Decision Tree Overhaul

Background

Dycom Industries relies heavily on decision trees to collect data from workers in the field. Each tree uses a series of conditional questions for users to answer about time worked on projects or assets used for a job. Though they were created with the intention of making billing quicker, many users found the questions clunky or confusing, while tree builders struggled to make improvements.

Our UX team took on the task of optimizing the decision tree experience, for both the end-users and tree builders. I guided the overall content strategy for this effort, with the following objectives in mind:

• Analyze existing questions to identify trends

• Create standards around language in trees

• Develop a framework for question writing

Process

Audience analytics and stakeholder interviews

I relied on data collected in previous research projects to influence certain decisions on comprehension and readability. In past studies, our business found that on average, field workers read at a 5th grade level.

While field laborers were the true final audience for these decision tree questions, I also spoke with the question writers to get an idea of what might help them create copy more efficiently. I found out quite a bit about their process: it actually takes a team of three to read the contracts, come up with questions to ask to capture the proper data, then code the tree. The knowledge it takes to read and translate contract language is very niche, so we really wanted to find a way to capture that knowledge in a streamlined system. Through these interviews, we came up with a few ideas on how to help out, most notably by standardizing the question writing process and improving their content strategy. My two major deliverables for this effort were content standards for these trees and a question bank to optimize their creation.

Data mining

Our team analyzed a spreadsheet of a few hundred questions utilized in past trees. We removed duplicates, then created groupings of the questions. Tree developers would use these groupings as filters in the final question bank to find pre-written questions they can use in their trees. These were the major question types we identified:

• Measurement

• Duration

• Type of

• Photograph

• Notes

• Timekeeping

Content strategy and design

After finding the prominent question types, I created a set of best practices and pitched these to the product team. Then, I helped rewrite the existing questions, created templates to use for common question types, and a guide to creating questions from scratch. I wanted all of our content to cater to the needs of our primary audience (construction workers) and stick to a conversational approach. Since I was working within a lower reading level, I spent time cutting down the complexity of our sentences/vocabulary and creating consistency among similar questions.

Final products