How the UI/UX designers’ meeting in Munich went: insights and talking points
Agile in UX, Chat GPT in UX Research, JTBD, User-Centric Innovation, and My Notes on Them.
On 25 May, I spent a day at the UI/UX designers’ meeting in Munich. It was nice to develop with some talented designers with whom I communicate on Twitter, make new acquaintances, listen to stories and exchange experiences and impressions of the reports.
I want to share my insights with you.
Who shared knowledge, concepts and stories?
The whole day was packed. It was filled with exciting and engaging presentations from guest speakers:
- Itamar Medeiros: Jobs to be done.
- Felix Kranert: User Centration Sparing Innovation.
- Hias Wrba: Agile in UX.
- Simone Damm: Chat GPT in UX-Research.
The concept of Jobs-to-be-Done
Itamar Medeiros introduced the concept of Jobs-to-be-Done (JTBD) as a typical “exchange” currency to facilitate strategy discussions between designers, business stakeholders and technologists.
JTBD is an approach to design that helps create only those products that the user wants and needs and are in demand.
I was interested to learn how using JTBD can help engage stakeholders and influence business decisions that contribute to product development.
Theses I wrote down:
- Using results creates focus and consistency. It puts the customer at the centre of everything you do.
- Results-based management gives teams autonomy, responsibility and freedom to find their way in the design.
- Results-based management is only as effective as the results themselves.
- Progress in creating value for customers will only occur when you focus on something other than the process of achieving results but on the outcome. You need to answer not “What right now can the team implement?” but rather, “What benefits the user?”
User Centration Sparing Innovation
Felix Krannert illustrated how companies could create innovative products and differentiate themselves in the market by understanding user needs and desires. What was memorable? The examples were taken from real life, not pulled out of thin air. After the presentation, I felt everyone could innovate and make users happier by using valuable products.
A few talking points:
- Customers will be delighted if products/applications/techniques are intuitive, user-friendly and self-explanatory.
- If the product is frustrating and complicated, customers will turn away and look for alternatives.
- Technology is evolving rapidly, with more and more features and increasing complexity. At the same time, human sensitivity has mostly stayed the same in recent decades. Our task is to use complex technology but make it as easy as possible for users to interact with it. Everything complex is scary; everything easy is attractive.
Agile in UX
Hias Wrba looked at the tensions that arise when combining Agile and human-centric design methodologies. He suggested solutions on a new level, addressing essential aspects such as:
- Integrating the Process
- (Re-)Mixing Methodologies
- Clarifying roles and responsibilities.
Chat GPT in UX-Research
Simone Damm’s presentation focused on how AI-based tools like ChatGPT can be used for user experience (UX) research. She shared practical examples and instructions on compensating for ChatGPT’s limitations with bright cues and additional tools to achieve quality and reliable results in UX research.
A few talking points:
- ChatGPT is a black box of data until 2021.
- ChatGPT does not provide expert information because it relies on general knowledge.
- ChatGPT is far from empathetic. It doesn’t operate on people’s feelings; it doesn’t see ulterior motives, and it doesn’t read between the lines.
- ChatGPT needs a situational context, which can lead to incorrect or irrelevant interpretations of user data.
- ChatGPT, as a probabilistic model, technically cannot conduct qualitative research to stimulate innovation.
- ChatGPT cannot provide any behavioural data or non-verbal communication. It learns from opinions. It knows what people say, not how they act.
I’ll also save the link to Simone’s post
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