rich, complex networks.

Makers All, the parent organization for Data Chefs, argues that our society would be far more effective in training community members to become emerging tech developers if we learn from the example of agricultural’s Extension Services, which leveraged the social nature of people to radically transform agricultural practices. For example, Extension Services employed at least one Extension agents in every rural county, who would:

  • Identify and develop Natural Leaders. Extension agents often focused on identifying and developing natural leaders: farmers who were already widely respected in their community. These natural leaders had preexisting social networks and relationships they could use to recruit other famers. And they were also likely to understand the concerns and fears that agents needed to address if farmers were to be convinced to adopt new techniques.
  • Nurture Neighborhood Clubs. Extension agents helped farming communities form neighborhood clubs and worked with clubs to ensure farmers got a steady stream of ideas about how they could improve their farming. As a result, farmers weren’t just hearing about an idea brought in by an outsider, they were learning while surrounded by their peers who spoke the same language and understood the realities they faced.
  • Foster Community Events. Extension agents helped foster state fairs and other places where farmers could see demonstrations, compete to see who could use new techniques to grow the best crops, etc.

Data Chefs argues that:

  • Individual organizations should use a chopped down, lightweight version of Maker All’s strategy that’s designed to fit the needs of their organization and staff
  • As organizations begin to collaborate across ecosystems, start taking small steps towards the more robust approach envisioned by Makers All