Methodology
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Stakeholder Interview
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Contextual Inquiries
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Personas
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User Journey Map
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Surveys
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Prototyping
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Usability Testing
Tools
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Sketch
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InVision
Reducing Racial Disparities Through a Data Resource Tool
Summary
Client | Project:
City of Minneapolis | REIA Web Resource
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Design Team:
See Xiong, UX Designer
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To help policy makers gauge how a policy ordinance, program, or budget item affects community members that they’re serving, particularly among Black, Indigenous & People of Color (BIPOC) communities, the City of Minneapolis’ Division of Race & Equity has implemented a Racial Equity Impact Analysis (REIA) process that consists of documentation that must be completed for proposal requests. The research section of the REIA documentation form has been a major challenge for city employees. Users struggle to find data on how their proposals impact the racial demographics of those geographic areas.
Objective
The City of Minneapolis’ Division of Race & Equity is in need of a data tool to help city employees find racially disaggregated data to support their requests for proposals, however, many city employees don’t know where to start looking for data. To reduce racal disparities, it’s crucial for city employees to understand how the policy, ordinance, program, or budget item affects community members, especially if that’s the community they’re making decisions for. The current solution is a folder of random external links on a Sharepoint page that is not accessible off VPN. There are no instructions as to where each link leads to or what types of data will be found under each link. Under constrained branding guidelines, I was given 3 weeks to research and prototype a tool that will help users easily find racially disaggregated data to incorporate in their REIA process to help reduce racial disparities for the City of Minneapolis.
Research & Prototyping
Understanding the Journey
After an initial stakeholder interview with the City of Minneapolis’ Division of Race & Equity a group of researchers, including myself, submitted a survey to current city employees to gain insight on attitudes and knowledge on the REIA process. In the survey I found that only 16% of participants felt very comfortable finding credible data to support program and policy decisions, with only 12% ranking Minneapolis as being effective in addressing racial equity. The survey also found that users wanted to find demographic information on residents, business owners, and renters across the city. I then conducted remote contextual inquiries to understand the process of submitting a proposal and researching data to include in the REIA form.
Persona based on City of Minneapolis employees developed by See Xiong
To externalize the user journey and highlight user pain points, I developed a persona based on employees I interviewed and mapped out a user journey map. A common challenge for employees was finding ways to eliminate racial disparities in daily operations, which was why the Division of Race & Equity implemented the REIA process. The Division of Race & Equity wanted employees to use it as an inclusive lens into the work that they do, but the process was still falling short.
User journey map designed by See Xiong. The "A" represents the part of the journey where I plan to implement a solution to make the REIA process easier for users to find supporting data.
Synthesizing & Wireframing
After conducting user interviews with several employees I learned that I needed to create a solution to help users find racially disaggregated data on Minneapolis communities. There were already many credible databases online, many of which are partnered with the City of Minneapolis. The problem wasn’t needing a new database, but figuring out how to help users find these databases. The solution needed to be accessible off vpn, public facing, with information on what type of data can be found. Because there are so many helpful databases already, I focused on compiling these databases in a webpage. I started sketching out various wireframes of what this webpage could look like before digitizing a prototype to be tested in usability testings.
Initial wireframes sketched by See Xiong
Prototyping with Informed Design Decisions
Following brand guidelines, I designed the resource tool in Sketch and transitioned it into an interactive prototype on InVision. At front and center of the webpage is Minneapolis demographics, which according to my user interviews is data that employees commonly include in the REIA.
I also found in my research that the top data employees search for are data on Minneapolis demographics broken down by neighborhoods, to which I designed a map where users could click on the communities they wanted to learn more about. US Census data and police provided data, also helpful databases according to participants, are set as icons as you scroll down the page. These icons will lead to external links of credible data sources and opened in new windows so users can easily go back to the resource webpage. Link descriptions are provided to save users time and guesswork of where the links lead to.
The REIA process is really important, and insight I found through my research was that users wanted helpful guides to help complete the REIA form. This is why I added a section on the right side of the page called "Helpful Guides" that includes links to helpful guides provided by the Division of Race & Equity.
Data Resource Tool Prototype for City of Minneapolis designed by See Xiong
Usability Testings
I moderated and tested the data resource tool prototype with city employees to assess the ease of finding racially disaggregated data. In my usability testings I found that participants said the webpage was easy to navigate and that they knew what to expect before clicking each button. They weren't overwhelmed with the information and the resources listed. Participants said the solution I created was very helpful in finding research to support their proposals. My prototype and findings were presented to the City of Minneapolis’ Division of Race & Equity, which was acclaimed as beneficial research findings. With so many divisions it's hard to track down readily available data, so mitigating it onto one webpage that can be accessed off VPN will help city employees easily finding racially disaggregated data for the REIA process during their daily operations.
Takeaways
When trying to understand the pain points of the problem, it’s extremely important to ask the right questions in contextual interviews. It was a challenge trying to understand in which part of the REIA process users were getting stuck in and why they were getting stuck. A lot of users said there wasn’t any data online to support their proposals, when in reality they were just stuck trying to find a starting point. I found it instrumental to remember the research goals and continually empathizing and asking questions to unravel where the problem space is.