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Summary
In tech culture, everyone is hell-bent on coming up with answers and solutions. We all assume we know what the person’s problem is; rarely does tech culture start at the very beginning, understanding the variety of approaches real people have to their real purposes and different moods and contexts. Instead, we build an idea into experiments to see if it solves the imagined “problem.” Sound familiar? We can’t go on solving things based on our own thin understanding of how others perceive the problem. We can’t go on assuming everyone is in the same mood and context. There is no one-size-fits-all solution. Indeed, we have done a lot of accidental harm in the world with the assumption that the tools we design are “neutral.” We need to get better at paying attention. We need to slow down and gather a richer, more nutritious understanding of the people we are trying to support. And we need to point a beam of light into possible future outcomes. Let’s put equal emphasis on the problem. Spending equal time in the problem space generates rich understanding. Understanding the depths, perspectives, horizons and histories of the way people achieve their purposes opens up loads more opportunities. We can begin making solutions that eschew “engagement” to truly support different people in different ways. The problem space deserves more attention and a slow cycle all of its own.
Key Insights
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Technology culture glorifies solutions but undervalues knowledge creation through deep research.
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Correlation from big data should never be mistaken for causation without deeper qualitative understanding.
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Demographic segments like age and gender often fail to explain user behaviors; thinking styles based on purpose provide richer insights.
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Problem space research focuses on understanding people's purposes, not just their interaction with a product or organization.
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Mental model diagrams and thinking styles enable gap analysis and strategic opportunity identification.
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Empathy in design is a skill, best developed through deep cognitive empathy rather than surface-level emotional contagion or simplistic feeling.
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"Research theater" refers to superficial data analysis aimed at influencing stakeholders without real insight.
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Mature disciplines like architecture and museum design pay better attention to human purposes compared to technology.
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Listening sessions, unlike typical interviews, prioritize deeply understanding users’ inner thinking and guiding principles.
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Integrating problem space research with methods like Jobs to Be Done enhances strategic decision making, though Jobs to Be Done alone is insufficient for design.
Notable Quotes
"We live in a solution culture where we glorify people who can come up with solutions but not the people creating knowledge."
"Correlation is not causation and many in technology don’t understand that big data correlations alone don’t prove causality."
"You can’t explain why women check their bags just by demographics; you need to understand their purposes and contexts."
"Research theater is results designed to create reactions rather than deep understanding."
"Technology often puts the organization’s logic on the outside and forces users to think like the organization, not themselves."
"Empathy is not an emotion or sensitivity; it is a skill you have to develop."
"Cognitive empathy means consciously understanding other people’s perspectives from their own inner voice."
"Most teams build empathy on imaginary personas instead of real, deeply researched thinking styles."
"We need to grab the reins and push back when stakeholders misunderstand what valid research is."
"Deep problem space research creates data that could last decades and support multiple future projects."
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