First Sketchnote – IDEO’s Tim Brown ‘A Call for Design Thinking’ via TEDTalks

Over the last few months I had two work projects to complete that involved Visual Thinking. While I love the concept of Visual Thinking – the creation of a succinct picture or road map out of something complex – the actual process was still foreign to me. I actually think visually, and work best when I’m hands on, but I’ve never actually combined the two together. This ties back in with my last post on ‘Re-Discovering Creativity‘ with how our education systems mold us to think and interpret information in a specific way.

The only way to get better at something is by doing – so I decided to jump in head first and take a shot at sketchnoting. I decided to go with Tim Brown ‘A Call for Design Thinking’ TEDTalk since Design Thinking is a topic I’m passionate about and have been researching for the past year. I figured the familiarization with the topic would make it easier to sketch out concepts or thoughts as they came to me.

Follow the Sketchnote along with the video.

Thought Process

The process I used was fairly straight forward. I put the title in top/middle of the page before I started the video, and then started my sketching in the top left corner. I wanted to try to keep it as visual as I could, but I realized that keywords would jump out at me, so I jotted those down as they came along. I also wanted to keep the right side open for any other topic that might spin off – which worked out well since Tim went into discussing Roger Martin’s Integrative Thinking process (side note: I really like Martin’s ‘Knowledge Funnel‘ process – simple to understand and it does a great job of explaining why we love simplicity).

Here is the finalized version of the note. I used Pilot G-2 07 pen’s in green, black, red and blue, on copy paper. I’ve noticed that some sketchnotes have too many pictures that you have no idea what is going on – while others just have a bunch of fancy fonts crammed in on a page. I wanted to meld the two a bit, while keeping a good amount of white space so it wasn’t too cluttered. I would have liked to have had some better visuals, but nothing was really jumping out at me. Hopefully I can work on that more over time.

If you’re interested in learning more about Tim Brown – check out his company IDEO, where he is CEO and president.


6 thoughts on “First Sketchnote – IDEO’s Tim Brown ‘A Call for Design Thinking’ via TEDTalks

  1. Thanks for the comment, and I definitely agree! I’m really inspired by your work on your blog and fassforward. What do you find to be some of the biggest obstacles to overcome in the sketchnote process?

  2. Great post! I like the term ‘design thinking’. Specifically what Tim Brown says about divergent and convergent thiinking struck me. Coincidently (if that exists), I just wrote two posts (See “In the middle of difficulty lies opportunity”: ***) about the topic last friday, based on a few scribbles I had made last year.

    I have a few comments and questioins on that particular model:
    – I agree that we often focus on the converging part of the ‘design thinking process’, you could call it the decision making side I guess. However, in some relatively creative professions (like mine: ‘human resources development’, ouch I hate that terminology) people tend to focus too much on the diverging part, and fail to put ideas into practice (I guess that would be converging).
    – I would call the diverging side ‘options creating’ instead of ‘choice creation’
    – In my view, the broadest part of the model (right between creating choices and making choices), could be called the ‘options optimum’, the moment where all the options are open. That can either be a great place to be (see Pink’s autonomy:, or a scary one (see Saleci’s anxiety: Would you agree with that link?
    – An investigation of the role of predictable versus unpredictable options might be interested in light of this model. The diverging effect is often limited to generating predictable options (still with me?), while there are also a lot of potentially valuable options out there that are harder to find. I guess serendipity (My definition: the talent to find valuable stuff that you were not looking for) would be interesting to add to the model (besides searching). See also link below. I’ve made a drawing to try to explain my point, will blog about it some day (See ***).
    – What comes before the diverging process of creating options? Sense-making? (See post “From sense-making to scenarios”: ***)

    *** The posts I linked to are scheduled to be published January 12th and 13th, but I think these links will work as a preview. I hope you don’t mind that I wrote such a long comment and refer to some posts on my blog?

  3. Thanks for the in-depth comment Dubito! Unfortunately the links to your new blogs wont work until you publish them, but I’ll be sure to check them out.

    I try to keep my posts under 500 words so I didn’t get a chance to get into it, but the thought process behind ‘design thinking’ is to not make incremental changes or rules of thumb to follow (heuristics), but to try to understand systems as a whole.

    An example given in Roger Martin’s ‘The Design of Business’ ( is how autism and genome researcher Stephen Scherer focused on the data that other scientists were discarding and throwing away – the outliers. Scherer called it the garbage can approach, and believed that the answers to difficult problems can be solved by data that doesn’t fit into existing frameworks. By focusing on what could be true, instead of what is true, you can create the understanding of a new heuristic.

    They call this the difference between Reliability and Validity. Reliability is getting a consistent result every time (you can replicate), where as Validity is getting the outcome you are looking for. This dart board example does a great job of illustrating it:

    I know that went off on a bit of a tangent, but here are some notes I took from Martin’s book that might help:

    “Deductive: Logic of what must be. Reason from general to specific. If all crows are black, and I see a brown bird, I can deductively declare that bird is not a crow.

    Inductive: Logic of what is operative. Reason from specific to general. If I study sales per square feet across a thousand stores, and find a pattern that suggest stores in small towns generate significantly higher sales per square foot than stores in cities, I can inductively declare that small towns are my most valuable market.

    Abductive: Logic of likeliest possible explanation. Does it’s best with information at hand, especially when it is incomplete. “logical leaps of the mind.” New ideas arose when a thinker observed data (or even a single data point) that didn’t fit with the existing model or models. The thinker sought to make sense of the observation by making what Peirce called an “inference to the best explanation.”

    p.s. – I dont mind the length or links back to your blog. The more exposure the better 🙂

  4. I like the reference to the garbage approach! Some time ago, I read a cool article on that called “Accept defeat: The neuroscience of screwing up” about Dunbar, who studies scientists ‘confirmation bias’ (if that’s the correct term). A quote:
    “The scientists had these elaborate theories about what was supposed to happen,” Dunbar says. “But the results kept contradicting their theories. It wasn’t uncommon for someone to spend a month on a project and then just discard all their data because the data didn’t make sense.” See: I always fantasize about starting a mirror image of a popular scientific journal, called “The journal of negative results”, celebrating the value of un-findings (garbage can stuff)… anyway..

    • Interesting article, thanks for the link! As a former scientist (physiologist), I definitely agree with the quote: “Dunbar came away from his in vivo studies with an unsettling insight: Science is a deeply frustrating pursuit.” Confirmation bias is the correct term for it, and it’s very common in science. Another thing I find interesting in science is the idea of ‘consensus’ .. doesn’t that go against everything that science is about? If we followed consensus, then we would still believe the world is flat, and the sun and universe revolve around us.

      Along the same lines, check out this article about bias in Scientific literature. Absolutely fascinating, and it explains why we hear conflicting news reports. Here are the two paragraphs that stand out the most to me:

      “[Dr. Ioannidis] and his team have shown, again and again, and in many different ways, that much of what biomedical researchers conclude in published studies—conclusions that doctors keep in mind when they prescribe antibiotics or blood-pressure medication, or when they advise us to consume more fiber or less meat, or when they recommend surgery for heart disease or back pain—is misleading, exaggerated, and often flat-out wrong. He charges that as much as 90 percent of the published medical information that doctors rely on is flawed. His work has been widely accepted by the medical community; it has been published in the field’s top journals, where it is heavily cited; and he is a big draw at conferences.”

      “He zoomed in on 49 of the most highly regarded research findings in medicine over the previous 13 years, as judged by the science community’s two standard measures: the papers had appeared in the journals most widely cited in research articles, and the 49 articles themselves were the most widely cited articles in these journals. These were articles that helped lead to the widespread popularity of treatments such as the use of hormone-replacement therapy for menopausal women, vitamin E to reduce the risk of heart disease, coronary stents to ward off heart attacks, and daily low-dose aspirin to control blood pressure and prevent heart attacks and strokes. Ioannidis was putting his contentions to the test not against run-of-the-mill research, or even merely well-accepted research, but against the absolute tip of the research pyramid. Of the 49 articles, 45 claimed to have uncovered effective interventions. Thirty-four of these claims had been retested, and 14 of these, or 41 percent, had been convincingly shown to be wrong or significantly exaggerated. If between a third and a half of the most acclaimed research in medicine was proving untrustworthy, the scope and impact of the problem were undeniable.”

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