GrowHub
CASE STUDY
This is a look inside the Species Product feature of a database application called GrowHub, which was developed for the United States Forest Service. The application tracks the production of seed and seedlings for 8 nurseries across the United States.
The GrowHub team was tasked with modernizing the legacy process for creating and editing Species Products.
The goal was to simplify the process for employees tasked with growing seedlings for clients. This would enable users to:
-
Select species products with optimal growth specifications
-
Quickly calculate the amount of seed and space needed to grow a requested product
-
Select seeder and grow location settings
-
Quickly calculate how many samples are needed for inventory and the expected growth of all seedlings being grown per product
A screenshot of the "Seed Factor Table" feature inside an individual Species Product
I used this to explain the logic behind my recommendations to our SMEs and Product Owner, alongside comparisons of the how the calculations between nurseries were inconsistent and how the proposed changes would align them.
A high-fidelity wireframe along with explanations for the SMEs and developers of the "Add Seed Factors" Default lifecycle state. Upon first creation, we needed to establish a "default" set of factors to be populated into the calculations of Estimated Seed Needed.
A screenshot of the "Seed Factor Table" feature inside an individual Species Product
Data Discovery
After gathering the primary user story from the business, we realized we needed a "big picture" view of how Species Products works with how seedlings are tracked inside of the Seedling Production section of the application.
I began to work through the data that existed inside the nurseries’ legacy system and inside of GrowHub. I highlighted relevant data between Species Products and Seedling Production.
Then I created two versions of the Seedling Production workflow; the first allowed us to walk through the process and the second allowed us to highlight the data that needed to be changed.
Gaps in the Workflows
The largest gap between our current version of Seedling Production and what was being introduced in Species Products was the addition of extra grow units, such as transplant beds and switching between containers.
While working through the legacy data, I realized that Species Products would have usually 2 different grow units broken up by how long the products were in each container.
Due to this pattern, I suggested the addition of “Grow Cycles” where we would allow users to designate how long and where products were grown. This also allowed us to further break up inventory specifications between each grow unit, which was missing in their legacy system.
Iterative Solutions
As we worked through each section of Species Products, we discovered each piece required its own set of problem solving.
For example, each Species Product had its own set of "Seed Factors," a percentage they used to affect the calculation behind the total weight of seed. Each of the 8 nurseries used its own language for each factor and changed the calculation based on its definition.
We broke down each factor used and determined the goal behind it. We concluded that every factor could be categorized into one of three percentages: survivability, harvestability, and shippability. We decided to standardize the factor names and their calculation function across the board. We also include definitions of what each one means inside the Seed Factor creation feature for usability.