Research is not about asking users what they want.

If I had asked people what they wanted, they would have said faster horses.

– Henry Ford

This is one of the most cited quotes on innovation and user involvement, associated with Henry Ford. It is often used to dismiss user research – but that is a misunderstanding of its point.

Asking users “why”, and observing how they do things, is essential for user-centered design. Asking users what they want is unhelpful; it’s akin to asking for trouble.

Users are experts on their tasks, workflows, problems, and wishes. This is their area of expertise. They know where things are overly complex for them, where they struggle, where their workflow is broken. And they can even show it to you.

They might have suggestions on how to fix obstacles they encounter, or how to integrate their workarounds into existing solutions. But this feedback is based on their experiences and workflow. They address their own problems, which is fine. It’s not their job to understand or solve the larger issues. That’s your job.

Observing and talking to users helps you find problems and generate solution ideas. However, users can’t tell you what the overall solution should be.

Asking users for their ideal solution can seem like granting them a wish. They might expect it now to be built and be disappointed if it isn’t.

There is value in research – observe users’ behavior to identify their actual needs. Use it to come up with solutions. Ask them what they would like to change, not how. Don’t rely on your users to provide you with a solution.

Translating user feedback into a concept, is your area of expertise, and it’s a job you need to do yourself.

Research can only offer insights, not definitive solutions.

There is a common misconception about the role of research in the UX design community. People hope that research (the more the better) will solve their design problem.

However, research doesn’t provide direct answers to design problems, nor does it magically reveal a solution. Instead, research can only provide insights as “food for thought”.

The primary goal of research is to understand users’ mindsets, workflows, and challenges. You want to see what users do, understand why they do it, and get their feedback. These insights are the raw material for your ideation.

However, there’s a limit. At some point, further research won’t bring you closer to an answer. You might think: “I still have so many questions.” — this feeling is normal. Research cannot answer all your questions.

It is your job to collect and combine these insights and use them to come up with a viable solution. This involves analyzing data, brainstorming, formulating assumptions, and creating prototypes. Research cannot replace the ideation process. There will always be ambiguity when coming up with solutions — embrace it.

Research alone won’t hand you an answer on a silver platter. While it lays the groundwork for ideation, you have to come up with solution ideas on your own. To address unanswered questions, turn to ideation to explore possible solutions.

During ideation you will come up with solution ideas. Map them out, brainstorm, document your assumptions, create prototypes, and validate them. This iterative process helps in refining the solution. You need to actively “work towards” the solution.

While research provides the foundation for ideation work, it’s your job to find the right solution. Don’t try to outsource ideation work to research.

On my birthday in 2009, I bought myself one of the first IoT consumer devices – a cute electronic rabbit, called the Nabaztag.

It was brilliant – it could rotate its ears, read out messages, tell the weather and air quality forecast, play music, „sniff“ and recognize RFID tags, blink lights, and even act on voice commands. I consider the Nabaztag to be the great-grandfather of Alexa and Cortana.

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“If you don’t have people that care about usability on your project, your project is doomed.”

— Jeff Atwood

Occasionally you’ll encounter people that question the value of user experience design. My advice is: don’t try to convince them. And don’t be goaded into an ROI (return of investment) discussion of UX with „non-believers“.

Make the case for user experience design and for its contribution once, maybe twice, as people may be unfamiliar with it. But don’t you don’t want a repearing “why this is actually needed?” discussion.

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I recently stumbled over the Atari Portfolio. It is the first handheld computer, released in 1989. It runs a (compatible) version of DOS 2.11 and is sheer beauty!

I got one on eBay to play with it and soon realized that it’s mainly a pretty plastic brick as you have a hard time accessing it with modern computers.

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In 2003/04 I spent a year in the United States, working as a User Interface Designer for Siemens Medical. To document my stay I bought the smallest camera I could find. (Yes, this was before phones had cameras or were smart). I picked the Pentax Optio S4i.

The S4i was my first real camera.
It fits in the palm of my hand and I always carried it with me. It had glorious FOUR megapixels and it was shiny and perfect – but only until the S5i came out. The S5i had even FIVE megapixels and it allowed me to customize two buttons (instead of one). This was just too good. I bought the S5i and took some good pictures with her over the years.

Actually, I took my best picture with it.

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This is part of a larger series, you might want to consider reading parts one and two first.

As promised, I will now discuss the parts of the platform in more detail – starting with the server.

The main job of the server is to connect the prototype’s HTML and the ESP devices via MQTT and WebSockets. In the first iteration, I used Node.js​ and Express to write it, resulting in about 600 lines of code. But since I am a UX designer and not a developer it’s probably best when I don’t write (a lot of) code.
The source code felt a bit crude and overly complex to me. It was hard for someone with little coding experience to get how the server worked. And that made maintaining and changing it hard for regular folks.

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Here is the link to part one of this series, you might want to start there.

Based on the before stated principles and requirements for the prototyping platform I came up with the following architecture:

On the left, you see the web server where the HTML of the Prototyping tool will be stored. On the right, the different hardware components (sensors and actuators, e.g. buttons, rotary encoders, LEDs) are connected to ESP8266 microcontrollers. In broad terms, ESPs are similar to Arduinos but also offer WiFi connectivity for a low price. In between sits a server to broker and translate the information coming from both sides.

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This is the first article of a series (parts: two and three), as this topic needs some more space and time. I have about half of the content written, so I will post updates as I go along.

Even though the Internet of Things (IoT) is a hot topic, with today’s tools it is really hard to prototype and test IoT products or services beforehand. Very few tools allow us to use hardware components (like buttons or knobs) together with software user interfaces (UIs). Most software prototyping tools are closed systems offering no or only very little outside connectivity. Most of them only allow us to link screens together and that’s about it.

Plus, hardware prototyping is more complex than software prototyping: In addition to software interfaces, you need to know something about hardware, of course. Programming skills are needed if you want to tinker with them. And some knowledge about IoT protocols and platforms is helpful, too. These are skills very few user experience (UX) designers possess since a lot of them focus on the design of digital-only products and services. Just google the evergreen argument whether UX designers should be able to code.

Motivation

I thought that this was unfortunate since prototyping is such a crucial activity for creating successful products or services. We need to make your ideas tangible, test them with users and evaluate their feasibility before starting to build the real thing. And since I have some experience with software prototyping tools and tinkering with hardware I started looking for a way to create IoT prototypes.

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In the picture below you see my first love computer: the Schneider CPC 464. It had a built-in tape deck and was sold with either a green or a color monitor. It was never as popular as its rival, the C64, but that didn’t matter to me. I got the brownish monolith in ’85 as a Christmas present and 35 years later it still looks timeless, I think.

Sure, the screen is a bit small (size and resolution wise) for today’s standard, 64k RAM is not too great, and music tapes are not a popular storage medium anymore – but it can still play the game heroes of my childhood: Elite, Gauntlet, and Saboteur.
That’s why I decided a while ago to re-buy my first computer since I sold mine in my late teens to get money for a newer one.

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