Tag: organizational change

design thinkingevaluation

Utility in Design-Driven Evaluation

on March 27, 2019

Design-driven evaluation focuses attention on what organization’s use in their decision-making and learning to support the creation of their products, delivery of services, and the overall quality of their work. While ultimately practical, this focus on utility also introduces some difficult conversations about what organizations truly value, not just what they say.

To say something is design-driven is to imply that its emphasis is on the process of creating something of value for someone. In this case, the value is through evaluation and what it means. Value in this case is framed as utility asking: what is it for? (and for whom and under what context)?

These are the questions that designers ask of any service, product, or structure that they seek to apply their attention to. Designers might ask: “what are hiring [the thing being designed] to do?” These are simple questions that may provoke much discussion and can transform the way we approach the creation and maintenance of something moving forward.

A different take is to ask people to describe what they already do (and what they want) to frame the discussion of how to approach the design. This can lead us into a trap of the present moment. It keeps people framing their work in the context of language that supports their present identity and the conceptions (and misconceptions) associated with it, not necessarily where they want to go.

Evidence-based?

You show me an evidence-based human service organization and I’ll show you one that is lying to you (and maybe to themselves), is in deep denial, or is focused on a narrow, established scope of practice. Very few fit the last category (but they do exist), which leaves us with the unsettling reality that we are likely dealing in some level of bullshit — a deliberate misrepresentation of the facts to impress others and themselves (see Harry Frankfurt’s work on the subject (PDF).

This is not to say that these organizations don’t use evidence at all or care about its application, but that there are so many areas within that scope of work that are not based on solid or even superficial evidence that to describe something as ‘evidence-based’ is an over-reach at best, a lie at worst. The reasons for this deception are many, but among them is simply that there is not enough evidence available to inform many aspects of the work. It’s impossible to truly be evidence-based when dealing with areas of complexity, social innovation, or complex innovation.

Consider this: an organization seeks to develop an evidence-based program and spends weeks or months gathering and reviewing research. They may even collect some data on their own and synthesize the findings together to inform a recommendation based on evidence. At play is the evidence for the program, the evidence to support the design of the program (converting evidence developed in one context into actionable structures, procedures, and plans into another), the evidence to support the implementation of the designed program in a new context, and the evidence generated through evaluation of the design, delivery, and outcomes associated with the program.

That is a lot of evidence to consider. I’ve never seen a program come even close to having evidence that even reasonably fits all of these contexts, let alone strong evidence. Why? Because there are so many variables at play in the program context (e.g., design, delivery, fidelity, etc..) and the process of evidence generation itself (e.g., design, data availability, analysis, etc..).

Utility means looking at what people actually use, not just what they say they use. To illustrate, I worked with an organization that proudly claimed that they were both evidence-based and a learning organization. When I asked what evidence they used and how they learned I was told with much more modest confidence that staff typically read “one or two” research articles per month (and that was it — and this was in a highly volatile, transnational, multidisciplinary field of practice). They also said that they engaged in reflective practice by writing up case reports, which (if completed at all), usually took up to four months to prepare after a site visit to a particular site or event due to the other activities they had to do as part of the day-to-day work of the organization.

This organization did their best, but that best wasn’t anywhere enough if they truly wished to be a learning organization or evidence-based. Yet, because they insisted they were these things they also insisted on an evaluation design that fit that narrative. They had not designed their organization to be evidence-based or a real learning organization. A design-driven approach would have developed things that suited that context and perhaps pushed them a little further toward being the organization they saw themselves to be.

Another Way: Fit for Purpose

Why bring up evidence-based decision-making? The reason has much to do with defining what makes design-driven evaluation different from other forms of evaluation (even research). Design-driven evaluation is about generating evidence for use within specific contexts. It involves using design principles and strategies to uncover and understand those principles ahead of the evaluation being designed. It means designing not only the evaluation itself, but the manner in which it produces products and the means associated with decision-making based on those products.

It is about being fit-for-purpose.

Most published forms of evidence is developed independent of the context in which it is to be used. That’s the traditional model for science. We learn things in one setting (maybe a lab) and then move it out into other settings (e.g., a clinic), do more trials and then eventually develop a body of evidence that is used to generalize to other settings. This works reasonably well for problems and issues that are simple or complicated in their structure.

As a situation involves ever greater complexity, that ability to translate from one setting or context to another breaks down. This complexity might also influence what the purpose and expected outcomes are of a program within that context. For example, a community-based health promotion program may have a theory, even program logic model, and goals, but it will need to consider neighbourhood design, differences in resident needs, local history, and the availability of other programs and resources. The purpose in one neighbourhood might be to provide a backstop to a local organization that is having financial problems where in another neighbourhood it might be to provide a vehicle for local leaders to take action where there are no other alternatives.

Not Leaving Things to Chance

Developing a fit-for-purpose program is not something that should be left to chance, because chances are very likely it won’t happen. If good design improves the use, usability, and overall translation of knowledge. A look at how real evidence-based practice emerges comes down to ways in which the design — intended or not — of the knowledge, the exchange opportunities, relationships, and systems come together.

Design-driven evaluation seeks to remedy one of the fundamental problems within the evidence translation process: the poor fit of the evaluation (data, process, focus) for the implementation of its findings. It’s about not leaving it to chance with the hope that maybe someone will figure out how to use things, overcome poor usability, persist through confusion, and still make good use of an evaluation.

Is this the system we want? Or could we do better? My answer is ‘no’ to the first and ‘yes’ to the second. Design-driven evaluations can be the means to get us to that ‘yes’ because as things get more complicated and complex and the need for better data, improved decisions, and decisive action rises we need to make sure we don’t leave doing better to chance.

Photo by Jeff Sheldon on Unsplash

If you’re interested in better and doing design-driven evaluation, contact Cense via this link.

psychology

The Developmental Psychology of Organizations

on January 17, 2019
Organizations start change somewhere

Every living thing has a journey that starts somewhere and ends eventually. Our ability to see this, understand it, and apply what we know about how humans grow and develop (as individuals and organizations) is what helps us determine how this journey unfolds and where it ends up.

The psychology of individuals is a complicated affair that involves understanding a variety of matters from personal and family history, genetics, cultural context, education, and social situating. While all of these contribute to who we are as people, the degree of influence and mix is different from person to person. It means that we are all a product of a collection of forces that combine together in various ways that make understanding how we change a challenge because of this holistic complexity.

For example, some of us might have behaviours and preferences associated with a certain personality type (extroverted and introverted) and find that quality to be relatively stable across the lifespan. While there are times we might exhibit qualities of another type, those are more situational than stable. For those who are more of an ambivert, identification with a particular preference might be more challenging. Whatever investment you place in this kind of personality assessment, what is important is that the stability and consistency of certain characteristics are what largely shapes our identity to others (and ourselves). It’s what makes us ‘us’.

From Individuals to Organizations

It has been argued that organizations exhibit much of the same kind of characteristic habits on their own while providing an aggregation of the characteristics of those within them and leading them to various degrees. Personality theory has been applied to organizational behaviour as a means of understanding how it is that certain actions, activities, habits, and patterns form from within organizations and their implications. This involves taking ideas developed for individuals and applying them to groups and the implications of this are considerable.

If we are to consider organizations similar to humans seriously, it can have significant implications for the way in which we engage in organizational change efforts. Much of the research on organizational change is tied to the development and implementation of a strategy. Strategy, in most conventional applications, is an expression of intent manifest through specific choices of focus and action. This approach rests largely on a cognitive rational model of change (pdf) where information (e.g., data, ‘facts’, perceptions, beliefs, and opinion) guides an assessment of the situation that forms the basis for a plan of action. The idea is that we see and learn things and plan and act according to that knowledge.

Most individual behaviour change models are founded on this approach that has thinking preceding action in a relatively rational, logical manner based on an objective assessment of the facts and evidence (with some emotional contributions here and there to make life interesting). So if we tie organizational change to the similar kind of mechanisms and models that we use to understand individuals, should we not apply similar modes of change facilitation? We do — but its how we do it that might be the problem.

Change Theory to Change Reality

One of the most vexing (and little discussed) issues for behavioural scientists is that the application of the cognitive rational model to personal, organizational, and social change has a rather unimpressive track record. A look at how people change finds that relatively little change comes from rationally reviewing a threat or opportunity and planning out a strategy (nevermind executing the planned strategy as envisioned). Even when the effects are modest, factors such as the match between the person, technique or intervention approach, and the problem being addressed continues to mediate the outcomes.

What happens when our theories and our practices don’t really work? Or at least don’t work as well as we think they do?

The answer — using the very argument that we are looking to disprove — is that we will address the matter as many individuals might: disagreement, resistance, and denial.

The field of organizational decision-making and innovation is littered with case studies that show how, in the face of overwhelming evidence to the contrary, organizations (like many individuals) resist change. Whether it was the speed at which those on the Titanic accepted the fact that their ship would sink after hitting the iceberg (nevermind the perception that the ship was invulnerable, to begin with) or companies who persist with a strategy that doesn’t match with changing times (e.g., Kodak and it’s photographic film business, Sears and its retail model), the inability to see, unwillingness to perceive or accept changing situations has led to major problems.

These problems are a matter of failing to change or adapt. To quote from The Leopard:

If want things to stay as they are, things will have to change

Change is something we need to do even if that is simply to maintain the status quo.

Person-Centred Organizational Change

Erik Eriksen, the Austrian-American psychoanalyst whose work focused on identity formation and development, was among the few to challenge the belief that people’s essential character was immutable and resistant to change. (The dominant view was that thinking and behaviour could change, but not ‘how one was’ as a person). He did, however, acknowledge that our ability to change who we are was not easy and takes a lifetime. This flies in the face of the dominant thinking in Western societies that we can make dramatic changes in an instant.

While talk-shows and popular self-books are filled with stories of dramatic transformation and inspiration about how you can change everything in an instant, the truth is that these cases are outliers (and often exaggerations) or misrepresentations. Much like the artist who ‘breaks out’ and becomes an ‘overnight sensation’ the journey to stardom is usually a long one that follows a Pareto distribution (that is a long, slow climb over time followed by very quick punctuation at the end). What is misread into these success stories is that the rapid change is a factor of a long, protracted build-up.

While there are some things that do follow this pattern much change is also linear and progressive. We see this in the work of another Ericsson: Anders Ericsson. His work is widely cited (and mis-cited) as being behind the ‘10,000 Hour Rule’ that suggests that expertise — a change from an unskilled novice to a skilled expert — is developed over that much time of practice. While the time itself is important, what is often missed in the citation of this work is that the key is on deliberative practice (pdf), which makes all the difference.

If we extrapolate from the work of both Eriksen/Ericsson’s we might develop a model of behaviour change that looks quite different than we have at present. Instead of trying 5-year plans, strategic goals, and inspirational visions of the future, we might be better off delving into an organization’s past, it’s formation, it’s core beliefs and personality, and spend more time looking at what it is already doing than what it seeks to do.

Developmental Organizations

We might then find what it seeks to deliberate on day-in-and-out and emphasize the ways in which to amplify the feedback that helps people learn deliberately and consistently. We might take these lessons — much like those small, tiny adjustments that expert violinists, athletes, and surgeons make to hone their craft — and make them visible and build on them. We would look upon organizations as developing organizations using approaches that fit with them developmentally (e.g., developmental evaluation). We would treat organizations like we would people.

Which is kind of funny because organizations are made of people. That’s some change.

Photo by Stanislav Kondratiev on Unsplash

behaviour changecomplexitysystems thinking

Reframing change

on August 10, 2017

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Change is one of the few universal constants as things — people, planet, galaxy — are always in some state of movement, even if it’s imperceptible. Change is also widely discussed and desired, but often never realized in part because we’ve treated something nuanced as over-simplified; it’s time to change. 

For something so omnipresent in our universe, change is remarkably mysterious.

Despite the enormous amount of attention paid to the concept of change, innovation, creation, creativity, and such we have relatively little knowledge of change itself. A look at the academic literature on change would suggest that most of human change is premeditated, planned and rational. Much of this body of literature is focused on health behaviours and individual-level change and draws on a narrow band of ‘issues’ and an over-reliance on linear thinking. At the organization level, evidence on the initiation, success, and management of change is scattered, contradictory and generally bereft of clear, specific recommendations on how to deal with change. Social and systems change are even more elusive, with much written on concepts like complexity and system dynamics without much evidence to guide how those concepts are to be practically applied.

Arguments can be made that some of the traditional research designs don’t work for understanding complex change and the need to match the appropriate research and intervention design to the type of system in order to be effective.  These are fair, useful points. However, anyone engaged in change work at the level where the work is being done, managed and led might also argue that the fit between change interest, even intention, and delivery is far lower than many would care to admit.

The issue is that without the language to describe what it is we are doing, seeing and seeking to influence (change) it’s easy to do nothing — and that’s not an option when everything around us is changing.

Taking the plunge

“The only way to make sense out of change is to plunge into it, move with it, and join the dance.” – Alan Watts

Dogs, unlike humans, never take swim lessons. Yet, a dog can jump into a lake for the first time and start swimming by instinct. Humans don’t fare as well and it is perhaps a good reason why we tend to pause when a massive change (like hopping in a pool or a lake) presents itself and rely both on contemplation and action — praxis — to do many things for the first time. Still, spend any time up near a cottage or pool in the summer and you’ll see people swimming in droves.

The threat of water, change of fear of the unknown doesn’t prevent humans from swimming or riding a bike or playing a sport or starting a new relationship despite the real threats (emotional, physical, and otherwise) that come with all of them.

Funny that we have such a hard time drawing praxis, patience, and sensemaking into our everyday work in a manner that supports positive change, rather than just reactive change. The more we can learn about what really supports intentional change and create the conditions that support that, the more likely we’ll be swimming and not just stuck on the shore.

Whatever it takes

“If you don’t like change, you’re going to like irrelevance even less.”—General Eric
Shinseki, retired Chief of Staff, U. S. Army

“It’s just not a good time right now”

“We’re really busy”

“I’m just waiting on (one thing)”

“We need more information”

These are some of the excuses that individuals and organizations give for not taking action that supports positive change, whatever that might be. Consultants have a litany of stories about clients who hired them to support change, develop plans, even set out things like SMART goals, only to see little concrete action take place; horses are led to water, but nothing is consumed.

One of the problems with change is that it is lumped into one large category and treated as if it is all the same thing: to make or become different (verb) or the act or instance of making or becoming different (noun). It’s not. Just as so many things like waves, moods, or decision-making strategies are different, so too is change. Perhaps it is because we continue to view change as a monolithic ‘thing’ without the nuance that we afford other similarly important topics that we have such trouble with it. It’s why surfers have a language for waves and the conditions around the wave: they want to be better at riding them, living with them and knowing when to fear and embrace them.

What is similar to the various forms that change might take is the threat of not taking it seriously. As the above quote articulates, the threat of not changing is real even if won’t be realized right away. Irrelevance might be because you are no longer doing what’s needed, offering value, or you’re simply not effective. Unfortunately, by the time most realize they are becoming irrelevant they already are.

Whatever it takes requires knowing whatever it takes and that involves a better sense of what the ‘it’ (change) is.

Surfing waves of change

To most of us, waves on the beach are classified as largely ‘big’ or ‘small’ or something simple like that. To a surfer, the conversation about a wave is far more delicate, nuanced and far less simplistic. A surfer looks at things like wind speed, water temperature, the location of the ‘break’ and the length of the break, the vertical and horizontal position of the wave and the things like the length of time it takes to form. Surfers might have different names for these waves or even no words at all, just feelings, but they can discern differences and make adjustments based on these distinctions.

When change is discussed in our strategic planning or organizational change initiatives, it’s often described in terms of what it does, rather than what it is. Change is described as ‘catastrophic‘ or ‘disruptive‘ or simply hard, but rarely much more and that is a problem for something so pervasive, important, and influential on our collective lives. It is time to articulate a taxonomy of change as a place to give change agents, planners, and everyone a better vocabulary for articulating what it is they are doing, what they are experiencing and what they perceive.

By creating language better suited to the actual problem we are one step further toward being better at addressing change-related problems, adapting, and preventing them than simply avoiding them as we do now.

Time to take the plunge, get into the surf and swim around.

 

 

Image credit: June 17, 2017 by Mike Sutherland used under Creative Commons License via Flickr. Thanks for sharing Mike!

behaviour changecomplexitydesign thinkingevaluationpsychology

Exploding goals and their myths

on July 20, 2017

SparkWall_Snapseed.jpg

Goal-directed language guides much of our social policy, investment and quests for innovation without much thought of what that means in practice. Looking at the way ideas start and where they carry us might offer us reasons to pause when fashioning goals and whether we need them at all. 

In a previous article, I discussed the problems with goals for many of the problems being dealt with by organizations and networks alike. (Thanks to the many readers who offered comments and kudos and also alerted me that subscribers received the wrong version minus part of the second paragraph!). At aim was the use of SMART goal-setting and how it made many presumptions that are rarely held as true.

This is a follow-up to that to discuss how a focus on the energy directed toward a goal and how it can be integrated more tightly with how we organize our actions at the outset might offer a better option than addressing the goals themselves.

Change: a matter of energy (and matter)

goal |ɡōl| noun:  the object of a person’s ambition or effort; an aim or desired result • the destination of a journey

A goal is a call to direct effort (energy) toward an object (real or imagined). Without energy and action, the goal is merely a wish. Thus, if we are to understand goals in the world we need to have some concept of what happens between the formation of the goal (the idea, the problem to solve, the source of desire), the intention to pursue such a goal, and what happens on the journey toward that goal. That journey may involve a specific plan or it may mean simply following something (a hunch, a ‘sign’ — which could be purposeful, data-driven or happenstance, or some external force) along a pathway.

SMART goals and most of the goal-setting literature takes the assumption that a plan is a critical success factor in accomplishing a goal.

If you follow SMART, Specific, Measurable, Attainable, Realistic, and Time-bound (or Timely) this plan needs to have these qualities attached to them. This approach makes sense when your outcome is clear and the pathway to achieving the goal is also reasonably clear such as smoking cessation, drug or alcohol use reduction, weight loss and exercise. It’s the reason why so much of the behaviour change literature includes goals: because most of it involves studies of these kinds of problems. These are problems with a clear, measurable outcome (even if that has some variation to it). You smoke cigarettes or you don’t. You weigh X kilograms at this time point and Y kilograms at that point.

These outcomes (goals) are the areas where the energy is directed and there is ample evidence to support means to get to the goal, the energy (actions) used to reach the goal, and the moment the goal is achieved. (Of course, there are things like relapse, temporary setbacks, non-linear changes, but researchers don’t particularly like to deal with this as it complicates things, something clinicians know too well).

Science, particularly social science, has a well-noted publication bias toward studies that show something significant happened — i.e., seeing change. Scientists know this and thus consciously and unconsciously pick problems, models, methods and analytical frameworks that better allow them to show that something happened (or clearly didn’t), with confidence. Thus, we have entire fields of knowledge like behaviour change that are heavily biased by models, methods and approaches designed for the kind of problems that make for good, publishable research. That’s nice for certain problems, but it doesn’t help us address the many ones that don’t fit into this way of seeing the world.

Another problem is much less on the energy, but on the matter. We look at specific, tangible outcomes (weight, presence of cigarettes, etc..) and little on the energy directed outward. Further, these perspectives assume a largely linear journey. What if we don’t know where we’re going? Or we don’t know what, specifically, it will take to get to our destination (see my previous article for some questions on this).

Beyond carrots & sticks

The other area where there is evidence to support goals is from management and study of its/ executives or ‘leaders’ (ie. those who are labelled leaders and might be because of title or role, but whether they actually inspire real, productive followership is another matter). These leaders call out a directive and their employees respond. If employees don’t respond, they might be fired or re-assigned — two outcomes that are not particularly attractive to most workers. On the surface it seems like a remarkably effective way of getting people motivated to do something or reach a goal and for some problems it works well. However, those type of problem sets are small and specific.

Yet, as much of the research on organizational behaviour has shown (PDF), the ‘carrot and stick’ approach to motivation is highly limited and ineffective in producing long-term change and certainly organizational commitment. Fostering self-determination, or creating beauty in work settings — something not done by force, but by co-development — are ways to nurture employee happiness, commitment and engagement overall.

A 2009 study, appropriately titled ‘Goals Gone Wild’ (PDF), looked at the systemic side-effects of goal-setting in organizations and found: “specific side effects associated with goal setting, including a narrow focus that neglects non-goal areas, a rise in unethical behavior, distorted risk preferences, corrosion of organizational culture, and reduced intrinsic motivation.” The authors go on to say in the paper — right in the abstract itself!: “Rather than dispensing goal setting as a benign, over-the-counter treatment for motivation, managers and scholars need to conceptualize goal setting as a prescription-strength medication that requires careful dosing, consideration of harmful side effects, and close supervision.”

Remember the last time you were in a meeting when a senior leader (or anyone) ensured that there was sufficient time, care and attention paid to considering the harmful side-effects of goals before unleashing them? Me neither.

How about the ‘careful dosing’ or ‘close supervision’ of activities once goal-directed behaviour was put forth? That doesn’t happen much, because process-focused evaluation and the related ongoing sense-making is something that requires changes in the way we organize ourselves and our work. And as a recent HBR article points out: organizations like to use the excuse that organizational change is hard as a reason not to make the changes necessary.

Praxis: dropping dualisms

The absolute dualism of goal + action is as false as the idea of theory + practice, thought + activity. There are areas like those mentioned above where that conception might be useful, yet these are selective and restrictive and can keep us focused on a narrow band of problems and activity. Climate change, healthy workplaces, building cultures of innovation, and creating livable cities and towns are not problem sets that have a single answer, a straightforward path, specific goals or boundless arrays of evidence guiding how to address them with high confidence. They do require a lot of energy, pivoting, adapting, sense-making and collaboration. They are also design problems: they are about making the world we want and reacting the world we have at the same time.

If we’re to better serve our organizations and their greater purpose, leaders, managers, and evaluators would be wise to focus on the energy that is being used, by whom, when, how and to what effect at more close intervals to understand the dynamics of change, not just the outcomes of it. This approach is one oriented toward praxis, an orientation that sees knowledge, wisdom, learning, strategy and action as combined processes that ought not be separated. We learn from what we do and that informs what we do next and what we learn further. It’s also about focusing on the process of design — that creation of the world we live in.

If we position ourselves as praxis-oriented individuals or organizations, evaluation is part of regular attending to the systems we design to support goals or outcomes through data and sensemaking. Strategy is linked to this evaluation and the outcomes that emerge from it all is what comes from our energy. Design is how we put it all together. This means dropping our dualisms and focusing more on integrating ourselves, our aspirations and our activities together toward achieving something that might be far greater than any goal we can devise.

Image credit: Author

 

 

innovation

Acting on Failure or Failure to Act?

on April 8, 2014

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Who would have thought that failure would be held up as something to be desired just a few years ago? Yet, it is one thing to extol the virtues of failure in words, it is quite another to create systems that support failure in action and if the latter doesn’t follow the former, failure will truly live up to its name among the innovation trends of the 21st century. 

Ten years ago if someone would have said that failure would be a hot term in 2014 I would have thought that person wasn’t in their right mind, but here we are seeing failure held up as an almost noble act with conferences, books and praise being heaped on those who fail. Failure is now the innovator’s not-so-secret tool for success. As I’ve written before, failure is being treated in a fetishistic manner as this new way to unlock creativity and innovation when what it might be is simply a means reducing people’s anxieties.

Saying it’s OK to fail and actually creating an environment where failure is accepted as a reasonable — maybe even expected — outcome is something altogether different. Take strategic planning. Ever see a strategic plan that includes failure in it? Have you ever seen an organization claim that it will do less of things, fail more often, and learn more through “not-achieving” rather than succeeding?? Probably not.

How often has a performance review for an individual or organization included learning (which is often related to failure) as a meaningful outcome? By this I refer to the kind of learning that comes from experience, from reflective practice, from the journey back and forth through confusion and clarity and from the experimentation of trying and both failing and succeeding. It’s been very rare that I’ve seen that in either corporate or non-profit spaces, at least in any codified form.

But as Peter Drucker once argued: what gets measured, get’s managed.

If we don’t measure failure, we don’t manage for it and nor do our teams include failure as part of their core sets of expectations, activities and outcomes and our plans or aspirations.

Failure, mindfulness and judgement

In 2010 post in Harvard Business Review, Larry Prusak commented on the phenomenon of measurement and noted that judgement — something that comes from experience that includes failure — is commonly missing from our assessments of performance of individuals and organizations alike. Judgement is made based on good information and knowledge, but also experience in using it in practice, reminding me of a quote a wise elder told me:

Good judgment comes from experience, but experience comes from bad judgment.

One of the persistent Gladwellian myths* out there is that of the 10,000 hours rule that suggests if we put that amount of time into something we’re likely to achieve a high level of expertise. This is true only if most of those 10,000 hours were mindful, deliberate ones devoted to the task at hand and involve learning from the successes, failures, processes and outcomes associated with those tasks. That last part about mindful, reflective attention or deliberate practice as the original research calls it (as so many Gladwellian myths suffer from) is left off of most discussions on the subject.

To learn from experience one has to pay attention to what one is doing, what one is thinking while doing it, and assessing the impact (evaluation) of that action once whatever is done is done. For organizations, this requires alignment between what people do and what they intend to do, requiring that mindful evaluation and monitoring be linked to strategy.

If we follow this lead where it takes us is placing failure near the centre of our strategy. How comfortable are you with doing that in your organization?

A failure of failure

Failure is among the most emotionally loaded words in the English language. While I often joke that the term evaluation is the longest four-letter word in the dictionary, failure is not far off. The problem with failure, as noted in an earlier post, is that we’ve been taught that failure is to be avoided and the opposite of success, which is viewed in positive terms.

Yet, there is another reason to question the utility of failure and that is also related to the term success. In the innovation space, what does success mean? This is not a trivial question because if one asks bold questions to seek novel solutions it is very likely that we don’t know what success actually looks like except in its most general sense.

A reading of case studies from Amazon to Apple and Acumen to Ashoka finds that their success looks different than the originators intended. Sometimes this success is far better and more powerful and sometimes its just different, but in all cases the path was littered with lessons and few failures. They succeeded because they learned, not because they failed.

Why? Because those involved in creating these ‘failures’ were paying attention, used the experience as feedback and integrated that into the next stage of development. With each stage comes more lessons and new challenges and thus, failure is only so if there is no learning and reflection. This is not something that can be wished for; it must be built into the organization.

So what to do?

  • Build in the learning capacity for your organization by making learning a priority and creating the time, space and organizational support for getting feedback to support learning. Devoting a small chunk of time to every major meeting to reflecting back what you’re learning is a great way to start.
  • Get the right feedback. Developmental evaluation is an approach that can aid organizations working in the innovation space to be mindful.
  • Ask lots of questions of yourself, your stakeholders, what you do and the systems you’re in.
  • Learn how to design for your particular program context based on feedback coming from the question asking and answering. Design is about experimenting without the expectation of immediate success.
  • Develop safe-fail experiments that allow you to try novel approaches in a context that is of relatively low risk to the entire organization.

There are many ways to do this and systems that can support you in truly building the learning capacity of your organization to be better at innovating while changing the relationship you have with ‘failure’.

For more information about how to do this, CENSE Research + Design offers consultation and training to get organizations up to speed on designing for social innovation.

 

* Refers to ideas popularized by journalist and essayist Malcolm Gladwell that are based on the scientific research of professionals and distilled into accessible forms for mass market reading that become popular and well-known through further social discussion in forms that over-simplify and even distort the original scientific findings. It’s a social version of the “telephone game“. The 10,000 hour ‘rule’ was taken from original research by K. Anders Ericsson and colleagues on deliberate practice and is often discussed in the context of professional (often medical) training, where the original research was focused. This distortion is not something Gladwell intends, rather becomes an artifact of having ideas told over and again between people who may have never seen the original work or even Gladwell’s, but take ideas that become rooted in popular culture. A look at citations on failure and innovation finds that the term deliberate practice is rarely, if ever, used in the discussion of the “10,000 rule”.

 

Photo Credit: Project365Fail by Mark Ordonez used under Creative Commons license via Flickr. Thanks for sharing, Mark!

 

 

behaviour changecomplexitypublic healthsocial systemssystems thinking

The New Zombie

on October 24, 2013

Zombie stare

They are among us and hungry for brains

Zombies are attacking us; not for brains, but for attention. The consequences of this is that they are everywhere and sucking the intelligence out of human systems. 

Forget orange, zombie is the new black.

Zombies are hot. TV shows, books and films about zombies are more popular than ever, and this time of year the public’s attention to the undead is at its nadir. The CDC in the United States even got into the act by using zombies as a health promotion vehicle to support emergency preparedness. From zombie walks to art shows, the staggering brain-eating, brain-less are everywhere.

Yet, there is a new breed being formed that doesn’t eat brains and has them, but may not be using them well and they are all around us everywhere.

They walk among us

Look around and what do you see? People online, on the phone, texting and walking and driving, being everywhere except where they are. Examples of people walking into fountains or falling into a sinkhole while on the phone are often seen as comi-tragic, yet they belie a remarkably powerful trend towards disengagement from the world around them. Charlene deGuzman and Miles Crawford‘s beautiful and disheartening short film I Forgot My Phone plays this for further comic and sad effect as they portray a day in the life of someone paying attention to those not paying attention to anything away from their screen. The film highlights the modern paradox of being more connected than ever, yet overwhelmingly alone.

Emerging research is showing remarkable spikes in risks associated with mobile phone use and injury and mortality. We might laugh at people falling into holes or bumping into things, but only when it hurts the ego and not the body. This is serious stuff. Keep in mind that we don’t see non-reported injuries (e.g., someone bruising their head) and the many near misses between person and object — including cars, which have their own epidemic of problems with texting and attention.

Indeed, zombies embody paradox: a brainless being that is undead seeks brains to stay unalive. Whether they are alive or dead depends on where you stand and that is what makes them a complex character despite their surface-level simplicity.

Brains…need…more…(use of science) brains….

Zombie Science

Zombie Science?

While it might be easy to point to those on phones, zombie behaviour occurs elsewhere in places where the effects are far less comic and just as dangerous. The latest issue of The Economist features a cover story on the problems science is having with it credibility and quality control. Some of this is due to what I would call zombie-like behaviour: mindless attention in a manner that restricts awareness and appreciation of one’s immediate context and the larger system to which that behaviour occurs.

The recent expose by science journalist John Bohannon published in the journal Science exposes zombie-like thinking in how open-access science journals accept and reject papers. Bohannon’s inquiry was prompted by questions about the way fees were charged for open access journals (which is how they can remain open to the public) and the peer review require to advance publication. Presumably, an article has to pass review from peer professional scientists before it is accepted and then the fee is paid. No acceptance, no fee (except for perhaps a small application processing charge).

As profiled in an interview with the CBC radio show The Current…

Bohannon wanted to find out whether fee-charging open access journals were actually keeping their promise to do peer review — a process in which scientists with some knowledge of a paper’s topic volunteer to check it for scientific flaws…

…In the end, what he concluded was that “a huge proportion” of the journals were not ensuring their papers were peer reviewed.

Even in cases where peer review happened, it didn’t always function correctly. For example, the Ottawa-based International Journal of Herbs and Medicinal Plants clearly sent the paper out to be reviewed by real scientists, who pointed out some flaws, Bohannon recalled. Even so, when Bohannon submitted a revised version of the paper without correcting any of the flaws, it was accepted.

Bohannon’s approach and findings are not without some problems of their own, but they don’t much change the conclusion that there are deep problems within the scientific enterprise.

Much of what Bohannon found can be attributed to greed, but a great deal of it is due to bad scientific practice. As a consultant who is also a publishing researcher and ‘recovering’ academic I know the enormous amount of energy that goes into publishing an academic article in a scholarly journal. As one who is sent between 4 to 5 manuscripts to review from legitimate journals per month I know the demands that are placed on reviews. We also publish far too much for the system to handle. Writing in the Chronicle of Higher Education, Mark Bauerlein and colleagues look closely at the ‘avalanche’ of publishing and shed light on many reasons why the problems that the Economist and Science occur (Note: I’d strongly encourage you to read through the comments as it is as instructive as the article itself).

They are everywhere

To add to the examples of zombie culture I need only look to my own daily life outside of science and  mobile phones. Just the other day I witnessed the following example at a community meeting that was organized in part to discuss the expenditure of funds to make a better living area for people in a building:

Presenter: “…and I am pleased to conclude that the new furniture for the outdoor spaces is going to be made by a company that created the same products at [place] out of recycled materials. We will expect to have the new furniture here in 6 to 8 weeks. Any questions?”

First question: “I love the work you’ve done. Can you tell me when the furniture will be here?”

Sadly, I have many other stories that show that many people are not paying attention. They are sitting through workshops and not picking up basic concepts (even after having asked for it and having been given it multiple times over), asking for materials that were already shared on multiple occasions, suggesting ideas that were already discussed and agreed upon over because that person didn’t engage in the discussion and so on. This happens not because people are stupid, but because they are disengaged.

A simple search through statistics compilations finds enormous material on what kind of inputs we expose ourselves to and its impact on attention. There is more coming at us in quantity and context and that is undoubtedly influencing quality of processing and engagement. I can speak of this personally and through observation. The amount of times I find people not hearing what is said, processing it effectively, or even remembering something said is staggering.

It’s not surprising. We are alerted everywhere: a text message, a phone call, a Facebook message, an email, an app alert, someone coming by the office, external noise outside, and visual noise everywhere. The explicit and ambient signals we are exposed to in a day is staggering. Clay Shirky suggests it’s not that we have too much information, it’s that our filters are failing. I think it’s now both and one reinforces the other.

Coming back…a look at systems

While individuals are distracted, they are products of distracted systems. To look at one part of the science zombie situation, professors are now asked to publish more than ever, get grants from a dwindling pool, teach more students than ever and in more crowded conditions and with greater social needs, and to find ways to make their research more accessible to different audiences while engaging more with the communities of interest affected by that research. All of this takes time. Add to that the probability that the professor her/himself has to raise their own salary and that the only way to do this is to be very successful at the above-mentioned tasks and you get someone who is stressed and overtaxed.

Mindfulness-based approaches do not change any of that, but they can help strengthen the filter. By being more individually mindful, but more importantly create mindful organizations. Building resilient tribes of social innovators and the leadership communities to steward them is another. Granting ourselves the time to reflect, sensemake and listen to the systems we work in is also key. By listening better, we are better able to design systems that are innovative, responsive and humane by building them to human scale.

All well and good you might say, but how? That’s what’s to come in some future posts as we look at designing better systems and making them more attractive so people stay engaged.

Stay tuned….and watch out for zombies.

Photo credit: Zombie Walk 2012 SP by Gianluca Ramalho Misiti used under Creative Commons License

art & designbehaviour changedesign thinking

The Literacy of Change

on October 14, 2013

Making Change

Making Change

It has been said that change is the only constant, yet for something so pervasive change is a remarkably thorny and poorly understood concept. One reason is that change is often approached as a set of facts about a static state of affairs instead of as a literacy, which at change in a far more dynamic context that reflects human systems more accurately. 

A summary of the literature on behaviour change research shows an enormous push towards cognitive rational models of thinking and acting. In brief, a cognitive rational approach to change posits that we acquire information; process that information’s relevance, timeliness, (possible) completeness*; and fit with our personal context and then usually make plans to change. These plans, as described in the Transtheoretical Model and related theories include a series of stages of change:

  1. Precontemplation: We are not even thinking about making a change
  2. Contemplation: We are considering making a change in the next 6-months
  3. Preparation: We are currently planning to make a change in the next 30 days and are taking some steps toward making that change a reality
  4. Action: We are actively working to make the change happen
  5. Maintenance: We are strengthening the new changed state

To the rational mind, this makes sense. Like other cognitive rational models of change like the Health Belief Model, Theory of Reasoned Action and Planned Behaviour, and others, this model assumes change is linear, straightforward and planned for. While some changes are planned, many are not. In a review of the literature on smoking cessation, Robert West and colleagues found that more than half of smokers quit without going through these stages or having any quit plan in place.

West and colleagues have since developed a model called the Behaviour Change Wheel that aims for a more nuanced, less prescriptive model for understanding change.  The Wheel is a refreshing model within a sea of linear stage or stepped approaches, yet still is an approach that encourages behaviour change to be deconstructed into parts first, then assembled to a whole. Complex systems — like much of what humans create individually and socially — are highly resistant to having linear frameworks imposed on them.  This is why many approaches to change fail to meet expectations.

Viewing change as a literacy

What if we stepped back and took a look at change a little differently.

Language is among the most adaptive, dynamic, change-oriented system we engage with on any day thus, it might provide a model for considering change. If I am trying to explain something to you there are myriad ways to do it. By using my words in different combinations, with different tones and cadences, and add some visual thinking to the mix and I create a potent method for communication.

Learning a language requires a lot of failure, many awkward phrases, and a complex array of trial and error, repetition, and luck we eventually learn how to communicate. Depending on the task at hand, we learn the language skill that matters. For someone looking to learn how to navigate a tourist area in another country, a set of basic phrases might suffice. For someone else, getting a technical job in a global organization might require a far deeper understanding of the language. In our efforts to change ourselves, our organizations and our communities we will find ourselves requiring different levels of skill and ‘good enough’ will look different from situation to situation depending on who we are talking with.

Frequently, we are talking to different audiences at the same time to take the metaphor further.

Design (thinking) change

We learn languages much like designers apply design thinking. We scope out our intended purpose, craft a strategy, prototype, evaluate and redesign accordingly until we get something right. Over time we get enough feedback to understand deeper patterns that allow for more sophisticated experimentation. If the feedback quality is high, we learn faster and more deeply.

Learning is by its very nature change. Language is applied learning; you can’t ‘theoretically’ learn a language — it’s useless without application.

Language learning also requires attention to learning on multiple levels simultaneously. It involves small, moment-to-moment interactions, something I call ‘micro-feedback’. This is akin to mindfulness-based approaches to innovation. By establishing a sensitivity to the situation, creating the means to reflect often on what is happening while it is happening without judgement, we create the means to observe ourselves behave and make modifications as we go. It allows us to provide the kind of rapid prototyping of our learning as we go.

It also requires macro-feedback mechanisms that focus on the bigger picture. Language is not just about words and sentences, but a larger way of phrasing that separates being ‘well spoke’ for just ‘speaking well’.

Viewing change developmentally

If change is a constant, viewing change as a persistent, ongoing process changes the way we look at it. By looking at change as a core feature of a complex system — one that brings together linear and non-linear elements, is constantly evolving, and involves random, planned and hybrid elements – we can see change in a manner that fits with complexity, rather than works against it.

Just as our language develops over time, so does the way we change. Viewing change as something that parallels the way we approach language might just be truer to the way we really change the way we want change to happen.

References:

Bridle, C., Riemsma, R. P., Pattenden, J., Sowden, A. J., Mather, L., Watt, I. S., & Walker, A. (2005). Systematic review of the effectiveness of health behavior interventions based on the transtheoretical model. Psychology & Health, 20(3), 283–301.

Michie, S., van Stralen, M. M., & West, R. (2011). The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implementation Science, 6(1), 42.

West, R. (2005). Time for a change: putting the Transtheoretical (Stages of Change) Model to rest. Addiction, 100(8), 1036–9.

* The argument for completeness of information is based on the often flawed assumption that we know what is missing from an informational context and how it fits with the other data we have before us.

Photo taken at the Heidelberg Project in Detroit, MI by Cameron Norman. Original art by Tyree Guyton.

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