How To Break Anything

Innovation + experience-minded design strategy. The pieces of a working model for understanding culture + change in an increasingly complex world.

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      1 Jun 2011

      Research that matters - observation, filtering, prototyping and iteration

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      Designers thrive when they have a working concept of what makes people tick, a context that allows them to shape their ideas by considering what people covet and use, and somewhere to focus all their creative energy. Research can provide the fuel for new ideas. To Ben's point, design research isn't a scientific endeavor aimed at finding truths. Our clients typically can't afford the large sample sets and extended time frames necessary for such a "scientific" process.

      And sometimes design teams don't have the patience to see the value in dragging out a study in an effort to make it scientifically or statistically significant. We're just not wired that way; we prefer to make and experiment and then analyze later. So what is research good for?

      1. Learning about people's behavior

      Behavior is fertile ground for design. Not just human behavior, but systems behavior: social, technical, environmental, political, and economic systems.

      2. Understanding and analyzing culture

      ...Culture is another important system when it comes to understanding design because it deals with the relationships we build between each other, our things, our routines, our view of the the world, and our beliefs. 

      3. Defining context

      Context includes the physical and virtual settings that behavior occurs in and that culture shapes and emerges from. Identifying touch points—the decisive moments where a customer and a business intersect—is an important part of defining context.

      4. Setting focus

      Ill-defined problems, short project schedules, and a lack of patience are common conditions in design, and these can often lead to poor solutions. Doing research demands being comfortable with ambiguity in the early stages of a project in order to attain eventual clarity.

      ...Even the legendary Charles Eames expressed a similar sentiment when asked about the boundaries of design. He responded, "What are the boundaries of problems?"

       

      Design research is not "a science" and is not necessarily "scientific." It gives designers and clients a much more nuanced understanding of the people for whom they design while providing knowledge that addresses some of the most fundamental questions we face throughout the process. What is the correct product or service to design? What characteristics should it have, and is it working as intended? "The research" won't necessarily provide cold hard answers. But it will generate some good and feasible ideas. 

      via designmind.frogdesign.com

      The above is taken from the longer full article The Art of Design Research (and Why It Matters). I think it's important to consider particularly while having the sentiment expressed by Faris in mind, in a piece called All Market Research Is Wrong. If you're interested in research both the above piece and Faris's thoughts are worth reading in full, because they both express the sentiment that research is of course valuable, but in a way that we often overlook.

      The phrase is "research is often used like a drunk uses a lamppost - not for illumination but for support." The idea at hand here requires a bit of long-term thinking - research that matters isn't the means to an end, rather it's a way to frame the beginning (#4 above). 

      Hence, the research that is important is often what takes place before and after you're actively researching. The first is something more like observation and filtering; the latter we call prototyping and iteration.  

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      13 Apr 2011

      Two kinds of intuition - evolutionary and multiplexed

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      Yesterday I was reflecting on Thad Starner's distinction between mutlitasking and multiplexing. It reminded me that not too long ago I made made the statement "most things worth thinking about are counter-intuitive, because human intuition is wrong about just about everything."

      To which my smart friend Alicia promptly replied that she strongly disagreed. Smart because it got me thinking that there are in fact at least two different kinds of intuition.

      There's a first kind of intuition that I was originally thinking about when making the statement - this is intuition based on biological and evolutionary process. This is the kind of intuition that is captured on my favorite page of all the internet, Wikipedia's list of human cognitive biases. This is a list commonly referred to as "all the ways that you could be completely wrong about everything."

      So, well-designed environments (both physical and cognitive) - the kind I mentioned are worth thinking about - are the types that recognize that humans are constrained by these limitations, as seemingly unnecessary their design elements may be. The Mother Bear Proverbial Wallet for example, shown below - it's seemingly counter-intuitive to build a product that is intentionally hard to use (the opening mechanism is wirelessly synced to your bank account - becoming more tense as your funds get lower). Though, like great architects might masterfully make use of physical limitations to create efficient physical space, great interaction designers use human cognitive limitations as design constraints for better behaviors. 

      Screen_shot_2011-04-13_at_9

      But there's also a second kind of intuition, the kind Alicia reminded me of -  which is more akin to muscle memory or something from the Gladwell-popularized idea of "10,000 hours." This kind of complex intuition is developed by way of individual microexperiences, over time, perhaps through Starner's notion of multiplexing. The kind of intuition that gets me wondering if perhaps much of the charge of long-term memory mechanisms can be characterized by the process of reconstructing neural pathways from disconnected to synergetic, when long-term experience and exposure shape them to do so. (sorry, that statement's a mouthful; see David Linden's The Accidental Mind for a nice primer on the biochemical basis of experience-based memory.)

      This kind of intuition is what makes a magician's slight of hand truly "magic" - magic is impressive not because there's some secret that could be divulged, rather it's because the magician has put in the hundreds of hours of work necessary to make 15 seconds of performance seamlessly invisible.  

      This is the kind of intuition that is behind the original charge of this blog: "how to break anything? observe everything" -  a statement about pattern recognition through broad and unrestricted exposure. 
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      17 Feb 2011

      from Forbes: Give Free Data-Points, Get Paid For Insights

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      Give Free Data-Points, Get Paid for Insights

      A great blog article interviewing the founder of PSFK reveals the new nature of information value-creation, and anyone in the business of information–professional services, publishers, media–should pay attention. The small team at PSFK navigates through an immense amount of information and data points at a voracious speed. Acting as a media platform, they freely share and broadcast the information they come across with the public. PSFK instead gets work and makes its money consulting on concept development and trends. Their value-added is not from the selection of information they broadcast, but from linking disparate data points, synthesizing patterns into insights.

      Why freely publish what you’re looking at? Shouldn’t keeping it secret give you more advantage?

      PSFK has embraced the new reality that information flows free, and the benefits gained from free broadcast outweigh the loss of potential revenue from taxing that information access. Consider why you use Twitter. What benefits come from freely tweeting and re-tweeting all those links? For one, you gain a following of people who begin to associate you as a credible source for a specific kind of information–sounds to me like the best kind of advertising you could hope for. Perhaps more importantly, you build conversations and relationships with a growing network of like-minded and equally amazing people. A network that will elevate the quality of information you consume by in turn sharing with you what they’re looking at. In this new insight economy, professional services are only as good as their information community. The traditional model of market research that ignores community immersion and commitment is dead. Give free data-points. Build your information community. Get paid for deeply nuanced insights.

      via blogs.forbes.com

      Thanks Forbes, couldn't have said it better. I often note that my value isn't from "knowing things first" or "predicting the future" but rather from pulling disparate ideas together in a manner that insightfully shapes the way people think about developing ideas.

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      14 Feb 2011

      from PSFK » Widen Your Interests To Become A Better Strategic Problem Solver

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      Edward Boches, Chief Innovation Officer at Mullen, has five great suggestions for creative strategists he recently shared at a class called ‘Curiosity for Strategists’ at the University of Oregon. Specifically, while exploring strategic thinking in advertising from a broader perspective, Boches says that a good strategic planner should be ready to dissect a great idea from the past to understand why it worked. He also suggests that creative strategists look beyond the advertising realm for inspiration and learn from experts in other fields.

      A few pieces of advice from Boches:

      Observe human from different angles

      This is the obvious one, so I don’t really need to talk about it.  But the one suggestion I will offer is this: it’s no longer only about relationships to brands and categories; it’s also about relationships to content, technology, media and most of all, community. So understand the latter as well as the former.  Then start with your customer and what she needs, not your brand and what it wants. Even when it comes to advertising.

      Find Unexpected Sources and Look Below The Surface

      Teachers are everywhere. Listen to Miles [Davis] and you learn much of what you need to know about collaboration:  a leader has to keep everything focused on the ultimate goal; learn to get out of the way; surround himself with young talent; let other people shine.  From Atul Gawande, the brilliant surgeon, you can re-think how you get people to change behavior, overcome old habits, and cast aside the blind deferral we sometimes bestow on a single “creative director” who may not always have the right answer.

      Edward Boches: “Five suggestions for creative strategists”

      via psfk.com

      //(the original remit inspiring the title of this blog was "How to break anything? Observe everything." [see: The more you know, the more patterns you recognize])//

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      17 Nov 2010

      on "The more you know, the more patterns you recognize"

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      What Dr. Borowitz finds most intriguing is the prospect of technology that works hand-in-hand in helping physicians with their most important cognitive task. “What doctors do when they make diagnoses is pattern recognition,” he explained. “And the more you know, the more patterns you recognize.”

      via bits.blogs.nytimes.com

      A simple line from an article on more data being available to physicians for diagnosis. It of course applies to a lot more than just medicine - it's a basic rule of understanding the world.

      I think the reason I originally started thinking of the notion of "how to break anything" is the idea that rules are just rules - and they are indeed meant to be broken. But not to be broken for breaking's sake - rules are made by people who know why they're made, and they're of course always made for a reason.

      But when you understand why rules exist - well, then you understand how to constructively break them. Breaking the rule has then added something to the world.

      This can apply to the mundane rules that guide daily behavior of course, but generally I apply this to the limitations we create to help understand complex behavior ('psychology,' 'sociology,' 'marketing,' etc.). It could be said that the one thing that all artists share in common is that they understand the rules of their particular world, and know how to best break them. 

      To bring it back to the above excerpt: the silly little line I would use when I first started writing here was something like "How to break anything? Observe everything."

      (Oh and of course the idea of pattern recognition is a cornerstone of what I do on my daily task of 'trends analysis.' For now, I'll let someone more brilliant than myself like Magnus Lundkvist go into depth on that if you'd like.)

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      4 Jul 2010

      Ideas in long-term pattern recognition and analysis

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      There's one particular and notable step in the path that has led me here to the world of analysis and pattern recognition that I always look back and kind of laugh at. Once upon a time I had a university class assignment centered around selecting & analyzing a "self-help" book. While browsing the bookstore I couldn't help but pick out Reading People: How to Understand People and Predict Their Behavior - Anytime, Anyplace, primarily because of it's absurdly ridiculous title. 

      As it turns out, the book is very much in the same camp as the "building layers and layers of understanding from thin slices of experience" idea from Malcom Gladwell's Blink. So it makes sense that a detailed analysis of the book and how it applies to pattern recognition has popped up on LessWrong.org, calling attention to the author's primary charge:
       
      If this book could deliver but one message, it would be that to read people effectively you must gather enough information about them to establish a consistent pattern. Without that pattern, your conclusions will be about as reliable as a tarot card reading.
       
      The author of the article relates the key points of the book to an earlier post of theirs, What is Bayesianism?. I've selected some highlights below that you might find helpful when thinking about identifying patterns; they are primarily written through the lens of observing individuals, but for the most part the ideas behind them apply to larger trends as well. 

      1. Start with the person's most striking traits, and as you gather more information see if his other traits are consistent or inconsistent.

      As computationally bounded agents, we can't simply take in all the available data at once: we have to start off some particularly striking traits and start building a picture from there. However, humans are notorious about anchoring too much (Anchoring and Adjustment), so we are reminded to actively seek disconfirmation to any initial theory we have.

      2. Consider each characteristic in light of the circumstances, not in isolation.

      The second core tenet in What is What is Bayesianism was "How we interpret any event, and the new information we get from anything, depends on information we already had."

      A Bayesian translation of this might read roughly as follows. "Suppose you told me simply that a young man wears a large hoop earring. You are asking me to suggest some personality trait that's causing him to wear them, but there is not enough evidence to locate a hypothesis. If we knew that the man is from a culture where most young men wear large earrings, we might know that conformists would be even more likely to wear earrings. If the number of conformists was sufficiently large, then a young man from that culture, chosen randomly on the basis of wearing earrings, might very likely be a conformist, simply because conformist earring-wearers make up such a large part of the earring-wearer population.

      3. Look for extremes. The importance of a trait or characteristic may be a matter of degree.

      4. Identify deviations from the pattern.

      5. Ask yourself if what you're seeing reflects a temporary state or a permanent quality.

      6. Distinguish between elective and nonelective traits [events]. Some things you control; other things control you.

      7. Give special attention to certain highly predictive traits.

      Full explanations at Applied Bayes' Theorem: Reading People
       
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      6 Jun 2010

      "The broader one's understanding of the human experience, the better design we will have."

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      Media_httpkitsunenoir_vigjt
      via kitsunenoir.com

      This reminds me of 2 things:

      1) Why I'm so big on exposure

      2) Why I have a problem with "firsts"

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      15 Apr 2010

      A list of sources, and some thoughts on the value of receiving a list of sources (vs 'curation')

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      One of the questions I often get (as well as anyone in the 'trends'/'curation'/inspiration scene) is typically expressed as: "where do you find your stuff??"
       
      Now and Next has put together a list of Best Sources For Trends And Futures Thinking. Below, I've attached an export of my RSS's .opml (not optimally organized, for the record). 
       
      These are great and likely helpful. I'll add one comment: I always tell people that if I were to give them a list of my feeds, it probably wouldn't deliver the same value that they might hope for. That is to say, if Tina of SwissMiss gave me a list of her feeds and bookmarks, it wouldn't transform me into SwissMiss, and I wouldn't be able to instantly recreate swiss-miss.com. 
       
      Her value, and the value of any 'curator,' is the sum total of a lifetime of cultivating interesting experiences. 
       
      This might even have something to do with the idea behind "how to break anything."

       

      Click here to download:
      google-reader-subscriptions.xml (50 KB)
      (download)
      Click here to download:
      google-reader-subscriptions.xml (50 KB)

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    • Contributors

      Kyle Cameron Studstill
    • Obox Design
  • How To Break Anything

    Hello friends and collaborators. I deal in innovation, working to build fantastic experiences enabled by the digital world. As part of this I track cultural change, primarily through observations guided by models and filters calibrated over years to sort out the cream.

    These pieces of thoughts here reflect concepts that are elements of those models: ecosystem thinking, long-term value, information filters, and pattern recognition.

    ("How to break anything" is an abstract notion that reflects my background in observation and analysis. Rules are meant to be broken, but only through understanding the rules - observing them with an empathetic eye - can they be broken constructively.

    So how to break anything? Observe everything.

    [You can't observe everything so how do you know what to observe? That's another project that I call Filter Theory - see the About link above.])

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