Tag: social innovation

behaviour changecomplexitypublic healthsocial innovation

Confusing change-making with actual change

658beggar_KeepCoinsChange

Change-making is the process of transformation and not to be confused with the transformed outcome that results from such a process. We confuse the two at our peril.

“We are changing the world” is a rallying cry from many individuals and organizations working in social innovation and entrepreneurship which is both a truth and untruth at the same time. Saying you’re changing the world is far easier than actually doing it. One is dramatic — the kind that make for great reality TV as we’ll discuss — and the other is rather dull, plodding and incremental. But it may be the latter that really wins the day.

Organizations like Ashoka (and others) promote themselves as a change-maker organization authoring blogs titled “everything you need to know about change-making”. That kind of language, while attractive and potentially inspiring to diverse audiences, points to a mindset that views social change in relatively simple, linear terms. This line of thinking suggests change is about having the right knowledge and the right plan and the ability to pull it together and execute.

This is a mindset that highlights great people and great acts supported by great plans and processes. I’m not here to dismiss the work that groups like Ashoka do, but to ask questions about whether the recipe approach is all that’s needed. Is it really that simple?

Lies like: “It’s calories in, calories out”

Too often social change is viewed with the same flawed perspective that weight loss is. Just stop eating so much food (and the right stuff) and exercise and you’ll be fine — calories in and out as the quote suggests — and you’re fine. The reality is, it isn’t that simple.

A heartbreaking and enlightening piece in the New York Times profiled the lives and struggles of past winners of the reality show The Biggest Loser (in parallel with a new study released on this group of people (PDF)) that showed that all but one of the contestants regained weight after the show as illustrated below:

BiggestLoser 2016-05-03 09.17.10

The original study, published in the journal Obesity, considers the role of metabolic adaptation that takes place with the authors suggesting that a person’s metabolism makes a proportional response to compensate for the wide fluctuations in weight to return contestants to their original pre-show weight.

Consider that during the show these contestants were constantly monitored, given world-class nutritional and exercise supports, had tens of thousands of people cheering them on and also had a cash prize to vie for. This was as good as it was going to get for anyone wanting to lose weight shy of surgical options (which have their own problems).

Besides being disheartening to everyone who is struggling with obesity, the paper illuminates the inner workings of our body and reveals it to be a complex adaptive system rather than the simple one that we commonly envision when embarking on a new diet or fitness regime. Might social change be the same?

We can do more and we often do

I’m fond of saying that we often do less than we think and more than we know.

That means we tend to expect that our intentions and efforts to make change produce the results that we seek directly and because of our involvement. In short, we treat social change as a straightforward process. While that is sometimes true, rare is it that programs aiming at social change coming close to achieving their stated systems goals (“changing the world”) or anything close to it.

This is likely the case for a number of reasons:

  • Funders often require clear goals and targets for programs in advance and fund based on promises to achieve these results;
  • These kind of results are also the ones that are attractive to outside audiences such as donors, partners, academics, and the public at large (X problem solved! Y number of people served! Z thousand actions taken!), but may not fully articulate the depth and context to which such actions produce real change;
  • Promising results to stakeholders and funders suggests that a program is operating in a simple or complicated system, rather than a complex one (which is rarely, if ever the case with social change);
  • Because program teams know these promised outcomes don’t fit with their system they cherry-pick the simplest measures that might be achievable, but may also be the least meaningful in terms of social change.
  • Programs will often further choose to emphasize those areas within the complex system that have embedded ordered (or simple) systems in them to show effect, rather than look at the bigger aims.

The process of change that comes from healthy change-making can be transformative for the change-maker themselves, yet not yield much in the way of tangible outcomes related to the initial charge. The reasons likely have to do with the compensatory behaviours of the system — akin to social metabolic adaptation — subduing the efforts we make and the initial gains we might experience.

Yet, we do more at the same time. Danny Cahill, one of the contestants profiled in the story for the New York Times, spoke about how the lesson learned from his post-show weight gain was that the original weight gain wasn’t his fault in the first place

“That shame that was on my shoulders went off”

What he’s doing is adapting his plan, his goals and working differently to rethink what he can do, what’s possible and what is yet to be discovered. This is the approach that we take when we use developmental evaluation; we adapt, evolve and re-design based on the evidence while continually exploring ways to get to where we want to go.

A marathon, not a sprint, in a laboratory

The Biggest Loser is a sprint: all of the change work compressed into a short period of time. It’s a lab experiment, but as we know what happens in a laboratory doesn’t always translate directly into the world outside its walls because the constraints have changed. As the show’s attending physician, Dr. Robert Huizenga, told the New York Times:

“Unfortunately, many contestants are unable to find or afford adequate ongoing support with exercise doctors, psychologists, sleep specialists, and trainers — and that’s something we all need to work hard to change”

This quote illustrates the fallacy of real-world change initiatives and exposes some of the problems we see with many of the organizations who claim to have the knowledge about how to change the world. Have these organizations or funders gone back to see what they’ve done or what’s left after all the initial funding and resources were pulled? This is not just a public, private or non-profit problem: it’s everywhere.

I have a colleague who spent much time working with someone who “was hired to clean up the messes that [large, internationally recognized social change & design firm] left behind” because the original, press-grabbing solution actually failed in the long run. And the failure wasn’t in the lack of success, but the lack of learning because that firm and the funders were off to another project. Without building local capacity for change and a sustained, long-term marathon mindset (vs. the sprint) we are setting ourselves up for failure. Without that mindset, lack of success may truly be a failure because there is no capacity to learn and act based on that learning. Otherwise, the learning is just a part of an experimental approach consistent with an innovation laboratory. The latter is a positive, the former, not so much.

Part of the laboratory approach to change is that labs — real research labs — focus on radical, expansive, long-term and persistent incrementalism. Now that might sound dull and unsexy (which is why few seem to follow it in the social innovation lab space), but it’s how change — big change — happens. The key is not in thinking small, but thinking long-term by linking small changes together persistently. To illustrate, consider the weight gain conundrum as posed by obesity researcher Dr. Michael Rosenbaum in speaking to the Times:

“We eat about 900,000 to a million calories a year, and burn them all except those annoying 3,000 to 5,000 calories that result in an average annual weight gain of about one to two pounds,” he said. “These very small differences between intake and output average out to only about 10 to 20 calories per day — less than one Starburst candy — but the cumulative consequences over time can be devastating.”

Building a marathon laboratory

Marathoners are guided by a strange combination of urgency, persistence and patience. When you run 26 miles (42 km) there’s no sprinting if you want to finish the same day you started. The urgency is what pushes runners to give just a little more at specific times to improve their standing and win. Persistence is the repetition of a small number of key things (simple rules in a complex system) that keep the gains coming and the adaptations consistent. Patience is knowing that there are few radical changes that will positively impact the race, just a lot of modifications and hard work over time.

Real laboratories seek to learn a lot, simply and consistently and apply the lessons from one experiment to the next to extend knowledge, confirm findings, and explore new territory.

Marathons aren’t as fun to watch as the 100m sprint in competitive athletics and lab work is far less sexy than the mythical ‘eureka’ moments of ‘discovery’ that get promoted, but that’s what changes the world. The key is to build organizations that support this. It means recognizing learning and that it comes from poor outcomes as well as positive ones. It encourages asking questions, being persistent and not resting on laurels. It also means avoiding getting drawn into being ‘sexy’ and ‘newsworthy’ and instead focusing on the small, but important things that make the news possible in the first place.

Doing that might not be as sweet as a Starburst candy, but it might avoid us having to eat it.

 

 

 

behaviour changecomplexitypsychologysocial innovationsocial systems

Decoding the change genome

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Would we invest in something if we had little hard data to suggest what we could expect to gain from that investment? This is often the case with social programs, yet its a domain that has resisted the kind of data-driven approaches to investment that we’ve seen in other sectors and one theory is that we can approach change in the same way we code the genome, but: is that a good idea?

Jason Saul is a maverick in social impact work and dresses the part: he’s wearing a suit. That’s not typically the uniform of those working in the social sector railing against the system, but that’s one of the many things that gets people talking about what he and his colleagues at Mission Measurement are trying to do. That mission is clear: bring the same detailed analysis of the factors involved in contributing to real impact from the known evidence that we would do to nearly any other area of investment.

The way to achieving this mission is to take the thinking behind the Music Genome Project, the algorithms that power the music service Pandora, and apply it to social impact. This is a big task and done by coding the known literature on social impact from across the vast spectrum of research from different disciplines, methods, theories and modeling techniques. A short video from Mission Measurement on this approach nicely outlines the thinking behind this way of looking at evaluation, measurement, and social impact.

Saul presented his vision for measurement and evaluation to a rapt audience in Toronto at the MaRS Discovery District on April 11th as part of their Global Leaders series en route to the Skoll World Forum ; this is a synopsis of what came from that presentation and it’s implications for social impact measurement.

(Re) Producing change

Saul began his presentation by pointing to an uncomfortable truth in social impact: We spread money around with good intention and little insight into actual change. He claims (no reference provided) that 2000 studies are published per day on behaviour change, yet there remains an absence of common metrics and measures within evaluation to detect change. One of the reasons is that social scientists, program leaders, and community advocates resist standardization making the claim that context matters too much to allow aggregation.

Saul isn’t denying that there is truth to the importance of context, but argues that it’s often used as an unreasonable barrier to leading evaluations with evidence. To this end, he’s right. For example, the data from psychology alone shows a poor track record of reproducibility, and thus offers much less to social change initiatives than is needed. As a professional evaluator and social scientist, I’m not often keen to being told how to do what I do, (but sometimes I benefit from it). That can be a barrier, but also it points to a problem: if the data shows how poorly it is replicated, then is following it a good idea in the first place? 

Are we doing things righter than we think or wronger than we know?

To this end, Saul is advocating a meta-evaluative perspective: linking together the studies from across the field by breaking down its components into something akin to a genome. By looking at the combination of components (the thinking goes) like we do in genetics we can start to see certain expressions of particular behaviour and related outcomes. If we knew these things in advance, we could potentially invest our energy and funds into programs that were much more likely to succeed. We also could rapidly scale and replicate programs that are successful by understanding the features that contribute to their fundamental design for change.

The epigenetic nature of change

Genetics is a complex thing. Even on matters where there is reasonably strong data connecting certain genetic traits to biological expression, there are few examples of genes as ‘destiny’as they are too often portrayed. In other words, it almost always depends on a number of things. In recent years the concept of epigenetics has risen in prominence to provide explanations of how genes get expressed and it has as much to do with what environmental conditions are present as it is the gene combinations themselves . McGill scientist Moshe Szyf and his colleagues pioneered research into how genes are suppressed, expressed and transformed through engagement with the natural world and thus helped create the field of epigenetics. Where we once thought genes were prescriptions for certain outcomes, we now know that it’s not that simple.

By approaching change as a genome, there is a risk that the metaphor can lead to false conclusions about the complexity of change. This is not to dismiss the valid arguments being made around poor data standardization, sharing, and research replication, but it calls into question how far the genome model can go with respect to social programs without breaking down. For evaluators looking at social impact, the opportunity is that we can systematically look at the factors that consistently produce change if we have appropriate comparisons. (That is a big if.)

Saul outlined many of the challenges that beset evaluation of social impact research including the ‘file-drawer effect’ and related publication bias, differences in measurement tools, and lack of (documented) fidelity of programs. Speaking on the matter in response to Saul’s presentation, Cathy Taylor from the Ontario Non-Profit Network, raised the challenge that comes when much of what is known about a program is not documented, but embodied in program staff and shared through exchanges.  The matter of tacit knowledge  and practice-based evidence is one that bedevils efforts to compare programs and many social programs are rich in context — people, places, things, interactions — that remain un-captured in any systematic way and it is that kind of data capture that is needed if we wish to understand the epigenetic nature of change.

Unlike Moshe Szyf and his fellow scientists working in labs, we can’t isolate, observe and track everything our participants do in the world in the service of – or support to – their programs, because they aren’t rats in a cage.

Systems thinking about change

One of the other criticisms of the model that Saul and his colleagues have developed is that it is rather reductionist in its expression. While there is ample consideration of contextual factors in his presentation of the model, the social impact genome is fundamentally based on reductionist approaches to understanding change. A reductionist approach to explaining social change has been derided by many working in social innovation and environmental science as outdated and inappropriate for understanding how change happens in complex social systems.

What is needed is synthesis and adaptation and a meta-model process, not a singular one.

Saul’s approach is not in opposition to this, but it does get a little foggy how the recombination of parts into wholes gets realized. This is where the practical implications of using the genome model start to break down. However, this isn’t a reason to give up on it, but an invitation to ask more questions and to start testing the model out more fulsomely. It’s also a call for systems scientists to get involved, just like they did with the human genome project, which has given us great understanding of what influences our genes have and stressed the importance of the environment and how we create or design healthy systems for humans and the living world.

At present, the genomic approach to change is largely theoretical backed with ongoing development and experiments but little outcome data. There is great promise that bigger and better data, better coding, and a systemic approach to looking at social investment will lead to better outcomes, but there is little actual data on whether this approach works, for whom, and under what conditions. That is to come. In the meantime, we are left with questions and opportunities.

Among the most salient of the opportunities is to use this to inspire greater questions about the comparability and coordination of data. Evaluations as ‘one-off’ bespoke products are not efficient…unless they are the only thing that we have available. Wise, responsible evaluators know when to borrow or adapt from others and when to create something unique. Regardless of what design and tools we use however, this calls for evaluators to share what they learn and for programs to build the evaluative thinking and reflective capacity within their organizations.

The future of evaluation is going to include this kind of thinking and modeling. Evaluators, social change leaders, grant makers and the public alike ignore this at their peril, which includes losing opportunities to make evaluation and social impact development more accountable, more dynamic and impactful.

Photo credit (main): Genome by Quinn Dombrowski used under Creative Commons License via Flickr. Thanks for sharing Quinn!

About the author: Cameron Norman is the Principal of Cense Research + Design and assists organizations and networks in supporting learning and innovation in human services through design, program evaluation, behavioural science and system thinking. He is based in Toronto, Canada.

complexitydesign thinkingpsychologysocial systemssystems thinking

Collective action, impact, intelligence & stupidity

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Collective impact is based largely on the concept that we can do more together than apart, which holds true under the assumption that we can coordinate, organize and execute as a unit. This assumption doesn’t always hold true and the implications for getting it wrong require serious attention. 

Anyone interested in social change knows that they can’t do it alone. Society, after all, is a collective endeavour — even if Margaret Thatcher suggested it didn’t exist.  Thatcherites aside, that is about where agreement ends. Social change is complex, fraught with disagreements, and challenging for even the most skilled organizer because of the multitude of perspectives and disparate spread of individuals, groups and organizations across the system.

Social media (and the Internet more widely) was seen as means of bridging these gaps, bringing people together and enabling them to organize and make social change. Wael Ghonim, one of the inspirational forces behind Egypt’s Arab Spring movement, believed this to be true, saying:

If you want to liberate society all you need is the Internet

But as he acknowledges now, he was wrong.

Ghonim’s beliefs were not illogical as he discusses in the Ted talk above. He espoused a belief about collective action that echoes what leadership consultant and author Ken Blanchard proclaims:

None of us is as smart as all of us

Blanchard’s quote is meant to illustrate the power of teams and working together; something that we can easily take for granted when we seek to do collective action. Yet, what’s often not discussed are the challenges that our new tools present for true systems change.

Complex (social) systems thrive on diversity, the interaction between ideas and the eventual coordination and synchrony between actions into energy. That requires some agreement, strategy and leadership before the change state becomes the new stable state (the changed state). Change comes from a coalescing of perspectives into some form of agreement that can be transformed into a design and then executed. It’s messy, unpredictable, imprecise, can take time and energy, but that is how social change happens. 

At least, that’s how it has happened. How it’s happening now is less clear thanks to social media and it’s near ubiquitous role in social movements worldwide.

Complicating complexity

The same principles underpinning complex social systems hasn’t changed, but what we’re seeing is that the psychology of change and the communications that takes place within those systems is. When one reviews or listens to the stories told about social change movements from history, what we see over and again is the power of stories.

Stories take time to tell them, are open to questions, and can get more powerful in their telling and retelling. They engage us and, because they take time, grant us time to reflect on their meaning and significant. It’s a reason why we see plays, read novels, watch full-length films, and spend time with friends out for coffee…although this all might be happening less and less.

Social media puts pressure on that attention, which is part of the change process. Social media’s short-burst communication styles — particularly with Tweets, Snapchat pictures, Instragram shots and Facebook posts — make it immensely portable and consumable, yet also highly problematic for longer narratives. The social media ‘stream’, something discussed here before, provides a format that tends to confirm our own beliefs and perspectives, not challenge them, by giving us what we want even if that’s not necessarily what we need for social change.

When we are challenged the anonymity, lack of social cues, immediacy, and reach of social media can make it too easy for our baser natures to override our thoughts and lash out. Whether its Wael Ghomim and Egypt’s Arab Spring or Hossein Derakhshan and Iranian citizen political movement or the implosion of the Occupy movement , the voices of constructive dissent and change can be overwhelmed by infighting and internal dissent, never allowing that constructive coalescing of perspective needed to focus change.

Collectively, we may be more likely to reflect one of the ‘demotivation’ posters from Despair instead of Ken Blanchard:

None of us is as dumb as all of us

Social media, the stream and the hive

Ethan Zuckerman of the MIT Media Lab has written extensively about the irony of the social insularity that comes with the freedom and power online social networks introduce as was explored in a previous post.

The strength of a collective impact approach is that it aims to codify and consolidate agreement, including the means for evaluating impact. To this end, it’s a powerful force for change if the change that is sought is of a sufficient value to society and that is where things get muddy. I’ve personally seen many grand collaboratives fall to irrelevancy because the only agreements that participants can come up with are broad plaudits or truisms that have little practical meaning.

Words like “impact”, “excellence”, “innovation” and “systems change” are relatively meaningless if not channeled into a vision that’s attainable through specific actions and activities. The specifics — the devil in the details — comes from discussion, debate, concession, negotiation and reflection, all traits that seem to be missing when issues are debated via social media.

What does this mean for collective impact?

If not this, then what?

This is not a critique of collective activity, because working together is very much like what Winston Churchill said about democracy and it’s failings still making it better than the alternatives. But it’s worth asking some serious questions and researching what collective impact means in practice and how to we engage it with the social tools that are now a part of working together (particularly at a distance). These questions require research and systemic inquiry.

Terms like social innovation laboratories or social labs are good examples of an idea that sounds great (and may very well be so), yet has remarkably little evidence behind it. Collective impact risks falling into the same trap if it is not rigorously, critically evaluated and that the evaluation outcomes are shared. This includes asking the designer’s and systems thinker’s question: are we solving the right problem in the first place? (Or are we addressing some broad, foggy ideal that has no utility in practice for those who seek to implement an initiative?)

Among the reasons brainstorming is problematic is that it fails to account for power and for the power of the first idea. Brainstorming favours those ideas that are put forward first with participants commonly reacting to those ideas, which immediately reduces the scope of vision. A far more effective method is having participants go off and generate ideas independently and then systematically introducing those to the group in a manner that emphasizes the idea, not the person who proposed it. Research suggests it needs to be well facilitated [PDF].

There may be an argument that we need better facilitation of ideas through social media or, perhaps as Wael Ghonim argues, a new approach to social media altogether. Regardless, we need to design the conversation spaces and actively engage in them lest we create a well-intentioned echo chamber that achieves collective nothing instead of collective impact.

Photo credit “All Power to the Collective” to Mike Benedetti used under Creative Commons licence via Flickr (original artist, Graffito)

behaviour changesocial systemssystems thinkingUncategorized

Systems thinking and collective impact

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When we seek change the temptation is looking for ‘the key’ component of a problem or situation that, if changed, is expected to lead to profound transformation. Too frequently these type of solutions fail not because the change to the component is poor, but that the thinking is not aligned to the system that contributes to the problem in the first place and thus, changing thinking is what’s actually the key not the designed solution. 

If you’re one of the millions of people who made a New Years resolution there is a very good chance that your resolve has already wavered if not been completely abandoned. Research shows that New Years resolutions simply don’t hold up. This is not because of lack of will or even lack of effort or thought, but because we often confuse changes in a part of the system (e.g., exercise and better diet) with changes in the system itself (overall better health and weight loss).

Travel might be the ultimate example of systems and change. For the scenario pictured above, having a better automobile does nothing to help navigate the streetscape. No amount of fuel efficiency, top speed, safety rating or performance tires are going to make an ounce of difference in traversing this space. The reason is that the transportation system is broken, not that the units within it are. Indeed, cars, bikes, rickshaws and foot all perform perfectly well in this environment as designed, yet are rendered disabled in this context, which was designed to facilitate, not hinder their use.

Collective impact, systems change?

The model of collective impact is one that recognizes the fallacies of assuming that organizations seeking transformative social change will do so on their own, independently through wise thought and action. Collective impact is a model that has been widely supported by organizations such as Tamarack as a means of building capacity for systems change, not just change in the system.

The concept of collective impact was first popularized by John Kania and Mark Kramer in an article in the Stanford Social Innovation Review. Collective impact is a specific set of strategies that align the following five qualities and brief summaries that follow:

  • Common agenda (are organizations striving for the same things?)
  • Shared measurement systems (are partners measuring the same things in the same ways to enable comparisons and combine data?)
  • Mutually reinforcing activities (are initiatives building on one another, syncing up, and coherent?)
  • Continuous communication (are partners ‘in the know’ about what is happening across the system as activities unfold? )
  • Backbone support organizations (is there an organization or more that provides coordinating support and infrastructure to maintain the whole enterprise?)

The concept of coordinated action toward a common goal supported by shared means of assessment and feedback and ongoing communication is an enormous step forward in organizing actors involved in social change initiatives.

What is often missing from the discussion of collective impact is systems thinking. That is, explicit discussion of the way systems operate and not just discussion of the system itself that is to be changed. To be clear, there are many ways of doing collective impact and I mention Tamarack because they are among the few organizations that bring systems thinking into their work on systems change and collective impact. But it’s important to note that this is an exception, not the rule when reviewing what’s out there on collective impact. Many organizations do not (or may not) realize that thinking about systems change is not the same as systems thinking.

It is quite possible that we could see collective impact produce a larger-scale version of the flaws we see in initiatives aimed at changing components of the system if systems thinking isn’t considered integral to how its implemented. No amount of communication or shared measurement will help if we don’t measure the right things.

Systems thinking about collective impact

Social change is not doing the same thing that works at one scale (e.g. a person, family or team) and simply doing a lot more of it in more places. There are corollaries to be sure, but it’s not a linear pathway. Just as scaling a challenge and the response to it up produces potential for benefits, it also can scale harmful (or limiting) effects if the problem is not well-defined.

With that, let me pose some questions and challenges for those engaging in collective impact to help advance our shared understanding that are rooted in systems thinking?

  • What is the problem that is aimed to be solved (and is it the real problem?) Have alternative viewpoints from a diversity of actors throughout the system been considered in light of their position within the system and the values, goals and aspirations of those seeking systems change?
  • One of the ways that this diversity of perspectives is gained is through systems mapping. Systems mapping can be done through many different methods with each producing different looks at the dynamics, structures and relationships within the system. But what is shared is that it visualizes these qualities in a manner that makes it accessible to (almost) everyone. It allows for participants in the process to ask questions like: “why is [x] located so close to [y]?” or “where is [z] in all of this?” These create the kind of discussions that allow assumptions to emerge about the dynamics of the system itself.
  • An important follow-up to this is tracking these issues and framing them as evaluation questions. This grounds some of the metrics and measures in the system itself, not just the activities that the participants in collective impact initiatives seek to perform. It can also recognize the limits of the organizations at the table and either better account for them or provide guidance on how to overcome them (e.g., recruit more or different partners).
  • Systems maps are not only useful at the beginning, but can be an evaluative tool in itself. Maps developed at the start of an initiative and at different time points can enable partners to see what has changed and potentially find out how by examining how the structures, relationships and inclusion or exclusion of certain parts of the system shift over time. It may not allow for explicit causal attribution, but it can help understand and document what changed and initiate collective sense making about how that might have happened.

This is just a sample.

If we consider the traffic problem posed at the start of this post, one might find that the system problem isn’t even one related to the street, but to the larger community. One may find that the distances or locations of places to work, worship, shop and play are misaligned or that there are times of days when certain activities bring people into the street or perhaps its related to temperature (too hot, too cold) and the absence of climate control systems that work. More importantly however, systems thinking may enable us to account for all of these at the same time and avoid us focusing on one or two problems, but the system as a whole avoiding what is known as “a fix that fails”.

 

 

complexityinnovationsocial innovation

The Ecology of Innovation: Part 2 – Language

Idea Factories or ecologies of innovation?

Idea Factories or ecologies of innovation?

Although Innovation is about producing value through doing something new or different than before, the concept is far from simple when applied in practice by individuals and institutions. This second in a series of articles on innovation ecology looks at the way we speak of innovation and how what we talk about new ideas and discovery shapes what we do about it. 

“Language can be a way of hiding your thoughts and preventing communication” – Abraham Maslow

Innovation is one of the few concepts that offers little benefit contemplated in the abstract. We innovate on specific things with an eye to application, maybe even scaling that idea broadly. Humans innovate because the status quo is no longer satisfying, is unacceptable or has changed so we strive to come up with new ways of doing things, novel processes and tools to make the current situation a preferred one.

Thus, we are designers seeking our client, customer and creation through innovation and we do this through our words and actions — our language. Indeed, if one agrees with Marty Neumeier‘s assertion that design is the discipline of innovation and Greg Van Alystne & Bob Logan’s definition of design as “creation for reproduction” then our language of innovation is critical to ensuring that we design products and services that have the potential to reproduce beyond an idea.

Language matters in innovation.

To illustrate, lets look at how language manifests itself in the communication of ideas using an example from public health. In a paper entitled Knowledge integration: Conceptualizing communications in cancer control systems I co-authored with my colleagues Allan Best and Bob Hiatt, we looked at the way language was used within a deep and broad field like cancer control in shaping communications. This was not merely an academic exercise, but served to illustrate the values, practices and structures that are put in place to support communicating concepts and serves to illustrate how innovations are communicated.

Innovation as product

What we found was that there are three generations of cancer communications defined by their language and the practices and policies that are manifested in or representative of that language. The first generation of terms were traced up to the 1990’s and were characterized by viewing knowledge as a product. Indeed, the term knowledge products can be traced back to this period. Other key characteristics of this period include:

  • The terminology used to describe communications included the terms diffusion, dissemination, knowledge transfer, and knowledge uptake.
  • Focus on the handoff between knowledge ‘producers’ and knowledge (or research) ‘users’. These two groups were distinct and separate from one another
  • The degree of use is a function of effective packaging and presentation presuming the content is of high quality.

The language of this first generation makes the assumption that the ideas are independent of the context in which they are to be used or where they were generated. The communication represented in this generation of models relies on expertise and recognition of this. But what happens when expertise is not recognized? Or where expertise isn’t even possible? This is a situation we are increasingly seeing as we face new, complex challenges that require mass collaboration and innovation, something the Drucker Forum suggests represents the end of expertise.

Innovation as a contextual process

From the early and mid-1990’s through to the present we’ve seen a major shift from viewing knowledge or innovation as a product to that of a dynamic process where expertise resides in multiple places and sources and networks are valued as much as institutions or individuals. Some of the characteristics of this generation are:

  • Knowledge and good ideas come from multiple sources, not just recognized experts or leaders
  • Social relationships media what is generated and how it is communicated (and to whom)
  • Innovation is highly context-dependent
  • The degree of use of ideas or knowledge is a function of having strong, effective relationships and processes.

What happens when the context is changing consistently? What happens when the networks are dynamic and often unknown?

Systems-embedded innovation

What the paper argues is that we are seeing a shift toward more systems-oriented approaches to communication and that is represented in the term knowledge integration. A systems-oriented model views the design of knowledge structures as an integral to the support of effective innovation by embedding the activities of innovation — learning, discovery, and communication — within systems like institutions, networks, cultures and policies. This model also recognizes the following:

  • Both explicit and implicit knowledge is recognized and must be made visible and woven into policy making and practice decisions
  • Relationships are mediated through a cycle of innovation and must be understood as a system
  • The degree of integration of policies, practices and processes within a system is what determines the degree of use of an idea or innovation.

The language of integration suggests there is some systems-level plan to take the diverse aspects within a set of activities and connect, coordinate and, to some degree, manage to ensure that knowledge is effectively used.

Talking innovation

What makes language such a critical key to understanding innovation ecologies is that the way in which we speak about something is an indication of what we believe about something and how we act. As the quote from psychologist Abraham Maslow suggests above, language can also be used to hide things.

One example of this is in the realm of social innovation, where ideas are meant to be generated through social means for social benefit. This process can be organized many different ways, but it is almost never exclusively top-down, expert-driven. Yet, when we look at the language used to discuss social innovation, we see terms like dissemination regularly used. Examples from research, practice and connecting the two to inform policy all illustrate that the language of one generation continues to be used as new ones dawn.  This is to be expected as the changes in language of one generation never fully supplants that of previous generations — at least not initially. Because of that, we need to be careful about what we say and how we say it to ensure that our intentions are reflected in our practice and our language. Without conscious awareness of what we say and what those words mean there is a risk that our quest to create true innovation ecosystems, ones where innovation is truly systems-embedded and knowledge is integrated we unwittingly create expectations and practices rooted in other models.

If we wish to walk the walk of innovation at a systems level, we need to talk the talk.

Tips and Tricks

Organizational mindfulness is a key quality and practice that embeds reflective practice and sensemaking into the organization. By cultivating practices that regularly check-in and examine the language and actions of an organization in reference to its goals, processes and outcomes. A recent article by Vogus and Sutcliffe (2012) (PDF) provides some guidance on how this can be understood.

Develop your sensemaking capacity by introducing space at regular meetings that bring together actors from different areas within an organization or network to introduce ideas, insights and observations and process what these mean with respect to what’s happened, what is happening and where its taking the group.

Some key references include: 

Best, A., Hiatt, R. A., & Norman, C. D. (2008). Knowledge integration: Conceptualizing communications in cancer control systems. Patient Education and Counseling, 71(3), 319–327. http://doi.org/10.1016/j.pec.2008.02.013

Best, A., Terpstra, J. L., Moor, G., Riley, B., Norman, C. D., & Glasgow, R. E. (2009). Building knowledge integration systems for evidence‐informed decisions. Journal of Health Organization and Management, 23(6), 627–641. http://doi.org/10.1108/14777260911001644

Vogus, T. J., & Sutcliffe, K. M. (2012). Organizational Mindfulness and Mindful Organizing: A Reconciliation and Path Forward. Academy of Management Learning & Education, 11(4), 722–735. http://doi.org/10.5465/amle.2011.0002C

Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the Process of Sensemaking. Organization Science, 16(4), 409–421. http://doi.org/10.1287/orsc.1050.0133

*** If you’re interested in applying these principles to your organization and want assistance in designing a process to support that activity, contact Cense Research + Design.

science & technologysocial innovationsocial systems

Social innovation, social inclusion

Inclusion means everyone

Social innovation is about bringing new ideas, products and services out into society with others for social benefit and improving the lives of our communities. While not every innovation will benefit everyone, there is a need to examine more deeply the question of who benefits(?) when we consider social innovation and that means taking some hard looks at who we are innovating for. 

On August 15th 2015 the New York Times ran a feature story titled Inside Amazon, which looked at the corporate culture inside one of the largest, most innovate retailers in the world. In the piece written by award-winning journalists Jodi Kantor and David Strietfeld, they interview more than 100 current and former employees of Amazon and find a culture that is fast-paced, exciting, dynamic, creative and sometimes cruel, relentless in its expectations of its employees, overwhelming and harsh. What was interesting is that many interviewees spoke in conflicting terms about working for the company which offered great compensation and a stimulating workplace with lots of opportunities to grow while simultaneously burning them out and challenging their sense of self in the process of delivering feedback that wasn’t always experienced as constructive.

Across the news aisle we find another example of innovation in the news. In the September issue of the Walrus Magazine, editor-in-chief Jonathan Kay returns to the front lines of reporting with a feature story called Uber v. Taxi (or The Truth about Uber on the cover), which takes a comparative examination of changing business models and culture around cars-for-hire comparing tech start-up Uber with the traditional taxi model. The piece involves Kay signing up to be an Uber driver and also completing the City of Toronto taxi school to get a first-hand look at both systems from the perspective of driver and passenger. In an interview on CBC Radio, Kay was asked about the differences between the two and commented on how Uber was working well for the young, the mobile and able-bodied whereas traditional taxis were left with the others, creating a gap in income and opportunity between the two services:

That’s where drivers make a ton of money. Uber is taking that. Taxis are being left with older people, people with special needs, people who require wheelchair access and the visually impaired. Those are the people who require special training and vehicles that taxi fleets can provide but that’s not a particularly profitable part of the trade. Those trips take a lot of time and effort and passenger care. There’s not enough money on the table left for the taxi drivers to make a living.

Innovating for whom?

What these two stories have in common is that it profiles the way innovation spaces can divide as much as unite. On the surface, we see two examples of ways in which new thinking, careful product design and marketing, and a focused attention on user experience can generate value for consumers. However, what they also illustrate is that what is perceived as value is largely contingent on whom it is being asked and that this perception is not a minority position. This is not a case of blacksmiths getting outraged at the dwindling market for horseshoes due to the automobile or manufacturers of picture tubes castigating people for buying digital televisions. This is a case of entire segments of the population being left out.

Both of these examples are based on age to illustrate a point of commonality.

In the case of Uber, its the young, urban professional who does well by its innovative model. It’s the person who has few things to carry, needs little assistance, and likes to travel to the popular places where there are many others like them, which creates an ideal marketplace. For taxis, they are being asked to go to out-of-the-way places (like doctors appointments), deliver people and their parcels (for people who aren’t highly mobile), and are bound by a set of rules that Uber is not to ensure that they assist those who need it in using their service. Uber gets the cream of the market, while taxis are left with what’s left and that is mostly older adults.

But what ‘older’ means is a matter of perspective as we see with Amazon. As the reporters explain, old age isn’t what it once was:

In interviews, 40-year-old men were convinced Amazon would replace them with 30-year-olds who could put in more hours, and 30-year-olds were sure that the company preferred to hire 20-somethings who would outwork them. After Max Shipley, a father of two young children, left this spring, he wondered if Amazon would “bring in college kids who have fewer commitments, who are single, who have more time to focus on work.” Mr. Shipley is 25.

Every innovation produces ‘winners’ and ‘losers’, but what is striking in both articles is that the ‘winners’ are a very narrow band of the population, young, urban professionals. A look across what we often gets heralded as innovation (pick up any issue of Fast Company magazine to see it) and you’ll see a world dominated by (mostly) young, (mostly) white, (mostly) male, (mostly) middle class, and (mostly) tech-driven innovations that come from places and cultures like Silicon Valley. Facebook, Apple, Google, Uber, AirBnB — they are all based in Silicon Valley.

How we design innovations and the cultures we create in that process can have enormous implications. Are we creating our own silicon valley for social innovation?

“Slamming the Door on Silicon Valley”

Jess Zimmerman, writing in The Guardian, remarked on how Silicon Valley’s culture is one of entitlement and male hegemony, pointing to work of women’s groups aimed at making the work culture in the valley more female-friendly. Even though Sheryl Sandberg’s Lean In is a product of that environment, it not of that environment. “The Valley” is an environment that fosters both Uber and Amazon (which is should be noted is based in Washington State and not Silicon Valley, but nonetheless is part of the same cultural milieu discussed here). That ethos is one that is characterized by cultures of hard work, long hours, dynamism and youth. As a result, a path dependence is created based on the design specifications proposed at the start and leads to products that are, no surprise, a reflection of their makers.

Facebook’s features of ‘extreme openness’ as evidenced by it’s settings that make it hard to keep things private and rules against using pseudonyms can be traced back to Mark Zuckerberg’s dorm room at Harvard and his personality and personal belief system about what social life is to be like. As a result, Zuckerberg’s design has influenced online interactions of more than one billion users worldwide and continues today.

So what does this have to do with social innovation? Consider the literature — wide in scope, thin in detail as it may be — on social innovation methods and tools from social labs to design thinking. What we might find is an incomplete list of items that looks something like this:

  1. Be bold, bring wild ideas to the table and lots of them to the table; no idea is a bad idea
  2. Co-create with others
  3. We live in a VUCA (Volitile, unpredictable, complex, ambiguous) world and need to work accordingly
  4. Flat organizational structures work best for innovation
  5. Innovation doesn’t happen during 9-5, it happens anytime
  6. Information technology will leverage creative innovation potential everywhere, anywhere: it always wins
  7. You have to ‘move fast and break stuff‘, including the rules

The list can go on.

While I have  belief in what is contained in this list, it’s a restrained belief. Each of these points (and there are many others) can be upended to illustrate how social innovation can exclude people, ideas, cultures and possibilities that are as harmful as helpful. As I’ve argued before, social innovation has embedded in it an ethic of social justice if it’s to truly be a true social innovation. This requires attention to the ‘winners’ and ‘losers’ of innovation in ways that go beyond a call to innovate and change, it means paying attention to the cultures we impose through the innovation process.

Do we place too much emphasis on disruption vs harmony?

Where is the role for contemplation in the speed to create new things?

Is there a place for an introvert in the innovation table?

While innovative ideas might not respect the 9-5 clock, many paycheques, office spaces, commuter schedules, daycares and employee benefits do, what does that mean for those who rely on this?

Are these values those of innovation or those of a particular type of innovation from a particular context?

The Trickle of Innovation Streams Through the Valley

If we are to adopt social innovation on a wide scale we need to create a culture of innovation that is more than just a new version of a trickle-down model. Indeed, as Geoff Mulgan from Nesta writes, innovation has the potential to be another ‘trickle down theory’ that rewards the most advantaged first and then eventually to others in some modest form, creating inequities.

Yes, we now know much more about how to cultivate buzzing creative industries, universities, knowledge intensive industries and so on. But we have almost nothing to say to around half of our population who face the prospect of bad jobs or no jobs, and look on with dismay and envy at the windfall gains accruing to the elite insiders.

Silicon Valley is currently the place of privilege in the innovation world. If you have the privilege of not needing add-ons to your taxi ride, require assistance or have to drive to a neighbourhood that’s off the beaten path or have to pay by cash, Uber is great. If you can work flex hours and long hours, are gregarious and extroverted, and aren’t temporally limited by the needs of a spouse or partner, children, a loved one who requires care, or pets (that can’t be brought to work for obvious reasons — and I’m thinking of you cat owners) then a place like Amazon is maybe for you.

When we use these spec’s as our models to design innovation more widely, including social innovation, we create systems that exclude as much as include and that might get us innovations, but not necessarily real social ones.

innovationpsychologysocial innovation

Social innovation, social justice and the emotional link between them

Justice

Social innovations are judged by their impact, but in the quest to assess what it does we can miss the way it does it and that is where justice and the emotional connections that justice deals with come into play. Unless we consider social justice a part of social innovation we are likely to exclude as much as we include the very people we need to help bring good ideas to light and promote true social change and development. 

Social innovation is most often characterized with emphasis on new ideas and products generated in social ways. The social part of social innovation is what distinguishes it from other forms that don’t require that same social engagement.

Social innovation has been defined in the following ways such as:

” a novel solution to a social problem that is more effective, efficient, sustainable, or just than existing solutions and for which the value created accrues primarily to society as a whole rather than private individuals.” – Phills, Deiglmeier, & Miller (2008)

Social Innovation Generation and Frances Westley describe social innovation as:

“Social innovation is an initiative, product, process or program that profoundly changes the basic routines, resource and authority flows or beliefs of any social system.”

And Geoff Mulgan, the CEO of Nesta in the UK provides perhaps the simplest of definitions:

“Social innovation is a new idea that meets social goals” — Geoff Mulgan (2013)

In all of these definitions the emphasis is on the new idea and the social environment in which that idea is cast. The first of these definitions above is the most detailed and includes mention of those new ideas being more just than those that are being replaced. Frances Westley’s definition speaks to authority flows and Mulgan’s addresses social goals. How social innovation addresses justice, authority flows and social goals is not suggested in these definitions. Indeed, a review of the literature and popular discourse on social innovation finds remarkably little mention of social justice.

Perhaps it is because there is an assumption that social innovation is a positive thing for society that justice is simply assumed to be part of the act. Yet, that is hardly the case in practice. While we may use terms like participatory, engagement, and co-creation in our discussion of social innovation, the manner in which society is part of the process and involved is not well-articulated or is described in vague terms such as “engage diversity”. What does that actually mean? And what does this mean for our connection to community?

The emotional connection

Part of the problem is that innovation gets defined in terms of the product produced and the methods of engagement used to produce that innovation. What doesn’t get discussed is the emotional connection to the innovation and the way that guides participation and engagement. That emotional connection is what sits at the seat of justice.

“Full membership in a community depends on certain feelings, and these feelings are easily starved. A community is a circle of respect, and respect is felt. When any of us don’t feel respected by the community, we withdraw”

Paul Woodruff’s book the Ajax Dilemma explores the matter of social justice and one can’t help but think of how we often neglect this important concept and the emotional way in which people connect to their community or are excluded from that community via social innovation.

Woodruff’s excellent book looks at the complex relationship between people, their community and the means that hold them together, which is justice. He maintains:

“The purpose of justice is to maintain the integrity of a community. It’s not merely what you decide that matters, but how you decide it, and how you communicate the decision”

For social innovation this means ensuring that our ideas are not only sound, but that we have generated them in a manner that promotes justice within the community and that we are clear in how we communicate the purpose and impact of our innovation to the world. This challenges the impression that good ideas are self-evident and that the ends justify the means even if they are well-intended and co-creative. This means that the innovation itself needs to fit and enhance the integrity of the community while simultaneously challenging it.

The communication imperative

The last part of Woodruff’s quote above is the piece that ties justice to making our innovations social. It’s not enough to engage others in our innovation efforts, its about communicating what we’re doing to those that are participating and those that are not at the same time. It means evaluating what we do and documenting what decisions we make along the way to ensure that we make our ideas and their implications transparent to others because, ultimately, an innovation that seeks to transform society is one that won’t always involve everyone, but it needs to consider them.

That consideration provides that emotional attachment between individuals and the ideas that we generate to serve the society in which those societies belong. In doing so we create these new ideas that preserve integrity while pushing the bounds of what communities are and the status quo that isn’t always serving the best interests of society. By communicating ourselves and our intentions and putting justice at the heart of what we do social innovators are more likely to do well and do good at the same time.

(For those interested in learning more about Paul Woodruff’s perspective the lecture below gives a sense of what justice means in general as he discusses what the Ajax dilemma really is).

Image credit: Scales of Justice – Frankfurt Version by Michael Coughlan, attribution to Blogtrepreneur. Thanks for sharing your work Michael.