Category: design thinking

design thinkingpsychologyscience & technologysocial mediasocial systems

Creating Sticky Networks

 

Networking is as big of a buzzword as you can find these days for good reasons: networks solve a lot of problems by connecting people together and leveraging the knowledge of many for social benefit (and sometimes not). Simply put: networks allow us to do more.

But more can also be a problem.

It is not just that there is a lot of information out there, which creates its own set of problems, its that there is also so much to DO with this information. With all of the data streaming at us from social networks like Twitter, Facebook, Google Buzz, LinkedIn, Ning, and the myriad other ways in which social media allows us to connect it is hard to stay on top of it all. Even with good filters, the wealth of information available on even very narrow topics can be remarkable. I find this creates a temptation to try and get to it all. How often have you heard people lament about not being able to catch up on all of their blogs, tweets, magazine articles and beyond — let alone your conversations with friends, colleagues and loved ones?

While sociologist Mark Granovetter’s concept of the ‘strength of weak ties’ has been promoted vigorously in the social sciences and business to justify the potential for social networking, the value of the concept has some clear limitations that often get dismissed in the hype. One of the risks is that the time and energy it takes to invest in social networks broadly can take you away from creating strong ties. Think of how we socialized a generation ago: we had a close set of friends and family and associates, a few pen and phone pals, and some who we saw at occasional events like family reunions and conferences. Now, we “see” them daily, maybe hourly. That creates a lot of encounters, but at a superficial level for the most part.

While this is good for some things, particularly like getting simple messages out quickly, it is a problem for dealing with complex information or messages with multiple layers and potential meanings. Those require a little depth of contact that many networking tools or “networking events” don’t encourage.For those kinds of complex problems, we need tighter bonds and more meaning-making opportunities in our networks.

Mario Luis Small from the University of Chicago has explored the role of social networks and how they benefit those with little social capital. His recent book, Unanticipated Gains: Orgins of network inequality in everyday life, looked in depth at how social capital could be grown with a community of low-income, New York City mothers:

Social capital theorists have shown that some people do better than others in part because they enjoy larger, more supportive, or otherwise more useful networks. But why do some people have better networks than others? Unanticipated Gains argues that the answer lies less in people’s deliberate “networking” than in the institutional conditions of the churches, colleges, firms, gyms, childcare centers, schools, and other organizations in which they happen to participate routinely. The book illustrates and develops this argument by exploring the experiences of New York City mothers whose children were enrolled in childcare centers.

Unanticipated Gains examines why scores of these mothers, after enrolling their children in centers, dramatically expanded both the size and usefulness of their personal networks, often in ways they did not expect. Whether, how, and how much the mothers’ networks were altered—and how useful these networks were—depended on the apparently trivial but remarkably consequential practices and regulations of the centers, from the structure of their PTOs, to the regularity of their fieldtrips to amusement parks and zoos, to their ostensibly innocuous rules regarding pick-up and drop-off times.

Relying on scores of in-depth interviews with mothers, quantitative data on both mothers and centers, and detailed case studies of other routine organizations (from beauty salons and bath houses to colleges and churches), Unanticiapted Gains shows that how much people gain from their connections depends substantially on institutional conditions they often do not control, and through everyday process they may not even be aware of. (Original post here)

Although Small was not intending to write about what makes a network ‘sticky’, to use Gabriel Szulanski‘s term, he winds up with a set of recommendations that do just that. Indeed, Small’s suggestions – create intimate, cooperative, active,  stable, yet flexible and adaptive networks — make networks sticky (and resilient) while mitigating the effects of creating widening gaps between the well-connected and capital-rich and the rest.

Small suggests that there are 7 ingredients that help dampen harmful, unintended consequences of networks:

1.      Create frequent opportunities for interaction;

2.      Ensure frequent and regular interactions between agents;

3.      Interactions must be long lasting and exist beyond simple, quick exchanges;

4.      Interactions are minimally competitive;

5.      Interactions are maximally cooperative;

6.      Intrinsic motivation consistent with that of the organizations or networks drive interactions and encourage engagement over time;

7.      Extrinsic motivators must also be present to support the maintenance of ties over time.

Perhaps it is time to consider employing some design thinking towards creating stickier, rather than bigger or broader networks.

For more reading on the phenomenon of “stickiness”, consider the following:

Szulanski, G. (2000). The Process of Knowledge Transfer: A Diachronic Analysis of Stickiness. Organizational Behavior and Human Decision Processes.

Szulanski, G. (2003). Sticky knowledge: Barriers to knowing in the firm. London: Sage.

Szulanski, G., & Jensen, R. (2004). Overcoming stickiness: An empirical investigation of the role of the template in the replication of organizational routines. Managerial and Decision Economics, 25(67), 347-363.

design thinkingeducation & learningpsychologyresearchscience & technology

Innovation and (Higher) Education

 

In my last post I wrote about the problems facing scientific discovery and how our system of research funding and support is stifling opportunities for young innovators. I’d like to expand on that by focusing on the larger system that this research is couched in, particularly the way in which education is tied to innovation.

Let’s start first with the term innovation. My description, as opposed to definition, looks like this:

Innovation sits at the intersection of discovery and application; it means doing something different to create value. If we take this as our defintion, it means that an innovator is someone who challenges orthodoxy or established ways of doing things and delivers value to others in the process of doing so.

Now let’s look at the term education. Looking at the various definitions, I actually like the one from Wikipedia which is:

Education or teaching in the broadest sense is any act or experience that has a formative effect on the mind, character or physical ability of an individual. In its technical sense education is the process by which society deliberately transmits its accumulated knowledge, skills and values from one generation to another.

Taken together, innovation and education look to fit well together. Both of these terms refer in some capacity to change and impact. It is not enough to be different for the sake of difference, it is change that produces value (innovation) and change that transforms the fundamental state of what was there before (education). This change could come from something genuinely new (discovery) or taking something we’ve learned before and apply it in a novel context. What is often forgotten is that novel context can be the mind of a young person learning something for the first time. It is easy to forget that math, history, art, geography, biology and all of these things are new to everyone at some point in their life and the degree of novelty is inversely proportional to experience. The more experience you have, the less things seem novel.

Experience is the accumulated influence of patterns of activity and information. We pull in data, transmute that into information, which combines to create knowledge and, with time and accumulation, leads to wisdom. Or so the thinking goes. Russell Ackoff, who I’ve mentioned here before in a couple of posts, adds understanding to this mix (via Bellinger, Castro & Mills). David Weinberger, writing in HBR, and author of the Cluetrain Manifesto and Everything is Miscellaneous, challenges this and questions whether this neat DIKW relationship taxonomy is really is as neat and clean as it seems. Weinberger’s challenge is not to Ackoff’s DIKW hierarchy per se, but rather the way in which the parts are put together to make the whole. Knowledge, for example, is the most problematic of the terms in this model:

The real problem isn’t the DIKW’s hijacking of the word “knowledge” but its implication that knowledge derives from filtering information. It doesn’t. We can learn some facts by combing through databases. We can see some true correlations by running sophisticated algorithms over massive amounts of information. All that’s good.

But knowledge is not a result merely of filtering or algorithms. It results from a far more complex process that is social, goal-driven, contextual, and culturally-bound. We get to knowledge — especially “actionable” knowledge — by having desires and curiosity, through plotting and play, by being wrong more often than right, by talking with others and forming social bonds, by applying methods and then backing away from them, by calculation and serendipity, by rationality and intuition, by institutional processes and social roles. Most important in this regard, where the decisions are tough and knowledge is hard to come by, knowledge is not determined by information, for it is the knowing process that first decides which information is relevant, and how it is to be used.

The real problem with the DIKW pyramid is that it’s a pyramid. The image that knowledge (much less wisdom) results from applying finer-grained filters at each level, paints the wrong picture. That view is natural to the Information Age which has been all about filtering noise, reducing the flow to what is clean, clear and manageable. Knowledge is more creative, messier, harder won, and far more discontinuous.

Knowledge generation is therefore social, challenging, process-oriented, prototyped and revised, and non-linear.

Now think of our universities and training institutions and know knowledge is generated and transmitted (using the term mentioned above) and what that looks like:

Students are graded individually, and absolutely. No value is placed on social interaction here, because then it is hard to assess what the individual learner “learned” if they did so working with others where the discrete contribution of each person can’t be parsed out. Think of how ridiculous the idea of letter grades are, which are only slightly more idiotic than number grades for any course that involves contextual subject matter (which is social sciences, humanities, business, most of medicine, some of engineering, lots of biology, quite a lot of architecture, design, ….)? A student gets a 79 and their grade is a B+, while a student with a grade one per cent higher gets an A-; a qualitatively different realm of feedback.

“Outcomes” trump process. By outcomes, these mean the #students who attended class, #lectures given, review of the syllabus and that’s about it. We evaluate courses using only the most banal indicators (did the course match the syllabus? did the professor show up? did the professor speak coherently?). The result is outcomes: what are the grades? Was there a normal distribution? (I am explicitly asked what percentage of my student grades are A’s when I submit my grading form, revealing both a horrid understanding of the university’s understanding of both learning and statistics. But this is not something unique, indeed it is pretty much standard across universities).

Courses are frequently lecture-based (one teacher, many students), which is also at odds with the social nature of learning (see Brown & Duguid’s book the Social Life of Information for more on the absurdity of this in practice). If we learn more from teaching than “being taught”, why are we not training students to be teacher-learners and giving them more opportunities to try things out and teach others what they learn?

Prototyping is discouraged. It saddens me that every year I get students who sit in my class with the sole purpose of getting an A. Doing anything risky, by its very nature, threatens the possibility of an A. Grades are meant to assess learning, but what they are doing is measuring performance to a standard derived without context to the learner. Thus, a student can get an A without learning much, and could get a D and learn more than they had in any course. Yet, it is the A that judges whether a student is deemed a success or not, whether they get scholarships and so on. A syllabus is designed to resist prototyping with its predictable week-to-week learning plan so there is little reason our students should come prepared for anything that deviates from this plan. So much for non-linear thinking.

Taken together, does this look like an environment that fosters innovation, or even education for that matter?

How then, do we create environments of learning, discovery and innovation when our system is designed precisely to discourage this?

behaviour changedesign thinkingenvironmenthealth promotionpublic health

Thinking: Why the Word Matters to Systems and Design

 

When I was applying for funding to do a post-doctoral fellowship I struggled with the term “systems thinking” as an identifier as I frankly thought it to be a rather silly term. After being awarded a CIHR post-doc in Systems Thinking and Knowledge Translation I still felt I ought to use another term — maybe complexity science or complex adaptive systems would be better — but thinking? It seemed rather unprofessional or scientific to me. But as I dove deeper into the science of systems and struggled to expand, re-learn or un-learn many of the ways I’d grown accustomed to approaching problems I found myself in admiration of the term. Indeed it was about a way of thinking about things, not just studying them.

The same can be said for design thinking, another term I’ve come to admire that I found equally goofy the first time I heard it. Yet, like systems thinking, the more I’ve embraced this school of thought the more potential it has. Design thinking is predicated on the not-so-obvious recognition that nearly everything we come into contact beyond our fellow humans and pets is designed. Whether it is the computer you use, the streets you walk on, the clothes you wear, or even the curriculum you follow in school, it is all designed. Therefore, if we want to make the world a healthier, more creative, innovative and just place approaching it through the lens of design thinking might be useful.

Indeed, this past week I attended a lecture by Henry Hong-Yiu Cheung from the design firm IDEO who spoke on his application of design thinking to his work and the concept of designing systems at scale. As the concept name suggests, this is about fusing design with systems, although I would argue that the level of systems thinking IDEO applies is not matched to the level of design thinking. But then, they are a design firm first.

I’ve been spending much time imagining what our a health promotion and public health system would look like if driven by systems and design thinking? Larry Green has argued that systems science provides a means of facilitating practice-based evidence emergence alongside traditional evidence. Allan Best and others have posited that systems thinking can improve dissemination in health promotion and facilitate knowledge integration.

Building on the work of Green, Best and others, I’ve argued that health promotion is a systems science and practice, however few have said the same about design thinking. My colleague Andrea Yip and I are looking to change that by exploring ways in which design thinking can inform the way we approach public health and health promotion. If the fit isn’t obvious, consider how the design of the places you live, the products you use, and the communities you inhabit shapes your behaviour and choices. Architects have long known how to create spaces that attract people to them, keep them moving, or drive folks away. John Thackara notes that 80% of the environmental impact of any product is determined at the design stage and Andrea and I are interested in whether designing for health might enable us to better influence the impact of our communities, organizations and practices to improve health.

Our first challenge is to change the thinking behind how we approach the problem in the first place. And just like with systems, there is much education to be done to convince people why these twin styles of ‘thinking’ are worthy of consideration in social innovation, public health and health promotion.

behaviour changedesign thinkingeducation & learning

Amazing Stuff: December 14th Edition

It’s final paper and exam time at the university so that means one thing: procrastination.

Procrastination also yields a lot of unusual thinking so with a nod to the serious and the silly, I’ve managed to whittle down the many amazing things sent my way to just five:

1. 1000 Awesome Things. Rather than be amazing, this blog captures awesome. Although not so much the amazing like mind-blowing or novel, what this blog does is remind us of the little, everyday kind of things that happen in life that make us smile, pause, or even contemplate enough to go “wow, that’s awesome”. AWESOME!

2. The Art of the Idea: 8 ways to Light a Lightbulb Above Your Head. Fast Company’s Sheryl Sulistiawan presents a visual pictorial based on John Hunt’s insights collected in his new book. It is a creative, artistic way to imagine new ways to visualize the creative process. It’s a lot different than the usual pictogram and got me thinking.

3. Yes, Bottled Water Really is That Bad. Another gem from Fast Company and their infographics: A look at just how awful bottled water is for the world. Where I live (Canada) we have more clean, fresh water than almost anyone in the world yet we fill our buildings with bottled water when its cheaper, healthier, and sometimes tastier to drink it from the tap.

4. The New York Times Magazine 9th Annual Year in Ideas issue. I look forward to this every issue every year for a highlight of the most innovative — and sometimes also ridiculous — inventions, social trends, and novel solutions to problems big and small. I’m  quite intrigued by the growing interest in zombie attack science.

5. World Food Programme’s Fight Hunger campaign. When you think of innovators and integrated thinking, the UN isn’t the first place that comes to mind. But the UN’s WFP has shown that it can out-campaign even the slickest corporation with its multi-channel social media campaign using Facebook, Twitter, crowd-funding and micro-donations to stimulate awareness and solicit donations to affect a problem that is big and getting bigger everyday. A great ‘101’ on the program is available in this CNN International profile.

behaviour changecomplexitydesign thinkingeHealthpublic health

Benchmarking Success in Times of Change

 

Successful evaluators know the power of benchmark. The Oxford English Dictionary describes the act ‘to benchmark’ as “evaluate or check (something) by comparison with a standard. The Wikipedia definition of Benchmarking is:

Benchmarking is the process of comparing the business processes and performance metrics including cost, cycle time, productivity, or quality to another that is widely considered to be an industry standard benchmark or best practice. Essentially, benchmarking provides a snapshot of the performance of your business and helps you understand where you are in relation to a particular standard.”

From an evaluation standpoint, a benchmark provides us with a comparator to help assess how well (or poorly) a particular program is doing. From corporate leaders to university presidents to healthcare administrators benchmarking serves as the referent and focus for programming activities and the foundation for ‘best practice’. But what if best practice isn’t good enough? Or put another way, what if following the leader means going the wrong way?

In the world of consumer or behavioural eHealth much of what we use as our benchmarks are derived from a type of healthcare model that is institution and often technology-centred rather than patient-centred. It is more often something tied to medical treatment of specific problems and technology focused using a highly linear approach to treatment.

Yet in the age of Google Wave, these linear models don’t look to fare well. The future of healthcare, as Frog Design recently opined, is social. What are the benchmarks when your eHealth intervention is not a single technology, but a suite of interacting tools that are online, collaborative and mobile in different measures at different times within a diverse context of treatment and preventive behaviour? How do we measure success? What happens when the ‘effect’ of an intervention is social in nature and supported by multiple tools working in different combinations each time?

In evaluation, we often look for the most likely cause of a particular effect. Yet, what is the effect of any one wave in an ocean of influence? While it is impossible to deconstruct the influence of that wave, it is possible to anticipate what a wave might do under certain conditions and, if the timing is right, it might be possible to get on top of that wave and surf it to shore.

What if we took a wave model and, like surfers, read the seas to determine the appropriate time to dive in, acknowledging that the break will occur differently, the velocity might vary, the height of can’t be predicted, but through activity and practice we can enhance our anticipatory guidance systems to better select waves that might lead to some fine surfing? My research team at the University of Toronto has begun working on these models and methods because as anyone in public health can tell you, the tide is high and with complex problems like chronic disease, the waves are getting big. Twitter, Facebook, blogs, iPhone apps big and small are all collectively influencing people’s behaviour in subtle ways and through acknowledging that these collective tools are the cause and consequence of change can we begin to develop evaluation models to make sense of their impact on the world around us.

design thinkingeHealthfood systemsscience & technology

Amazing Stuff: November 14th Edition

It’s been another busy week filled with lots of ideas, but little time to post them. Expect a lot more on the blog in the coming weeks however as there is too much going on not to discuss.

Thankfully, the rest of the world was still Tweeting, blogging, You-tubing and sharing all kinds of amazing things with us and here are the top ones that captured my attention this week:

1. I love food from all kinds of sources and certainly those that come from animals are the ones I spend the most time thinking about. A new book by Jonathan Safran Foer looks at the ethics and industry of eating animals. I haven’t read the book, but a detailed and insightful review in the New Yorker suggests that I might be thinking a lot more about this in the days and weeks to come based on the arguments that Foer puts forth. Natalie Portman is one who also has thought differently because of this book — this time about vegetarianism and veganism — and she writes her review in the Huffington Post. Read any of the reviews and you’ll know that this is a book making buzz and adding to our already considerable array of options when considering the merits of what we choose to eat. Tofu anyone?

2. Keeping with the contrarian perspectives: have you thought about how healthcare might actually be unhealthy for the planet? This week Ariel Schwartz posted an interesting article in Mother Jones (and replicated in Fast Company ) questioning the carbon footprint of the healthcare industry and whether we ought to be working harder to consider how green our care facilities are. Could a sick planet be coming from healthy humans?

3. While we’re on health care, The New York Times published a story about text messaging for teens as a possible way to engage young people more in health care using mobile phones. Seems like a no-brainer to me, but will it fly in the face of most healthcare organizations, which are a little slow to adopt technologies like this into practice?

4. The international social innovation leadership group, Ashoka, announced the winners of this year’s sustainable food (GMO: risk or rescue?) contest. The blog biofortified was the grand winner. There are some novel ideas and certainly opportunities to expand the dialogue on food safety and security in some new ways through this initiative. GMO good or bad? The answer seems to be: yes.

5. Lastly, Mobifest is coming to Toronto and I was captivated by some of the novel and creative films on display as the finalists in this year’s competition. Mobile filmmaking is getting bigger, better and more creative all the time and I’d encourage anyone interested in looking at one of the futures of film to check this mini and mobile film fest out.

design thinkingenvironmentpublic healthscience & technologysocial media

Amazing Stuff: November 6th Edition

A year ago something that truly is amazing happened: Barack Obama was elected the 44th president of the United States. This week there were some far less amazing things that I found — but some amazing stuff no less.

1. Wired Science published some of the newly released photos of islands from space. It is a stunning collection of visual images of our planet from thousands of metres into space. They provide a remarkable perspective on our world.

2. Are you better off owning a dog or a Toyota Land Cruiser in terms of the planet’s health? According to a New Scientist article published this week (and commented on in Fast Company) owning a pet might be worse for the environment than a gas guzzling SUV. True? It’s not clear, but it does provoke some interesting discussion on what really influences carbon emissions and the health of our world.

3. Visualization of data is one of the ways in which we can make complex information accessible to more people. A newly published TED talk by JoAnn Kuchera-Morin provides a stunning representation of some of the ways in which visualization tools can aid our understanding of our planet and our brain.

4. The New York Times has a new innovation portfolio site. For those interested in new ideas and design, this is a must-visit on the tour through the Internet.

5. Amazing or not, H1N1 is causing a lot of distress around the world. This week, Fast Company (their second mention this week!) reviewed some of the ways in which people can get on top of tracking and preventing the disease using iPhone apps. Mobile public health has never been so interesting.