At Pivotal Labs, it’s second nature to bring lean user research methods to design in order to build better software. But what does it look like when you apply those research methods to the hardware development life cycle? Here’s what we learned in partnering with Revolar - a safety and wellness wearable startup.
Revolar is Spanish for “to take flight again” and their mission is to enable everyone to feel safe by being connected to loved ones. One way that Pivotal contributed to this mission was by partnering with Revolar to improve user research methods to help drive product decisions for both hardware and software. This post will focus on the user research methods we conducted to help inform updates to industrial design of the wearable hardware and its accessories.
We partnered with Revolar while they were planning and building the second launch for their product Instinct (now available on Indiegogo!). It is the only wearable capable of using GPS alerts to send for help, check-ins to be in touch, and step tracking to stay active.
Lean Research Similarities
For the most part running the hardware research study was more similar to software product studies than you might think. I would encourage anyone that is comfortable with lean agile software research methods to feel confident when approaching a study for hardware. By doing the lean user studies we made the product easier to use and more appealing to buyers. The industrial design changes came early enough the process while cost was minimal and we could avoid timeline delays.
Our approach to planning and designing the study looked quite consistent. Here are some of the activities we conducted for the user hardware studies:
Prioritization of potential studies
Research Planning Workshop
Recruiting + Scheduling
Interview Best Practices
A/B Testing (various options of hardware and accessories)
Iterate (Updated the hardware via 3D prototype)
Here’s a picture of some of the resulting synthesis…
Probably the biggest difference between hardware and software development life cycle is that typically hardware manufacturing is a lot less flexible than software. See the below mountain diagram that correlates the cost/risk of changes (y-axis) according to the phase (x-axis) in the industrial design/mechanical engineering life cycle. Having empathy and understanding of this cycle helps the software product team plan more effectively with the hardware team.
While flexibility is limited once manufacturing begins, there is definitely opportunity for iterations in the prototype / evaluate phase via 3D printing. For Revolar’s Instinct there were 25+ iterations from concept to final design. We were able to put the more mature iterations put in the hands of user and incorporate the feedback to modify some of the pieces or to make informed decisions on accessory options. The goal was to finalize the evaluative changes because once the tool and die are created it can cost tens of thousands to change the mold and causes significant timeline delays. For this project, the designs with the hardware vendor had to happen 4-5 months before the production and launch of the product.
To see a glimpse into the manufacturing process, check out this video about Instinct's manufacturing:
Lean Research Differences
While there were many similarities in how to plan and run the user testing research there were also some key differences. Here were some of the learnings and considerations we gained and want to share for anyone considering a wearability study:
Logistics: Testing with wearables requires extra consideration when recruiting and planning since they need to physically have the wearable. That can be solved by shipping them the wearable in advance (if the prototype is stable enough) or having them come in person for the interview. When onboarding, it also required some extra instruction and context education.
Study Type + Duration: We were extra discerning about what type of research study is appropriate for the desired learnings. Wearables often require the user to “live” with it for some time (e.g. at least a week). Sometimes a week-long (or longer) video diary study may be more appropriate to understand the natural contexts in which participants use the wearable.
Prototype Quality: 3D printed prototypes can break easily. We had 15 or so prototypes on hand and used them all. We explained they were rough prototypes to participants up front and offered to help them with certain tasks (after seeing how they would complete the task). We also had the industrial designer nearby to help fix them when needed.
Material samples: 3D printed prototypes will usually be plastic and won’t represent the quality of the materials of the final product. As a workaround, we had samples of the materials the product could be (e.g. shiny metal vs. matte) so that the user could hold, feel, touch and gauge the weight of options. It led to more insightful feedback.
Wearability In Motion: To better simulate actually wearing the wearable we divided our interviews into several sections. For part of the interview, we went on a walk or asked the participant to use a treadmill etc. We asked many of the task-oriented questions for when the participant was in motion. This helped minimize the hypothetical answers.
All in all, the studies let the team design an even better product for Revolar’s users by incorporating their feedback. We could not be more excited about the launch of Instinct or more grateful for the opportunity to partner with Revolar to help people feel safer.
For more about Revolar visit their website.
About the Author
Christina Freking is a Product Manager for Pivotal Labs with a passion for working on lean and agile teams and loves to learn what users think. She has a knack for breaking down chaos into valuable steps. Out of the office you can find her enjoying all that the Colorado sunshine and mountains have to offer - camping, hiking, skiing and snowshoeing.More Content by Christina Freking