Part Two: Researching The New American Dream with the Gig Economy
This is the second post in a series about our research in partnership with JUST, an Austin-based nonprofit that seeks to build resilient communities through financial inclusion. For Part One with information about AC4D, JUST, and the focus of our research, go here.
Initially, our focus was simply to look at how gig economy workers are making financial decisions with fluctuating income streams. After a few initial interviews and feedback from our team, we’ve shifted our focus to better understand how the gig economy is supporting a new “American Dream” — one that values flexibility and freedom over stability.
Why the Gig Economy?
The gig economy is experiencing incredible turmoil as lawmakers, unions, workers, and companies all struggle to find common ground. Despite nearly a decade of growth in the on-demand economy, few unions exist and labor classifications are largely still in a traditional 1099 vs W2 model.
In the last few months alone, the first international food delivery app union formed, Instacart workers striked for the fourth year in a row, Uber drivers protested en masse at the homes of investors to protest the treatment of drivers, and lawmakers from California to New York fought to give more rights to workers.
While the gig economy offers a low barrier to entry and access to fast cash, it is also ripe for worker exploitation. Less than 5% of on-demand gig economy workers use apps as their primary source of income and retention rates among platforms are low, which leads to a highly transient workforce that is difficult to mobilize.
Despite these pitfalls, the gig economy continues to grow as Americans search for ways to supplement their income, pay debts, or meet earnings goals.
Assumptions to Guide Research
With all of this in mind, we started our project with assumptions that helped guide our script and exercises.
- We believe that on-demand gig workers largely overestimate what they receive from platforms — money, freedom, and control.
- We believe that on-demand workers will be more likely to cut corners and assume greater risks to achieve their goals, like not purchasing commercial auto insurance or preparing for taxes in advance.
- Because of quick access to cash that is difficult to track, we believe that on-demand workers will likely consider their goals in terms of time (hours, days, months) rather than clear dollar amounts. For example, a worker may set goals to work 3 hours a day, 5 days a week rather than setting a strict dollar amount goal.
- As a result of this easy access to “instant cash”, we also anticipate that gig-economy workers will loosely budget resources in the short term (days/weeks) rather than long-term (months/years).
We talked to 14 on-demand gig economy workers with current and previous experience with Uber, Lyft, Shipt, Instacart, Favor, Postmates, Amazon, Task Rabbit, Bird, and Rover. Roughly half of our participants used the gig economy as their main source of income with the other half using the gig economy to supplement their primary job.
With our focus statement and assumptions in mind, we developed a script and exercises to help guide our research.
First, we start the interview to get a foundational understanding of our participants’ backgrounds and involvement with the gig economy. Then, we ask participants to engage in a series of activities designed to uncover the mindset and behaviors people have related to gig work, decision making, and personal value systems.
We give participants cards with words commonly used to describe work like flexible, money, community, on-the-job training, and more. Then, we ask participants to organize these cards in a way that is meaningful to them to help us uncover what aspects of work are important and affect their decision-making.
Nando, an Amazon worker and previous Favor Runner, ordered cards from most important to least important. He placed most of his emphasis on a fulfilling, stable career with strong growth potential.
To help us consider how participants consider their current or future potential, we had them map out a dream web. Starting with them in the center, they mapped specific goals and we probed on if they had timelines or clear paths towards achieving those goals.
Brittany, a single mom of 4, drew that her main goals were to own a home, put her children through college, get married, and start a nonprofit. She was very focused on providing a better future for her children and her community, so they don’t have to overcome the same difficulties she went through as a single parent.
Stressed vs Stable Timeline
Next, we had participants map out a recent time in their life when they were feeling financially stressed or stable. This exercise helped us understand how participants have navigated moments of financial stress or stability. We also were able to better understand what specifically made certain situations stressful or stable and what strategies were employed in either state.
Holly, an ex-software developer and Lyft driver, mapped out the last year of her life — starting with getting laid off in January until now. A major theme we saw was that stressed periods are not always a result of finances. In Holly’s case, one of her strongest periods was when she was not working at all.
Why contextual research?
You may be asking: why sit with people and map their dreams when you could send out a survey? Why start with people at all? Oftentimes, we think we understand the problem space and spend the majority of our time on solutions. But our method forces us to take a step back and first look for the right problem.
By spending time with the people we seek to help, we can get a better idea of their values, needs, and behaviors. Surveys often point you to what people already know they want. Through contextual research and probing, we are able to find latent needs: problem areas that our users may not be aware of yet.
By the end of this quarter, we hope to present JUST with a succinct problem statement so they can move forward — confident that their solution solves the right problem.
Now that we’ve compiled all of our interview data, we are in synthesis mode — making sense of this data by finding themes and creating visual representations of the system (service slices and concept maps). From there, we’ll use those themes as the foundation for insights — which will help lead us to our primary problem statement. This problem statement will ultimately serve as the catalyst for all of our design ideas in Quarter 3 and Quarter 4.
Have questions about our research? Are you in the gig economy and want to design with us? Email us at firstname.lastname@example.org with details.