Emotional Waste
Emotional Waste
UC Berkeley | Fall 2017
During fall 2017, I took a class at UC Berkeley's Haas School of Business called Design Thinking & Innovation in Business. The class was led by Haas professor Clark Kellogg, who is also the founder + CEO of an innovation strategy firm, Berkeley Innovation Group. The main focus of this class was to teach human-centered design principles and translate those skills into a final project. My team and I chose to research the topic of improper waste management.
The Problem
How might we motivate consumers and producers to become more sustainable when it comes to disposing waste? Many people don't understand the difference between compost, landfill, and recycling, which is typically a result from lack of proper education and awareness or lack of care. When waste is sorted incorrectly, it affects the environment, the safety of waste management facility workers, and the products we use. My team and I were inspired to approach this problem from this article.
first step: observations
Design thinking methodology follows a four step process that begins with observations, which typically consists of primary and secondary research. We began with primary research and conducted many ethnographic interviews. Our main goals for this step of the process was to understand people's comprehension of waste management, how they go about a trash routine, and what their perception is on modern waste systems. We listened to many different stories and from these takeaways we created customer journey maps.
Second Step: insights
The next step of our process was to formulate insights from our observations. We compiled information from each of our interviews and noted the most interesting takeaways and aspects from each interviewee. Our main goal for this step was to find trends among reasons as to why proper waste management is still a societal issue.
Grouping our observations into affinity maps.
Key Insights
- Consumers like convenience, so producers support a non-reusable culture by providing single-use items, which ultimately encourages consumers to continue a wasteful lifestyle.
- The size of a trash bin restricts the amount of landfill created by consumers for their own convenience.
- Quantifying the amount of water bottles saved on refill stations creates a community out of the displayed number and singles out the user who does not participate.
- When a company is penalized for improper waste sorting, their employees associate a monetary cost to trash that incentivizes people to participate in a culture of sustainability, even outside of work.
From these insights, we brainstormed opportunity spaces of people who might fall into situations that we created from our insights. These opportunity areas are essentially demographics that would be targetable with an implemented solution. We placed these opportunity areas into 2x2 matrices:
Highly educated → Low education & A little of time → A lot of time
Low income → High income & Infrequent shopping → Shopaholic
Ignorant → Advocate & Apathy → Empathy
Urban → Rural & Detachment → Attachment
2x2 Matrices
How might we
After determining different target demographics for our problem, we constructed a few "How might we" questions that could eventually lead into an idea.
How might we change appearance into actuality?
How might we make sustainability affordable and profitable?
How might we get the wealthy to invest in sustainability?
How might we motivate the highly educated to dedicate their time to sustainability?
How might we adjust company cultures?
How might we redesign waste management systems to emotionally inspire and influence consumers?
We decided on the last "How might we" statement because we believed that this allowed for multiple ideas that also focused on consumer need. This statement also addressed our insights because it centralizes around an emotional influence, which according to our insights, is lacking.
Third step: ideation
We focused on our main "How might we" statement and developed multiple ideas that circulated around the central idea.
Low-fidelity prototypes
These bins are low-fidelity prototypes of what they may actually look like if implemented. The front facing side of the bins have environmental statistics and accompanying images that aim to adjust consumer behavior. (Materials: Cardboard boxes, paint, X-acto knife, chalk)
