Information Architecture (IA)

TLDR*: 

Using search analytics, card sorting, tree testing tools, and interviews with stakeholders, I conducted a content audit, then created a robust, effective, information architecture plan for ProbablyMonsters, significantly reducing the time to find information for engineers and the hightly technical C-Suite at ProbablyMonsters. 

"The new documentation architecture will accelerate productivity across the board."

The Challenge: 

ProbablyMonsters included component independent game design studios. Their IA goal? To maximize opportunities to share information while limiting data where needed. They were dedicated to providing state-of-the-art technology to their engineers and artists, so the architecture was best-of-breed but highly specialized and, often, unique to each studio. Valuable content was distributed in various Slack channels, Atlassian Confluence, and SharePoint. 

The Method: 

I used search analytics, tree testing tools, and interviews with stake holders. In addition, I spent some time doing a  deep dive into what made this content, and ProbablyMonsters' goals, unique. This gave me the content expertise to ask the right questions of my audience, and to predict needs they did not verbalize. See the analytics screen shot below for an example of the analytic process. 

Snapshot of the Results: 

When my project had ended at ProbablyMonsters: 

• duplications were gone

• obsolete information was clearly archived

• new information was found first

• information that had been "lost" in Slack conversations or SharePoint was organized intelligently in Atlassian Confluence

• documentation was organized, sorted, and keyed in a way intuitive to Probably Monster's audience. 

• creation of templates with keyword fields and other organizational items built in to continue the newly designed doc structure going forward. 

*TLDR is an acronym in tech that means "Too Long, Don't (Want to) Read" 

In other words, a summary.