Precision Ag Project


The modern farm is data-driven. Good design makes the data actionable for everyone, not only the largest and most advanced farming operations.

For almost five years, I’ve worked as an interaction designer on a complex platform for precision agriculture. My areas of focus have included:

  • Cloud Data Management
  • GPS-Based Mapping and Visualization
  • Real-Time Operation Monitoring

Designing with Data

Integrating views of data across a diverse suite of products is always a challenge. It’s a special challenge to make it all come together on a tractor in the middle of an Iowa corn field.


KeyS to Success

Being able to switch between thinking at a high, global level to a low, detailed level was critical to delivering successful designs that stayed consistent across disparate parts of a complex system.

The design team I worked with supported multiple groups of developers. Our ability to quickly digest information ranging from technical specifications to tribal knowledge allowed us to keep ahead of a fast-paced development schedule.

At the end of the day, there are only so many resources available to get a product out the door. The trick is in finding a solution that not only supports the user but that the business is also able to build and support.


Creating flows are a big way that I think through interactions, feel out the shape of a system, and communicate with others about the design. They also feed directly into the development of interactive prototypes.


Diverse Stakeholders

My role on this project involved wrangling complex streams of operational and equipment data into something that benefits everyone involved:

· Operators sitting in the cab
· Farm managers back at the office
· Agricultural service providers
· Technicians
· Dealers

Driving Consensus

What excites me is being able to make things that people can point at and rally around. That happens through debate and iteration, but in my experience, it always happens best when there’s somebody in the room drawing to keep the thoughts on the wall and out of our heads.


This system was tested constantly. To do that, we created lots of prototypes at different levels of fidelity. They ranged from PDFs with hotspots to relatively robust interactive prototypes in code.


Complexity and time invested

It’s amazing what you can learn from just printing out some wireframes and putting them in front of users. Building robust prototypes is sometimes appropriate, but as complexity increases, it can easily become time-consuming and difficult to maintain. With any prototype, you want to learn from it as quickly as possible. So, to try to avoid wasting time, I always try to have a good idea of what I want to learn before anything is built.