Research Findings

After performing our research, our team developed an extensive listing of findings and initial design opportunities that will to drive our ideation process during the summer semester. Our findings fell into three broad categories, which we outline here as design opportunities.

1. Efficient Website Pipeline

AIR’s audiences, despite their diversity, all share at least one goal: access to the organization’s wealth of knowledge. Unfortunately, uncertainty and inefficiency complicate the current process for getting a project’s results from the researchers to the website. This has damaged employee confidence in the website, so fewer researchers even attempt to submit their work for the website.

2. Compelling Portrayals of Employees

As any AIR employee can attest, AIR’s strength and uniqueness derive from the individuals who walk into the office every morning. We strongly believe that showcasing more employees would better reflect AIR’s people-centered mission and dedication to employees’ well-being. Displaying more people on the website would help illustrate AIR’s commitment to its employees and would also help to promote its employees as leaders in their fields. It would better represent the breadth of research conducted by showing researchers in a wide variety of fields, and it would attract potential employees eager to work with brilliant, accomplished individuals.

3. Enhanced Search

The site search should enable users to rapidly locate publications, products, people, and any other desired information. However, the current AIR website does not offer filtering mechanisms. It also suffers from poor information design, offering incomplete result listings and leaving the site's users with little support in finding content that is relevant to their search criteria.

We grouped salient points and quotes from interviews by stakeholder group to build a picture of participants' motivations.
Between rounds of research, we gathered salient points and quotes from the interivews and contextual inquiries. We grouped these points by stakeholder group to build a picture of the motivations of different sets of participants. This data fed directly into our models and design.