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Precision Livestock

An online application that visualizes cattle health in feedyard operations.

My Role

UX/UI Designer (Focus)
Brand Designer
Marketing Designer

The Team

1 UX/UI Designer (Me)
2 Software Engineers
1-2 Developers
1 Dev Ops Engineer
1 Machine Learning Engineer


From 0 to 17 users
Average Time Between Sessions: 7.25 hours
Acquired by Merck & Co.

Key Contributions

Design Scrum Process
User Research/Discovery
User-Centric Design Execution
User Testing
Design Update Releases

11.01.2016 – 09.01.2020


Precision Livestock was an early-stage start-up based in Lincoln. The founder aimed to visualize cattle health in a simple application that paired with the Quantified Ag Tag. The team was small, and we worked in an agile manner by continually updating our concepts from user feedback.


The cattle industry hasn’t changed much in the past 100 years. Many operations are stuck in a “If it’s not broke, don’t fix it” mentality. Many who knew about us could see the competitive edge it could provide but avoided adopting it into their operation.


After speaking with cattle workers across the country we learned cattle workers feared the time it would take to train workers on a completely new system, the unknown cost of a system like ours, and the potential of making some cattle worker jobs obsolete.

Our Challenge

With the fears of the users we were trying to serve our challenge was clearly user adoption. To get past this we would need to prove ourselves through scientific research and positive early adopter feedback. 

Design Challenges

Regarding design, these fears presented a whole set of challenges for me to work through with Precision Livestock software design.

  1. Whom would we be able to help the most within a cattle operation?
  2. How can we help those cattle operators be more successful?
  3. What current practices and technology are cattle operators working with on a day-to-day basis? How can we make it better?
  4. Many managers like to view data a specific way. How can we be flexible to that without jeopardizing our applications design. 

1. Whom would we be able to help the most within a cattle operation?

After spending time observing many operations around the country I learned there are three main personas we should design the application for initially.

All personas below are emulated on real people we know in the cattle industry.

Tadd Thomas

Skills: Riding Horses, Handling Cattle, Identifying Sick Cattle, Processing Cattle, and Doctoring Cattle.

Description: Tadd is a Pen Rider for a major feedyard operation. Tadd is highly hands on and knows how to identify sick animals.

Goals: Identify sick animals, process new incoming lots, and help maintain healthy animals at the feedyard.

Problems: Cattle naturally hide their sick symptoms so finding every sick animal is close to impossible. Processing new incoming lots can be tedious and take all day to complete. Tadd’s job depends on his ability to maintain healthy animals at the feedyard.

Jason Floyd

Skills: Has an analytical mind, loves to build and create reports, knows how to generate a profit, keeps cattle operation in business.

Description:Jason is a Feedlot Manager for a major cattle operation in the Midwest. He wears a lot of hats throughout the day to make sure his cattle operation stays in business.

Goals: Organizing 10,000-50,000+ head of cattle, ensure the operation is profitable, manage employees, report weekly and monthly on feedlot performance, and overall maintain cattle operation from a business perspective.

Problems: Lack of documentation from busy employees, poor organization of cattle during content entry by Pen Riders, communication with employees can be difficult day-to-day, having a high-level perspective of overall health of the operation in it’s entirety.

Dan Thomson

Skills: professional vet, identifying sick animals, treating sick animals, prevention of sick animals, lowering morbidity & mortality rates

Description: Dan is an exclusive veterinarian for many different feedyard operations in a particular region.

Goals: Identify sick animals, monitor an operations mortality & morbidity rates, prevent operations mortality and morbidity from increasing, keep disease from breaking out, and generally keep animals healthy

Problems: Not always there to help treat sick animals or monitor the cattle’s overall health.

 Due to the nature of their job, Pen Riders were the users to design the application for the initial product launch. Pen Riders process new lots (cattle groups) into a cattle operation so they are responsible for initial cattle data entry. Pen Riders also are responsible for visually observing the animals identifying sick outliers. Our software flagging system will help them achieve the most success day-to-day.

2. How can we help Pen Riders be more successful?

To start, we needed to answer these questions.

  1. What do Pen Riders need?
  2. What would make them open the application every day?
  3. What would help them with their job so much they can’t help but use the application?
  4. Do they currently do or use something to help them with job success?

After observing Pen Riders for a full year we learned we could answer all of these questions with the design of a single module, a “Pull List”

A “Pull List” is a list of sick animals Pen Riders would identify to pull and treat the next morning, increasing their efficiency.

Let’s Make It Digital

Taking the “Pull List” from paper to dynamic and interactive list created the perfect stage to show off which animals our Quantified Ag Ear Tag flagged within the last 24 hours.

After the discovery of this problem’s solution I began wireframing the design out and after many iterations and updates with user trials and feedback we finally landed here.

Insight #1

The “pull list” gives the user a reason to open the application up every day. Without doing this they would be completely inconvenienced in their job.


Average Time Between Sessions: 6.5 hours Desktop and 8.5 hours Mobile

Insight #2

Once Pen Riders were in the application they were more likely to keep using it for different tasks throughout the day.


This encouraged us to aim for an all-in-one software solution to help with Pen Rider’s efficiency even further. I designed a “Processing” and “Doctoring” system within the app to help record animal treatments and initial content/data entry.

Insight #3

Both the Pen Rider and our system used together gave a cattle operation the best results in identifying sick animals.


Created a decrease in morbidity and mortality rates. With a sick identification rate over 95%.

3. What current practices and technology are cattle operators working with on a day-to-day basis? 

On top of  identifying sick animals Pen Riders also take on the bulk of “Processing” and “Doctoring” events at most feedyard operations. However, the software they use to accomplish these events are all archaic and not integrated at all. We could make it better by integrating “Processing” and “Doctoring” into our application for an all-in-one solution so, we did.

How can we make it better?

Giving users an all-in-one software solution just made sense. Not only would this make adoption easier but we could dynamically input content fields. Speeding up “processing” and “doctoring” content entry; which for many is a huge plus!

4. Many managers like to view data in a specific way; how can we be flexible to that without jeopardizing our application’s design?

We obviously couldn’t design a custom setup for every single one of our customers but what we could do is discover what the most important reports would be for a list of canned reports.

No longer focusing on the Pen Riders this was a task more suited to the Feedlot Managers and Veterinarians. So I conducted a handful of user interviews to learn what exactly was the most important information to see at a high-level every day for these individuals. From there I designed a dashboard that hosted all of those reports in one place.

To go even further and cater to the managers who are power users and whom are going to create their own reports anyways we designed a report builder for those individuals to build their own reports and save them to a custom reports list.


Insight #4

The “pull list” feeds into a need for further interaction with eventls like “Processing” and “Doctoring”


Adoption went from 0 to 17 customers from around the world with small to large size cattle operations./p>

Insight #5

High-level cattle health data gave Feedyard Managers and Veterinarians more flexibility in their on-site/off-site management.


Managers and Veterinarians had the opportunity to work remotely more often. Giving our system a competitive edge in the market.

Insight #6

Our system had the capability to zoom out very high-level and zoom into one single individual animal.


Now users can view the health of every single animal in any large or small cattle operation. A feature that’s never been possible before.

What we learned

I learned

Throughout this entire experience the biggest thing I’ve learned was how to whittle big ideas down into a functional hierarchy of shippable updates. How to take a product from the very start to an initial launch in the hands of early adopters to updates using user research and feedback.

The team learned

Throughout this entire process creating a brand new product that solved an old-time problem the team learned how to navigate through a sea of past failures from others that came before us. We also learned from our own failures, adapted, and moved on more times than we could count. At the end of all of it, we clearly communicated our ideas in a way that excited potential customers enough to get Precision Livestock to its official product launch within android and ios app stores.