Working with some of the front end research was done by a team of MPD alumnae, we set off to re-evaluate a case study for Nissan’s (then concept) the Leaf. The study concentrated on using the available “shore power” from the home when the vehicle is charging, as well as the downtime to provide a self-cleaning solution for a car. Using the research we were provided, we create concepts, developed and gathered more concentrated research, and validated our ideas.
The process for this project moved forward with the design running parallel to research. After analyzing the research, we came together as a team with our individual concepts.
We each picked concepts and went through a round robin ideation session. This gave us the opportunity to improve upon and build on each others’ ideas. At the end of this session we discussed our concepts and used them as building blocks to create a holistic solution to a self-cleaning car.
In parallel to this, we developed and distributed a make kit to identify user pain points and document their current car cleaning processes. The participants were different from those who were prompted to provide feedback on our original concept solutions. After compiling our research, we used it to evaluate our proposed system. This gave us the opportunity to address holes and over engineering. After revisions, we showed the concept to users to get direct feedback.
Our research was focused on user collages and coloring in parts of the car that were hard to clean as well as areas where the most time was spent cleaning.
We took both of these sets and overlaid them to create a heat map of areas where difficulty and time spent were most universally prevalent.
We used the user collages to validate our proposed system while highlighting opportunities that we might have missed the first time around. After sketching out the user solutions we plotted against our original concepts based on their similarities. We received both validation and new insights based on the unprompted research.