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The Complexity Curve: How to Design for Simplicity (SXSW, March 2012)

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The Complexity Curve: How to Design for Simplicity (SXSW, March 2012)

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Interfaces and devices are providing more and more power and functionality to people, and in many cases this additional power is accompanied by increasing complexity. Although people have more experience and are more sophisticated, it still takes time to learn new interfaces, information, and interactions. Although we are able to learn and use these often difficult interfaces, we increasingly seek and appreciate simplicity.

The Complexity Curve describes how a project moves from boundless opportunity and wonderful ideas to requirements checklists and constraints then finally (but only rarely) to simplicity and elegance. Where many projects call themselves complete when the necessary features have been included, few push forward and strive to deliver the pleasing and delightful experiences that arise from simplicity, focus, and purpose.

David M. Hogue, Ph.D. - VP of Experience Design, applied psychologist, and adjunct faculty member at San Francisco State University - introduces the Complexity Curve, discuss why our innovative ideas seem to fade over the course of a project, explain why "feature complete" is not the same as "optimal experience", and offer some methods for driving projects toward simplicity and elegance.

Comments on twitter at #SXsimplerUX

Audio available at:

http://schedule.sxsw.com/2012/events/event_IAP13657

Interfaces and devices are providing more and more power and functionality to people, and in many cases this additional power is accompanied by increasing complexity. Although people have more experience and are more sophisticated, it still takes time to learn new interfaces, information, and interactions. Although we are able to learn and use these often difficult interfaces, we increasingly seek and appreciate simplicity.

The Complexity Curve describes how a project moves from boundless opportunity and wonderful ideas to requirements checklists and constraints then finally (but only rarely) to simplicity and elegance. Where many projects call themselves complete when the necessary features have been included, few push forward and strive to deliver the pleasing and delightful experiences that arise from simplicity, focus, and purpose.

David M. Hogue, Ph.D. - VP of Experience Design, applied psychologist, and adjunct faculty member at San Francisco State University - introduces the Complexity Curve, discuss why our innovative ideas seem to fade over the course of a project, explain why "feature complete" is not the same as "optimal experience", and offer some methods for driving projects toward simplicity and elegance.

Comments on twitter at #SXsimplerUX

Audio available at:

http://schedule.sxsw.com/2012/events/event_IAP13657

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The Complexity Curve: How to Design for Simplicity (SXSW, March 2012)

  1. COMPLEXITY simplicity
  2. The Complexity Curve Designing for Simplicity @DaveHogue #SXsimplerUX
  3. Welcome David M. Hogue, Ph.D. VP XD at Fluid San Francisco
  4. Complexity is easy. We can make anything complex.
  5. Even our wristwatches.
  6. Simple to read, difficult to set.
  7. Not much has changed…
  8. Daylight Saving Time Starts tonight at 2:00 am. Do you know how to set your watch?
  9. To make something simpler, we first need to define complexity, which is, ironically, not simple.
  10. What is complexity?
  11. complexus entwined; twisted together (Latin)
  12. “… I know it when I see it …” Supreme Court Justice Potter Stewart (Jacobellis v. Ohio, 1964)
  13. Three perspectives: Designers People (Users) Scientists
  14. Designers Appearance Aesthetics Style
  15. Space
  16. Noise
  17. Hierarchy http://blog.typekit.com/2011/03/17/type-study-typographic-hierarchy/
  18. Designers Functionality Context Flow
  19. Interactivity
  20. Dark Pattern?
  21. What is the goal?
  22. Structure
  23. Flow
  24. People Relevance Difficulty Clarity
  25. Clutter http://www.uie.com/brainsparks/2011/11/04/clutter/
  26. Difficulty
  27. Confusion
  28. Scientists Chaos
  29. Weather
  30. Edward Lorenz, Sc.D. dt/dx = σ(y−x) dt/dy = x(τ−z)−y dt/dz = xy− βz
  31. Lorenz Attractor
  32. Chaos Dynamical systems Deterministic Not predictable
  33. Chaos Self-organizing Emergent structure Sensitivity to perturbation
  34. Butterfly Effect
  35. Some things are naturally complex. So why discuss chaos?
  36. Complex systems that appear to have an impossibly large number of variables can actually be described and understood with remarkably few.
  37. The Complexity Curve In which the level of complexity increases the further we get into a design project.
  38. Complexity Curve
  39. Complexity Curve
  40. Where does complexity come from?
  41. Let’s skip the obvious: Disregard for design www.webpagesthatsuck.com 790 Flickr groups with “bad design” in the name
  42. Designers Models Patterns Scope Creep Constraints & Requirements
  43. Expectations v. Reality Mental Conceptual System Model Model Model (user) (interface) (device)
  44. Mental Model Mismatch Impedes progress Interrupts focus Incorrect direction
  45. Designers Models Patterns Scope Creep Constraints & Requirements
  46. Copying Patterns
  47. Anti-Patterns
  48. Dark Patterns
  49. New and different
  50. Designers Models Patterns Scope Creep Constraints & Requirements
  51. Scope Creep (Jog or Run) Forgotten features Absent stakeholders Vendor systems
  52. Executive Bungee-Jumping
  53. Designers Models Patterns Scope Creep Constraints & Requirements
  54. Constraints & Requirements Technical constraints Legal requirements Business unit requirements
  55. System Model Exposure Where is the current price per share? Why can't I buy a certain total value?
  56. People Difficulty Expertise
  57. Do not conflate complexity with difficulty. Difficult tasks often appear complex only until we have learned the necessary knowledge and skills.
  58. High cognitive loads feel difficult. Understanding and memory Problem-solving and decision-making Associations and connections
  59. People Difficulty Expertise
  60. Developing Expertise Declarative Procedural Automaticity Knowledge Knowledge (Habits)
  61. Novices & Experts
  62. Technology Limitations
  63. Limitations Materials Manufacturing Technological capability
  64. Inexorably Forward
  65. What can be done about complexity?
  66. Not everything should be simple.
  67. Law of Parsimony All things being equal, simpler solutions are generally better than complex ones.
  68. The Complexity Curve In which the level of complexity may be decreased if we continue to iterate and refine the design.
  69. Complexity Curve
  70. Complexity Curve
  71. Technology Advances
  72. Materials and Manufacturing
  73. Patience
  74. Forward Forces
  75. People Motivation Transfer Support
  76. A sufficiently motivated person will tolerate: Complexity Difficulty Confusion
  77. Sometimes we need to teach people, because we cannot make it any simpler.
  78. Transfer of knowledge and skills Instruction Demonstration Analogy
  79. Design Leverage our ignorance Place people first Use mental models Focus & Reduce Iterate
  80. Leverage our ignorance. Often our best ideas arise before we have become shackled by constraints. Write them down before we know why we can’t do them. Then return to them.
  81. Put people first. Motivation Behavior Emotion Creativity
  82. Use mental models. Match conceptual and mental models Hide system models
  83. Mental models evolve
  84. Conceptual models evolve
  85. Focus Reduce Attention Effort Flow Time Errors
  86. However, Simplicity is not just about reduction. Do not confuse subtraction with simplification.
  87. “Make everything as simple as possible, but not simpler.”
  88. Complexity moves.
  89. Shift the complexity…
  90. …away from the person.
  91. Law of Conservation of Complexity
  92. Feature complete is not experience optimized.
  93. Iteration Incubation Cross-pollination Observation
  94. New solutions…
  95. …emerge.
  96. None of these solutions, advances, and innovations could have been possible without...
  97. Critical Thinking A persistent effort to examine any belief, idea, or fact in terms of the available evidence.
  98. We know that designers: Ask questions Gather information Identify problems Generate ideas Evaluate options Communicate solutions
  99. Critical thinkers go further: Ask questions Gather information Identify problems Recognize assumptions Assess relationships Generate ideas Evaluate options Consider consequences Communicate solutions
  100. Designing for simplicity is not about Checklists Formulas Patterns Rules
  101. It is about Thinking and reasoning Understanding the problem Analyzing and optimizing
  102. So, how do we make stuff simpler?
  103. Ten Opportunities to Simplify
  104. “Messy & Confusing” Irrelevance Disorganization Ambiguity
  105. Indirect Action Abstracted Disconnected Increased cognitive load
  106. Everything to Everyone Too many variables Too little focus
  107. Design by Consensus Scope creep (or worse…)
  108. “Nice to have…” Noise Clutter Excess
  109. Copying Solutions Misapplied patterns
  110. Map Structure to Organization or Technology Exposes the system model
  111. Leading with Technology Solving the wrong (or non-existent) problems
  112. A solution looking for a problem?
  113. Or a tremendous opportunity?
  114. Designing for Yourself Ignoring the person’s mental models
  115. Accepting Assumptions Not collecting data Absence of critical thinking
  116. It may be complex if… “Messy & Confusing” Copying Solutions Indirect Action Map to Organization Everything to Everyone Lead with Technology Design by Consensus Design for Yourself “Nice to Have…” Accept Assumptions
  117. Thanks! David M. Hogue, Ph.D. VP XD at Fluid San Francisco
  118. The Complexity Curve Designing for Simplicity
  119. Credits

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