WaterWise is a web-based solution that accumulates water quality data and information about lead pipes infrastructure into one, easy-to-use platform. Within the site, users can uncover about the quality of water in their homes, learn about the health risks of contaminated water, compareoptions for addressing poor water quality, and connect with local government andcommunity representatives who can help.
Although much of this information exists today, it is highly fragmented and difficult to understand. WaterWise is a first-of-its-kind platform that simplifies the water quality conversation into a digestible problem and empowers users to take meaningful action based on their needs.
The site leverages AI and predictive modeling from Blue Conduit, a water infrastructure consultancy started at the University of Michigan, and is designed to reach communities across United States that may be impacted by poor water quality and help them understand their water infrastructure.
As an Impact Design Fellow at the Ross School of Business, I was fortunate to have worked with Blueconduit on this project that serves my passion of designing information and communication technologies for development. As a UX design evangelist, I kickstarted the design thinking process at BlueConduit and helped to make their platform more intuitive and reachable with an added value.
Update [27/09/2020] This project is currently under development.
Role and Responsibilities
Impact Design Fellow - UI/UX Evangelist
- Lead a complete design sprint to ideate on a solution for the water vulnerability problem
- Ideated on business solutions to make the product viable and have a competitive advantage.
- Developed a working prototype for BlueConduit to pitch their solution to their respective partners.
5 months (Jan '20 - May '20)
Zichen Wang / Torre Palermino / Nan Sithanamsuwan
Professor Eric Schwarts
Impact Design Studio Team
‘Clean Water and Sanitation’ is sixth on the list of the United Nations’ (UN) seventeen Sustainable Development Goals for achieving a better and more sustainable future for all. According to the UN, “Water scarcity, poor water quality and inadequate sanitation negatively impacts food security, livelihood choices and educational opportunities for poor families across the world.
Nearly 63 million people in the United States have been exposed to unsafe drinking water in the past decade. Because of the pervasive nature of this water problem, estimates for replacement of affected pipelines trend north of $1 trillion USD. Thus, it is not feasible for the federal or state governments to budget for total replacement at once.
How might we leverage and consolidate available information to create awareness that builds trust and inspires action for improved water quality?
A Michigan run startup focused on this problem has devised an algorithm to predict the lead pipe infrastructure of the area. Blueconduit’s Flint Service Line Map allows residents and local governments to get the latest service line data for their address. This not only create awareness and action towards water quality, but also helps local governments to push their funds to the AI predicted most affected areas.
Unfortunately the designs are in a Non Disclosure Agreement. Feel free to email me at firstname.lastname@example.org to learn more.
Waterwise was developed in conjunction with BlueConduit where our team of designers and MBA graduates worked on an interlaced business + design sprint to ideate on solutions that would benefit the cause and the business. While we were understanding the user pain points and defining our problem statements, we were also ideating on our business model canvas to re-imagine the product for BlueConduit.
The target users are those who live or plan to live in communities with high risk of water contamination like lead exposure, such as those established prior to 1950.
To understand more about the users and their needs, we conducted contextual interviews and surveys to get a sense of their pain points.
02. USER RESEARCH
To understand our users’ needs and the current water information sources, we interviewed community members, water vulnerability experts and local government officers to better understand the problem. This helped us identify gaps in the current system and how all of the different users get affected by it.
We created a survey to gauge the understanding of the problem and current solution used by residents. We started off by listing out all the questions that we needed answers for. For example, demographics, awareness of the water problem, current solutions they use.
- 66% of the respondents are not aware of the water quality reports in their area.
- 55% of participants found lead levels to be extremely important, followed by contaminants in the water.
- Most participants prefer water solutions that are easy to implement and can be customized to their needs.
- More than 50% of the people are completely unaware of the health issues caused by water.
- Community involvement is one of the most preferred way to contribute to water problems.
Based on our research we created multiple personas for our residents and community members. We identified three major target groups who directly or indirectely are affected by the water vulnerability issue.
03. IDEATE AND DESIGN
Business Model Canvas
We started developing our business model canvas and identifying areas where we can place our product within Blueconduit’s landscape and ideate on potential sources of revenues.
Based on our research, users and business model canvas I started ideating on a platform aiming towards water quality information and inspiring action. I identified a basic user flow with all the data that we had access to:
- Lead pipe infrastructure data from Blueconduit.
- Water quality information by the local EPA reports.
- Water quality and health information by EPA websites.
- Possible call to actions - such as community and civic engagement
Low fidelity Prototypes
After validating the sketches with the stakeholders I took a closer look at the required features and created low fidelity wireframes and prototypes for the platform. The low fidelity prototypes were made and iterated upon
After deciding on the feature list we mapped out a user flow that would cater to all the required features of the platform.