systems science Category
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:
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.
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.
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.
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.
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.
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.
Innovation might be doing things different to produce value, but there’s little value if we as a society are not able to embrace change because we’re hiding from mental illness either as individuals, organizations or communities. Without wellbeing and the space to acknowledge when we don’t have it any new product, idea or opportunity will be wasted, which is why mental health promotion is something that we all need to care about.
Today is Bell Let’s Talk Day in Canada. Its (probably) the most visible national day of mental health promotion in the world. The reason has much to do with the sponsor, Bell Canada, who happens to be one of the country’s major providers of wireless telecommunications, Internet, and television services in addition to owning many entertainment outlets like cable channels, sports teams and radio stations. But this is not about Bell**, but the issue behind Let’s Talk Day: ending mental health stigma.
Interestingly perhaps, the line from the film and novel Fight Club that is most remembered is also the one that is quite fitting for the topic of mental health (particularly given the story):
First rule of Fight Club: Don’t talk about Fight Club.
Mental health stigma is a vexing social problem because it’s about an issue that is so incredibly common and yet receives so little attention in the public discourse.
The Mental Health Commission of Canada‘s aggregation of the data provide a useful jumping off point:
- In any given year, one in five people in Canada experiences a mental health problem or illness bringing a cost to the economy of more than $50 billion;
- Up to 70 per cent of adults with a mental health problem report having had one in childhood;
- Mental health was the reason for nearly half of all disability-related claims by the Canadian public service in 2010, double what it was in 1990;
- Mental health problems and illnesses account for over $6 billion in lost productivity costs due to absenteeism and presenteeism;
- Among our First Nations, youth are 5-6 times more likely to die at their own hands than non-Aboriginal youth and for Inuit, the suicide rate is 11 times the national average;
- Improving a child’s mental health from moderate to high has been estimated to save society more than $140,000 over their lifetime;
And this is just Canada. Consider what it might look like where you live.
It seems preposterous that, with numbers this high and an issue so prevalent that it is not commonly spoken of, yet that is the case. Mental illness is still the great ‘secret’ in society and yet our mental wellbeing is critical to our success on this planet.
Like with many vexing problems, the place for change to start is by listening.
Mind over matter: Dr. Paul Antrobus
Last year one of the most incredible human beings I’ve ever — or will ever — meet passed away. Dr. Paul Antrobus was the man who introduced to me psychology and was the wisest person I’ve ever known. Paul was not only among the greatest psychologists who’ve ever lived (I say with no exaggeration) by means of his depth of knowledge of the field and his ability to practice it across cultures, but he was also someone who could embody what mental health was all about.
In 2005 Paul fell off the roof of his cottage and was left as a paraplegic, requiring ventilation to breathe. For nearly anyone this would have been devastating to their very being, yet for Paul he managed to retain his humour, compassion and intellect as well as sharp wit and engagement and put it on display soon after his accident. He demonstrated to me the power of the mind and consciousness over the body both in the classroom and, after the accident, in his wheelchair.
Paul lived a good life, by design. He surrounded himself with family and friends, built a career where he was challenged and stimulated and provided enough basics for life, and gave back to his community and to hundreds of students whom he mentored and taught. Much of this was threatened with the accident, yet he continued on, illustrating how much potential we have for healing. He learned by listening to his life what he needed and when he needed it, tried things out, evaluated, tinkered and persisted. In essence: he was a designer.
Paul would also be the first to say that healing is a product of many things — biology (like genes), personality, family upbringing, access to resources (human, financial, spiritual, intellectual), and community systems of support. He made the most of all of these and, partly because of his access to resources as part of being a professor of psychology, was able to cultivate positive and strong mental health while helping others do the same. Although he might not have used the term ‘designer’, that’s exactly what he was. One of the reasons was that he discovered how to listen to his life and that of others.
And because he was able to listen to others he recognized that nearly everyone had the potential for great health, but that such potential was always couched within systems that worked for or against people. Of all of the things that contribute to healing, a healing community had the potential to allow people to overcome nearly any problem associated with the other factors. Yet, it is the community — and their attitudes toward health (and mental health in particular) — that requires the greatest amount of change.
That’s why talking and listening is so important. It creates community.
Listening to your life
Paul wrote a book and taught a course on listening to one’s life. Part of that approach is also being able to share what your life is teaching you and listening to what your body and the world is telling you. For something like Bell Let’s Talk Day, a space is created to share — Tweet, text, post — stories of suffering, hope, recovery, support, love and questioning about mental health without fear. It’s a single day and part of a corporate-led campaign, but the size and scope of it make it far safer and ‘normal’ on this day than on almost any day I know of.
A couple of years ago a colleague disclosed to the world that she had struggled with depression via Twitter on Bell Let’s Talk Day. She was so taken by the chance to share something that, on any other day, would seem to be ‘oversharing’ or inappropriate or worse, that she opened up and, thankfully, many others listened.
Let’s Talk Day is about designing the conversation around mental health by creating the space for it to take place and allowing ideas and issues to emerge. This is the kind emergent conditions that systems change designers seek to create and if you want to see it in action, follow #BellLetsTalk online or find your own space to talk wherever you are and to listen and to design for one of the greatest social challenges of our time.
This post is not about innovation, but rather the very foundation in which innovation and discovery rests: our mental health and wellbeing. For without those, innovation is nothing.
Today, listen to your life and that of others and consider what design considerations are necessary to promote positive mental health and the creative conditions to excel and innovate.
As for some tips in speaking out and listening in, consider these five things to promote mental health where you are today:
- Language matters – pay attention to the words you use about mental illness.
- Educate yourself – learn, know and talk more, understand the signs of distress and mental illness.
- Be kind – small acts of kindness speak a lot.
- Listen and ask – sometimes it’s best to just listen.
- Talk about it – start a dialogue, break the silence
Thank you for listening.
** I have no affiliation with Bell or have any close friends or family who work for Bell (although they are my mobile phone provider, if that counts as a conflict of interest).
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”.
Planning is something that is done all the time, but the shape in which these plans unfold is often complex in hidden ways. Without the same resources to evaluate those plans (and make different ones should they change) many organizations are left with great expectations that don’t match the reality of what they do (and can do).
In my neighbourhood in Toronto there are no fewer than 10 building projects underway that involve development of a high-rise apartment/university residence/condominium on it of more than 20 stories in a 5 block radius from my home. Most are expected to be about 40 stories in height.
As a resident and citizen I was thinking one day: How does one even engage with this? I could attend a building planning meeting, but that would be looking at a single development on a single site, not a neighbourhood. There is a patchwork of plans for neighbourhoods, but they are guidelines, not embedded in specific codes. I was (and am) stuck with how to have a conversation of influence that might help shape decisions about how this was all going to unfold.
At the risk of being pegged as a NIMBY, let me state that I am fully able to accept that downtown living in a fast-growing, large urban centre means that empty lots or parking pads are a target for development and buildings will go up. I get to live here and so should others so I can’t complain about a development here and there. But when we are talking about development of that magnitude so quickly it gets quickly problematic for things like sidewalks, transit, parking, traffic, and even things like getting a seat at my favourite cafe that are all going to change in a matter of months, not years. There’s no evolution here, just revolution.
Adding a few hundred people to the neighbourhood in a year is one thing. Adding many thousand in that same time is something quite different. The problem is that city planning is done on a block-by-block basis when we live in an interconnected space. An example of this is transit. Anyone who takes a bus, streetcar or subway knows that the likelihood of getting a seat depends greatly on when you travel and where you get on. Your experience will radically change when you’re at the beginning of the line or near the end of it. Residents of one neighbourhood in Toronto were so tired of never being able to get on packed streetcars because they were in the middle of the line they crowdfunded a private bus service, which was ultimately shut down a few months later.
Planning for scale: bounding systems using foresight
On a piece-by-piece basis, planning impact is easier to assess. Buildings go through proposals for the lots — a boundary — and have to meet specific codes, which act as constraints on a system. Yet, next to these boundaries are boundaries for other systems; other lots and developments. They, too are given the same treatment and usually that produces a plan perfectly suited to that individual development, but something that might falter when matched with what’s next to it. Building plans are approved and weighed largely on their merits independent of the context and certainly not as a collective set of proposals. Why? Because there are different stakeholders with separate needs, timelines, investments and desires.
One of the keys is to have a vision for what the city will look like as a system. Does your city have one? I’m not talking about something esoteric like “Be the greatest city in the world”, but generating some evidence-supported form of vision for what the city will look like in 5, 10, 25 years. This requires foresight, a structured, methodical means of drawing evidence-informed speculations about the future that combines design, data, and some imagination. In fact, my colleague Peg Lahn and I did this for the city of Toronto and what we envisioned the future ‘neighbourscapes’ of the city might look like using foresight methods. We forecast out to 2030, drawing on trends and drivers of social activities and looking at current patterns of migration, development, policy and political activity.
That report focused on the city itself and its neighbourhoods in general, but didn’t look at specific neighbourhoods. Yet, strategic foresight can help create a bounded set of conditions where one can start to imagine the potential impact of decisions in advance and develop scenarios to amplify or mitigate against certain challenges or uncertainties. Foresight allows for better assessment of the landscape of knowns and unknowns within a complex system.
From cities to organizations
The same principles to civic planning through foresight can be applied to organizations. If you are assessing operations and plans for programs independent of one another and not as a whole, yet are operating an organization as a system with all its interdependencies, then without strategic foresight plans may just arbitrary statements of intent. Consider the “5-year plan“. Why is it five years? What is special about 5 years that makes us do that? How about four years? Ten? 18?
Plans are worthless, but planning is everything.
The planning process, no matter what the time scale, works best when it allows for engagement of ideas about what the future might look like, how to create it, and how to tell when you’ve been successful. This is part of what developmental evaluation does when blended with strategic foresight and design. This creates conversations about what future we want, what we see coming and how we might get to shape it. The plan itself is secondary, but the planning — informed by data and design — is what is the most powerful part of the process.
To draw on another US President, Abraham Lincoln:
The best way to predict your future is to create it.
By focusing on the here and now, independent of what is to come and might be, organizations risk designing perfectly suited programs, policies and strategies that are ideal for the current context, but jeopardize the larger system that is the organization itself.
Do you have a plan? Do you know where you’re going? Can you envision where things are going to be? How will you know when you get there or when to change course?
For resources on these topics check out the Censemaking library tab on this blog, which has a lot of references to tools and products that can help advance your thinking on strategic foresight, evaluation, design and systems thinking. For those interested in how developmental evaluation can contribute to program development, check out Michael Quinn Patton’s lastest book (with Kate McKegg and Nan Wehipeihana) on Developmental Evaluation Exemplars.
Lastly, if you need strategic help in this work, contact Cense Research + Design as this is what they (we) do.
Our information landscape has been compared with our diets providing an ample opportunity to compare what we ‘consume’ with how we prepare food and perhaps draw on the analogy of the frog and the boiling point of water. Are we slowly killing our ability to produce independent thought through vehicles like blogs as we draw our gaze to and focus on the social media stream?
Iranian-Canadian blogger Hossein Derakhshan was one of the few who opposed the state-imposed media messaging about what was (and has been) happening in Iran. For that, he was jailed. Writing in the Guardian news service, Darakshan, once referred to as Iran’s ‘Blogfather’, discusses how blogging enabled him to be this voice and how he’s become increasingly concerned with how that option is getting slowly silenced not necessarily by governments but by social media.
Darakhshan’s perspective on social media is made all the more interesting because of his role as a prominent blogger before his arrest and the 6-year prison term that disrupted that role, offering something of a time-travel experiment in social media that he illustrates with a story from the Qur’an (known as the tale of the Seven Sleepers).
Upon his return online, Darakhshan noticed that the patchwork quilt of perspectives that were present in the blogosphere was being replaced by ‘The Stream’ that social media provides.
This stream is no longer about a diversity of perspectives, but rather something custom-tailored to meet our preferences, desires, and the needs of corporations seeking to sell advertising, products and services that align with their perception of what we want or require. This stream also allows us to shield ourselves from perspectives that might clash with our own. Groups like ISIS, he suggests, are enabled and emboldened by this kind of information vacuum:
Minority views are radicalised when they can’t be heard or engaged with. That’s how Isis is recruiting and growing. The stream suppresses other types of unconventional ideas too, with its reliance on our habits.
The Stream & our information diet
What’s interesting about The Stream is that it is about bits and bites (or bytes) and not about meals. Yet, if we consider the analogy of information and food a little further we might find ourselves hard-pressed to recall the snacks we had, but (hopefully) can recall many memorable meals. Snacking isn’t bad, but it’s not memorable and too much of it isn’t particularly healthy unless it’s of very high-quality food. With no offence to my ‘friends’ and ‘follows’ on social media, but most of what they produce is highly refined, saccharine-laden comfort food in their posts and retweets, with a few tasty morsels interspersed between rants, cat videos, selfies, and kid pictures. To be fair, my ‘offerings’ aren’t much better when I look across many of my recent Tweets and posts as I am no more than a box of sugar-topped Shreddies to others’ Frosted Flakes. (Note to self when composing New Years Resolutions, even if they are likely to fail, that I need to add less sugar to my stream).
Yet, we are living an age of information abundance and, like food abundance (and the calories that come with it), we are prone to getting obese and lethargic from too much of it. This was the argument that political communicator Clay Johnston makes in his book The Information Diet. Obesity in its various forms makes us slower, less attuned, more disengaged and often far less mindful (and critical) of what we take in whether it’s food or information. And like obesity, the problem is not just one of personal choice and willpower, it’s also about obesogenic systems that include: workplaces, restaurants, communities, markets and policies. This requires systems thinking and ensuring that we are making good personal choices and supporting healthy, critical information systems to support those choices.
The Stream is actually antithetical to that in many regards as Darakhshan points out. The Stream is about passing content through something else, like Facebook, that may or may not choose to pass it on to someone at any given time and place. I’ve noticed this firsthand over the holiday season by finding “Getting ready for Christmas” messages in my Facebook feed on Boxing Day and beyond.
The problem with The Stream is that everything is the same, by design, as Darakhshan notes in an earlier post on his concerns with his new post-imprisonment Web.
Six years was a long time to be in jail, but it’s an entire era online. Writing on the internet itself had not changed, but reading — or, at least, getting things read — had altered dramatically. I’d been told how essential social networks had become while I’d been gone, and so I knew one thing: If I wanted to lure people to see my writing, I had to use social media now.
So I tried to post a link to one of my stories on Facebook. Turns out Facebook didn’t care much. It ended up looking like a boring classified ad. No description. No image. Nothing. It got three likes. Three! That was it.
An information food web
Diversity of perspective and content is critical for healthy decision-making in complex systems. Our great problems, the wicked ones from terrorism to chronic disease to mass migration to climate change, will not be solved in The Stream. Yet, if we push too much toward creating content in social networks that are no longer controlled by users (even if the content is produced by users) and designed to facilitate new thinking, not just same thinking, our collective capacity for addressing complex problems is diminished.
Wicked problems will not be solved by Big Data alone. We cannot expect to simply mine our streams looking for tags and expect to find the diversity of perspective or new idea that will change the game. As Ethan Zuckerman has pointed out, we need to rewire our feeds consciously to reflect the cosmopolitan nature of our problems and world, not just accept that we’ll choose diversity when our information systems are designed to minimize them.
Much like a food web, consideration of our information ecosystems in systems terms can be useful in helping us understand the role of blogging and other forms of journalism and expression in nurturing not only differences of opinion, but supporting the democratic foundation in which the Web was originally based. Systems thinking about what we consume as well as produce might be a reason to consider blogging as well as adding to your social media stream and why more ‘traditional’ media like newspapers and related news sites have a role.
Otherwise, we may just be the frog in the boiling pot who isn’t aware that it’s about to be cooked until it’s too late.
It is interesting that Darakhshan’s piece caught my attention the day after WordPress delivered my ‘Year in Blogging’ review to my inbox. It pointed out that there were just 4 posts on Censemaking in 2015. This is down from more than 90 per year in past calendar years. Clearly, I’ve been drawn into the stream with my content sharing and perhaps it’s time to swim back against the current. This blog was partly a response. Stay tuned for more and thanks for reading.
Image: Frog & Saucepan used under Creative Commons License via Wikimedia Foundation.
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?
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.
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.
Evaluation is supposed to be driven by a program’s needs and activities, but that isn’t always the case. What happens when the need for numbers, metrics, ‘outcomes’ and data shape the very activities programs do and how that changes everything is something that is worth paying some attention to.
Since the Second World War we’ve seen a gradual shift towards what has been called presence of neo-liberal values across social institutions, companies, government and society. This approach to the world is characterized, among other things, by its focus on personal and economic efficiency, freedom, and policies that support actions that encourage both. At certain levels of analysis, these policies have rather obvious benefits.
Who wouldn’t like to have more choice, more freedom, more perceived control and derive more value from their products, services and outputs? Not many I suspect. Certainly not me.
Yet, when these practices move to different levels and systems they start to produce enormous complications that are at odds with — and produce distortions of — the very values that they espouse. We’ve seen the same happen with other value systems that have produced social situations that are highly beneficial in some contexts and oppressive and toxic in others – capitalism and socialism both fit this bill.
Invisible tails and wags
What makes ‘isms’ so powerful is that they can become so prevalent that their purpose, value and opportunity stop being questioned at all. It is here that the tail starts to wag the dog.
Take our economy (or THE economy as it is somewhat referred to). An economy is intended to be a facilitator and product of activities used to create certain types of value in a society. We work and produce goods (or ideas), exchange and trade them for different things, and these allow us to fulfill certain human goals. It can take various shapes, be regulated more or less, and can operate at multiple scales, but it is a human construction — we invented it. Sometimes this gets forgotten and in times when we use the economy to justify behaviour we forget that it is our behaviour that is the economy.
We see over and again with neoliberalism (which is among the most dominant societal ‘ism’ of the past 50 years in the West and more reflected globally all the time) taken at the broadest level, the economy becomes the central feature of our social systems rather than a byproduct of what we do as social beings. Thus, things like goods, experiences, relations and so on we used to consider as having some type of inherent value suddenly become transformed into objects that judgements can be made.
The role of systems
This can make sense where there are purpose-driven reasons to assign particular value scores to something, but the nature of value is tied to the systems that surround what is valued. If we are dealing with simple systems, those where there are clear cause-and-effect connections between the product or service under scrutiny and its ability to achieve its purpose, then valuation measurement makes sense. We can assert that X brand of laundry detergent is better than Y on the basis of Z. We can conduct experiments, trials and repeated measures that can compare across conditions.
It is also safe to make an assumption of value based on the product’s purpose that can be generalized. In other words, our reason for using the product is clear and relatively unambiguous (e.g., to clean clothes using the above example). There may be additional reasons for choosing X brand over Y, but most of those reasons can be also controlled for and understood discretely (e.g., scent, price, size, bottle shape etc..).
This kind of thinking breaks down in complex systems. And to make it even more complex, it breaks down imperfectly so we have simple systems interwoven within complex ones. We have humans using simple products and services that operate in new, innovative and complex conditions. Unfortunately, what comes with simple systems is simple thinking. Because they are — by their nature — simple, these system dynamics are easy to understand. Returning to our example of the economy, classical micro-economic models of supply and demand as illustrated below.
Relationships and the systems that surround them
Using this model, we can do a reasonable job of predicting influence, ascertaining value and hypothesizing relationships between both.
In complex systems, the value links are often in flux, dynamic, and relative requiring a form of adaptive evaluation like developmental evaluation. But that doesn’t happen as much as it should, mostly because of a failure to question the systems and their influence. Without questioning the values and value that systems create — the isms that were mentioned earlier — and their supposed connection to outcomes, we risk measuring things that have no clear connection to value and worse, we create systems that get designed around these ineffective measures.
What this manifests itself in is mindless bureaucracy, useless meetings, pompous and intelligible titles, and innovation-squashing regulations that get divorced from the purpose that they are meant to solve. And in doing so, this undermines the potential benefit that the original purpose of a bureaucracy (to document and create an organizational memory to guide decisions), meetings (to discuss and share ideas and solve problems), titles (to denote role and responsibility — although these aren’t nearly as useful as people think in the modern organization), and regulations (to provide a systems lens to constrain uncoordinated individual actions from creating systems problems like the Tragedy of the Commons).
More importantly, this line of thinking also focuses us on measuring the things that don’t count. And as often quoted and misquoted, the phrase that is apt is:
Not everything that counts can be counted, and not everything that can be counted counts.
Counting what counts
It is critical to be mindful of the purpose — or to reconnect, rediscover, reinvent and reflect upon the purposes we create lest we allow our work to be driven by isms. Evaluators and their program clients and partners need to stand back and ask themselves: What is the purpose of this system I am dealing with?
What do we measure and is that important enough to matter?
Perhaps the most useful way of thinking about this is to ask yourself: what is this system being hired to do?
Regular mindful check-ins as part of reflective practice at the individual, organizational and, where possible, systems level are a way to remind ourselves to check our values and practices and align and realign them with our goals. Just as a car’s wheels go out of alignment every so often and need re-balancing, so too do our systems.
In engaging in reflective practice and contemplating what we measure and what we mean by it we can better determine what part of what we do is the dog, what is the tail and what is being wagged and by whom.
A recent study found looked into the experience of cyberbullying by university professors at the hands of their students. This disturbing phenomenon points to much larger issues beyond mental health promotion and calls into question many of the assumptions we have about the systems we’ve designed to foster education and what it means to be a learner at university.
The university is one of our oldest cultural institutions and its instructors are considered to have among societies most respected jobs, even if not always well compensated. In the past, students often approached their professors with a mixed sense of wonder, respect, curiosity and fear and that, in healthy situations, was reciprocated by faculty to create a space where people could explore ideas, learn, and challenge themselves and others to grow. That relationship has started to change as evidenced by the rise of cyberbullying in the classroom.
A recent article in Macleans Magazine looked at the changing state of the post-secondary classroom and the role of cyberbullying. Only this was not about student victims, but students as the perpetrators against their professors. The effects of cyberbullying are crippling and professors are bearing the burden of having hundreds of eyes watching them, writing about them and writing ‘consumer reviews’ about them in anonymous and sometimes unflattering, inflammatory and questionable terms on sites like RateMyProfessor.com .
Researchers at the University of California, Riverside found that as students age the incidence of face-to-face bullying decreases and cyberbullying increases, which might partly explain why we’re seeing this in university settings when face-to-face bullying goes subterranean. Yet, the notion that professors that are getting bullied by their students belies some other issues that require further investigation, namely those related to the nature of education and the role of students-as-consumers.
Consuming knowledge, producing expectations
If you pay for something, should you not expected to get something rather specific for that experience or product? Aside from some rare experiences of profane/profound personal challenge/punishment like Tough Mudder and its peers or dental work, there are few things we willingly pay for that we don’t derive pleasure from or achieve a very specific (anticipated) outcome.
Education is problematic because we might not know what we’ll get from it going in, what kind of experiences or ideas will emerge, and how our relationship to those experiences will change us. That is its great gift.
Many of us have had profound life changes because of something we experienced through our education and writing as one who has completed four different degree programs and a post-doc I can confidently say that I didn’t receive a lot of what I expected in any of those programs and I am a better person for it. Indeed, if I go to a specific learning event (aside from those focused on a specific technique or technology) I am disappointed if I actually come away with exactly what I expected.
That is part of the point. We don’t know what we don’t know.
But when you start viewing education as a thing that resembles any other market-driven product or services, you begin to focus on learning as a consumable good and your students as customers. In following this line of thought, it makes some sense to focus the delivery of this product on the desires of the consumer.
Increasingly, teachers (of various stripes) are being asked to consider a range of student-related variables in their education. Things like learning styles and preferences are now being woven into classroom instruction and students have come to learn to expect and are increasingly demanding to be taught in ways that match their unique learning preferences and styles. While there is reason to imagine that this approach is useful in stimulating engagement of students in the lessons, there is increasing evidence much of it does little to enhance actual learning. Many of the life lessons we’ve gained that shape what we do and who we are were not delivered in the manner of our choosing, conformed with our preferences and were not desired, expected or enjoyed in the moment. We risk confusing enjoyment with learning; they can be aligned but one isn’t necessary for the other to take place.
However, when we are viewing education from a consumer model, the specific outcomes become part of the contract. If I come to get a degree in X because I believe that the job market demands the skills and knowledge that X brings and I am paying tens of thousands of dollars and spending four or more years acquiring X then I feel entitled to expect all the benefits that X brings. Further, I expect that my journey to acquiring X will be enjoyable, because why would I spend more money than I’ve ever seen on something I don’t enjoy.
Particularly when that is money I don’t have.
A debt to pay
In Canada and the United States, student debt rates have dramatically increased. The Canadian Federation of Students note that Canadian’s attending post-secondary education now owe more than $15B to the Canadian federal government (PDF) as part of their student loan program, a number that doesn’t include debt accumulated from borrowing from banks, family, credit cards and other means. In Canada’s largest province, Ontario, the rate of graduate employment has decreased since 2001 and the overall youth unemployment rate continues to be the highest, despite the province having one of the most educated youth population in the country (and arguably, the world). And while Ontario universities continue to promote the fact that education is a better pathway to success, it is a hard pill for many students to swallow when many can’t apply what they trained for and paid for after they graduate.
Satirist John Oliver has an informative, humorous and distressing take on student debt and the state of consumer-oriented education for those who want to learn more.
None of these reasons are excuses for cyberbullying, but it does give a more complicated picture of those that might feel they are entitled to bully others and their reasoning behind it.
What we are seeing is a systems change in the way education is being produced, consumed and experienced. Even the mere fact that we can now reasonably use the language of consumerism to speak to something like education should give us pause and concern. I’ve been involved in post-secondary education for nearly 20 years and there has always been students who simply wanted the ‘piece of paper’ (degree) as a stepping stone to a job and little more than that from their time at school. They were willing to do the work — often the minimum possible — to graduate, but they knew they had to put the effort in to be successful. There was never an expectation that one was entitled to anything from going to school, although that might be changing.
Market identities and education systems
Belgian psychotherapist Paul Verhaeghe has explored the role of identity in market-based economies in his new book What About Me? In the book, Verhaeghe illustrates how we construct our identities as people drawing on the research that reflects (and often contradicts or obscures) the two major perspectives on personality and identity: the person-as-blank-slate and the person as a reflection of the environment. The former perspective assumes we come into the world as we are while the latter assumes the world makes us who we are and both have enormous amount of moral, cultural and evidentiary baggage attached to them.
What Verhaeghe does is point to the ways in which both have elements of truth to them, but that they are mediated by the manner in which we construct the very questions about who we are and what our purpose is. These questions are (for many cultural, historical, economic and political reasons that he elaborates on) frequently market-based. Thus, who we are is defined by what we do, what we own, what we produce, and how we use such things once out into the world and that the value that come with such ways of defining ourselves is considered self-evident. He makes a disturbing and convincing case when one stops to reflect on the way we think about how we think (metacognition + mindfulness) .
When viewed from the perspective of a market, knowledge and its products soon become the goal and not the journey. Indeed, I’ve even written about this in support of an argument for better research-to-action and knowledge translation. Much of the knowledge-to-action discourse is about viewing knowledge as a product even if the more progressive models also view this as part of a process and even more as part of a system. But it is the last part — the system — that we often give the shortest shrift to in our discussions. What Verhaeghe and others are doing is encouraging us to spend more time thinking about this and the potential outcomes that emerge from this line of thinking.
Unless we are willing to talk more about the systems we create to learn, explore and relate we will continue to support Verhaeghe’s thesis and uphold the conditions for the kind of education-as-a-product thinking that I suspect is contributing to students’ changing behaviour with their professors and creating a climate at universities that is toxic instead of inspiring.