Summary
Enterprises are increasingly complex. Workers are faced with more information, more tools, more demands, and research needs to keep up. The field of Systems Thinking can help researchers uncover the models behind this complexity. This talk covers practical techniques for illuminating how models are interconnected, where feedback loops exist, and how we might transform these complex systems to drive innovation. It highlights how we can understand these systems without losing sight of the workers themselves… their ideas, concerns, motivations, and needs. Marrying systems clarity with this human perspective is critical, and is something researchers are uniquely positioned to do.
Key Insights
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Systems thinking offers a essential lens to research complex products by revealing whole systems and their subsystems simultaneously.
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Effective research balances understanding detailed subsystems with maintaining a holistic system-level perspective to avoid 'blind men and the elephant' problem.
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Feedback loops—reinforcing and balancing—help explain dynamic behaviors in product ecosystems and user interactions.
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Bounded rationality causes users in different system roles to make reasonable decisions with limited visibility, often leading to systemic challenges.
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In Customer 360 Audiences, data engineers lack visibility into marketers' downstream needs, causing inefficiencies and user frustration.
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Intangible elements like emotions and user confidence significantly impact how users experience and perceive product subsystems.
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Redrawing system boundaries based on research insights can lead to pivotal product strategy shifts, as Salesforce experienced prioritizing foundational features.
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Mental models about data ownership and collaboration between roles shape communication and product adoption, requiring targeted enablement.
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Keeping system diagrams and research at appropriate abstraction levels helps communicate complexity without overwhelming stakeholders.
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Collaborative exploration of system boundaries with stakeholders ensures the research stays focused on core system elements and relevant opportunities.
Notable Quotes
"Systems Thinking can give us this new lens to think about research in the middle of complexity."
"If you dive too deep into the subsystems or the bits right away, then your understanding of the whole is going to be lacking."
"People make decisions with limited information, especially about more distant parts of the system."
"Marketers don’t try very interesting things when their confidence in data is low, which can create a downward spiraling reinforcing loop."
"Our big idea was big and they wanted it, but what they wanted way more was the foundational features."
"You drew the boundaries wrong, so we pivoted and re-drew the boundaries, and those foundational features became our marquee product launch."
"Data is like a black box. It’s owned by IT. I’m not allowed to know how it works, but I kind of resent that it introduces delays into my marketing processes."
"Drawing a boundary was the hardest part for me, like stopping drawing the systems."
"System diagrams are a nice level of abstraction over something that is really complicated underneath."
"If you can draw that picture and tell that story, it just makes it easier for everybody to talk about how it's really going to be used."
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