Designing Systems at Scale
Summary
This talk will cover about the common threads of these failures, how they can be detected and ultimately prevented using various research disciplines – from market research to anthropology to data science. We need to get good at designing and building for systems to tackle multi-dimensional problems at the intersection of people and technology.
Key Insights
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Judy Ellis taught that the key to good design is combining aesthetics, manufacturing knowledge, business understanding, and an appreciation of play.
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Successful processes must be transparent yet become invisible in their application to empower creativity and decision-making.
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Shopify divides work into product lines addressing audiences and service lines ensuring knowledge flow and organizational alignment.
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Data types fall into two complementary streams: object-oriented 'what' data and context-oriented 'where' data.
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The brain processes 'what' and 'where' data in different hippocampus areas before combining them for decision-making.
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Qualitative, context-rich data (the where stream) reaches decision centers earlier and is critical for effective decisions.
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Cross-disciplinary collaboration among UX researchers, data scientists, anthropologists, and market researchers maximizes insight quality.
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Knowledge distribution is best managed by shaping the environment and workflows rather than micromanaging the process itself.
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Leadership support and clear executive ownership are vital to sustaining centralized research and knowledge cycles.
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Tools like Shopify’s merchant frustrations database improve asset visibility and continuous improvement for customer-centric decisions.
Notable Quotes
"Toy design is not about the toy itself but a tool that unlocks unlimited possibilities before a child."
"Successful operations must have well laid out and transparent process documentation but that process must become invisible in its application."
"Service lines bridge gaps between product lines by facilitating knowledge flow and alignment."
"Our brains are terrible at operating on only one type of information—object-oriented or context-oriented."
"It’s the context-related data gathered through qualitative research that reaches our decision-making centers first."
"UX researchers at Shopify travel across product lines to share expertise and knowledge continuously."
"Knowledge creation, distribution, application, and evaluation form a reusable circular process, not a linear one."
"Leadership is really important—having an executive who understands the value of the knowledge cycle is key."
"Shopify’s merchant frustrations tool tracks customer issues over time, making that knowledge available to all teams."
"Properly maintained, knowledge becomes a vehicle that probes the most hidden spaces of what’s possible."
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