Approximately 120 hours into the UX/UI Design program in IronHack, I’ve completed my first project in the program. For this first week in the Ironhack UX/UI program, I was sorted into a team of three to tackle the subject of our choosing.
Ahem…Captain’s Log, Stardate 20201708. My group set out to find a solution to better the immigration situation for enterprising immigrants coming into the U.S. and we hit most of our intended marks.
‘’The new century has experienced an exponential increase in people’s mobility all around the world. Even if migration has been a recurrent phenomenon across history, never before has humankind seen such a variety of destinations, motivations, and setups.
Along with the experience of migrating — possibly having to adapt to a different culture or language — come a number of bureaucratic tasks that need to be fulfilled within a certain period of time to legalize the journey in the host country.’’
My team members and I elected this particular wicked problem to solve, we wanted to try and challenge ourselves in going out of our comfort zone —
and trying to find an optimal solution to tackling this hard subject.
To try and get a better insight into the process of immigrating to the U.S., we began preparing, and publishing a survey and interviewing individuals who have in fact gone through the said process.
To help us get a better insight into people’s firsthand woes of dealing with this obtuse system we asked some people for interviews. The following were some of their key takeaways:
The majority of the applicant just couldn’t get a good read on how exactly everything works, and most had to depend on third-parties to help them navigate the system.
Moving onto our survey data we found from our data pool that 63.5% of past applicants hailed from Europe. Most had heard and spoken about this process with friends and family. About 34% had major frustrations navigating the immigration process, with a further 26% finding it hard keeping track of all the documents necessary.
Now while this was good from the onset — alas, we quickly we ran into a snag. We discovered that our data pool of individuals to research who have gone through the U.S. immigration system was rather limited with only about a total (as of writing) of 58 responses on our survey and only two successful interviews.
Consequently, the scope of the project had to include a wider gamut of data to include anyone who has gone through the immigration system, not limited to just the U.S. one. For this, we included some assumptive data of our own to help fill in potential knowledge gaps.
Following this, and some preliminary data, we finally started getting intp some fun stuff as we transferred our data into the Affinity Mapping phase:
Many people can have various reasons to immigrate to any place around the world. For example, someone who decides to immigrate may be seeking better employment, dodging regional conflict, or perhaps just seeking new adventures.
Via a combination of our survey, interview, and second-hand research, we ended up finding some common pain points that many individuals had when trying to go through the system we identified some primary Pain Points:
After we accumulated all the data we could from people’s demographic, behaviors, and other miscellaneous data — we proceeded to create our user persona to represent them all.
And so, Maria Smith (our user persona) was born. We thought she best represented the pool of people we interviewed, who have the aspiration of moving to the United States to pursue her dream of one day running a restaurant.
Provided the system doesn’t put a total break to it first…
After creating Maria, we hunkered down to try and map out what would be her actions throughout each stage of the immigration process, and after it is completed.
Unfortunately, the problems don’t end after being accepted.
After detailing our user persona, and figuring out what their intended goals are, we created a graph detailing what Maria’s journey through this process may look like in a few month's time. Any struggles she may at each stage of the process serve as potential opportunities for us to try and better her experience somehow.
Proceeding from the roadmap above, we analyzed the key events in Maria’s journey and came together again to finalize a problem statement:
‘’Our subjects, Entrepreneurial Immigrants, are finding the process of immigrating to the United States extremely difficult because of the lack of transparency, and unlisted resources necessary to complete the process. If we can solve these problems, this would make the immigration process for all future prospective immigrants a far more streamlined and smoother experience.’’
With our problem statement clearly outlined to ourselves, we started an individual brainstorming session to generate some ideas in a vacuum before later combining it back together to expand on one another take on how best to tackle those problems.
After further exploring our ideas, and discovering both: how similar, and radical they were, we followed by further quantifying our brainstorming and filtering out the features by using the MOSCOW method; from here we added and eliminated what said features were absolutely required now and what could be added later on for our product.
By recommendation of our TA, we began processing all our proposed ideas into the ‘’Won’t have’’ section of the graph. From here we worked bottom-up, quickly organizing ideas from lowest to highest priority.
By working this way, we expedited organizing key ideas that absolutely must receive our attention as soon as possible; and quickly spotting, and demoting those that can’t possibly meet the user’s needs in any practical form.
Finally. Concluding this part of the process we finally identified some must-have features for the intended Minimal Viable Project to meet the user's needs:
In the end, there was a lot to learn from diving into this subject, this was one of the most in-depth research projects I’ve ever undertaken. It was a really cool experience working in a team and trying to use all these techniques to better understand and filter our data. My only regret is that, as I implied at the beginning we were only able to hit most of our marks, with us running out of time trying to show our Success & Failure metrics in how effectively our proposed solutions can work. See you next time!
