Marsha Nunes

I addition to user research for a specific project, I also conducted broader research such as periodic surveys to understand how MITRE employees use their phones and our mobile services.

For this latest survey, I worked with stakeholders to identify their questions and refine topics - tracking trends such as personal phone OS preferences, benchmarking satisfaction, gathering thoughts on proposals such as a Bring Your Own Device model and providing access to advanced Microsoft tools with AI, and collecting evidence to support plans such as retiring a MITRE phone-specific version of MITRE@Work.

While the survey was over 30 questions, I aimed to keep participants moving through it. From previous iterations, I had learned to place free text questions at the end, so people didn't repeat themselves or try to squeeze everything into the first available comment box. Generative AI was also helpful for refining questions and creating more complete sets of possible answers, to avoid respondents getting stuck if none of the options quite fit.

High level topics for the survey. Source: MITRE

Sample survey question. Source: MITRE

I used AI to identify preliminary high-level themes but also completed my own analysis of the free text responses to get at more subtle findings within MITRE’s context. My presentation for stakeholders and project teams highlighted both the data and recommendations as well as the authentic voice of employees.

Analyzing the free text responses. Source: MITRE

Sample responses and themes. Source: MITRE

Sample MITRE@Work results. Our timecard (TRS) is the most frequently used feature and the control value here. The lower rated features were ones we had hoped to retire due to reduced usage within the app. Source: MITRE