Polaris research repository
In 2016, under the leadership of Tomer Sharon, the WeWork UX team created Polaris: a live, dynamic, company-accessible database of the member experience. This tool provided a way for WeWork employees to access the qualitative research that could provide answers about our members and their relationship to WeWork in a way that solved broader research problems such as bad research memory, research silos, reports and research dictatorship*.
* For more details, read Tomer’s medium post, Democratizing UX (Jan 2017). Polaris was also mentioned in Tomer’s interview with Steve Portigal on Dollars to Donuts (March 2019).
Creating polaris
In the early years of WeWork it was possible for teams to talk to every single member. However, with the rapid growth of WeWork’s member base, geographical expansion and increase in diversity, the direct connection to members was becoming increasingly difficult. The goal of Polaris was to create a way for teams to stay connected to the member experience, first-hand, and enable teams to better:
Prioritize: decide whether one project is more important than another
Educate: learn more about a topic of an existing project
Allocate: help inspire ideas for a next project (big or small)
By providing access to the qualitative research that could answer fundamental questions about the member experience, teams would be able to “own” research and be empowered to make decisions based on real human-based understanding.
TIMELINE
This project spanned 6 months from kick off to the internal release of the Polaris web app.
ROLE
I worked alongside another researcher and a service design lead to develop the taxonomy and initial prototype (in Airtable). During this time I personally contributed >300 qualitative interviews (amounting to thousands of nuggets), curated > 50 “playlists”, developed a unique discussion guide format for remote interviews and refined the structure of meta-data tags.
I later led the internal marketing of the Polaris web app (including a full email marketing strategy and content curation) and developed / facilitated a training strategy around conducting qualitative research interviews, creating nuggets and curating playlists within Polaris.
Communicating polaris
Polaris was a research tool that would allow WeWork team members to search and view/listen to nuggets (consume), contribute their own research (create) and assemble playlists to save or share (curate). But we knew it would be powerless unless potential users were aware of and knew how to use it to their advantage.
An internal marketing strategy was crafted and executed that targeted several teams at WeWork (across departments) and communicated the function and impact Polaris could have for them. This targeted content was created by getting a full understanding of each team’s unique motives and challenges through scanning internal content, conducting interviews and observing teams work.
This communication not only allowed us to introduce and familiarize Polaris to teams but also served as a channel for us to receive feedback and improve the experience.
Impact and implications
Since it’s release internally, Polaris has served as a crucial foundation and inspiration for several projects across the company. It has provided substantial evidence for prioritization and inspiration pre-project, education and gap-finding for additional research mid-project as well as a historical reference of changes in the member experience over time.
This aggregation of data has not only served individual teams, Polaris has also been used to develop shared languages and taxonomies used company-wide. Additionally, Polaris playlists have been used as an on-boarding tool; familiarizing new employees with aspects of the member experience.
Though released as an internally facing tool, public communication and access to the Airtable base template has inspired discussions in the public UX, Design and Research communities. Polaris has also been mentioned in public channels related to Research Ops - a recently emerged and rapidly growing field focused on operationalizing research.