Month: February 2010

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Indispensibility and Organizational Change

Seth Godin‘s recent book throws out the challenge to its readers to be indispensable in the jobs that they do. This is a tall order for most, but Godin points to ways of thinking, approaching problems and examples of how even the most mundane, mechanical jobs can be more when we bring the best of ourselves to what we do each day — no matter what the job is. He wants us all to reclaim our genius. The message is an unusual one in that it applies very well to individuals — you and me — but is a lot harder to apply at the organizational level. This is an important issue for those wanting to create better, healthier systems and it is here that the role of individual and system can get confounded.

Mike Myatt, from Blogging Innovation, wrote a critique of the indispensibility position in terms of its implications for organizations. His post, a fair and appreciative one regarding Seth’s position in many areas, is nonetheless critical of the idea of fostering indispensibility in firms:

A well managed company does not allow itself to become dependent upon the performance of any single individual. Those individuals who attempt to hoard knowledge, relationships, or resources to attain job security should not to be valued or viewed as indispensable, but should be admonished as ineffective and deemed a liability. Corporate talent that cannot be shared, duplicated, distributed, or leveraged is not nearly as valuable as talent that can.

It is here that I first disagree. Godin is not advocating for valuing the hoarder, rather he is suggesting the opposite: unparalleled sharing and generosity. Someone who hoards will not advance system change: period. Systems rely on exchange of information and intense conservation of knowledge or information reduces the response capacity of a system (which could be an organization). An organization that relies on a hoarder for survival hasn’t been paying attention or created processes of openness that allow information to move through the system. If you have a hoarder, one needs to ask: how did we create an organization that enabled that person to become so important? How can we transform it so that person’s unique talents can come out and that knowledge that is sharable and distributed gets to whomever it needs to when its needed?

I would like to address two of Myatt’s issues:

Myatt goes on:

In fact, I would go so far as to say that anyone who sets out to make themselves indispensable would be the one committing career suicide for two reasons:

  1. Anyone who is “perceived” as indispensable in their current role completely eliminates any possibility of promotion
  2. Any good leadership team who finds themselves dependant upon a linchpin will immediately move to mitigate the risk of finding themselves in such an untenable position

Regarding point 1: What would one promote themselves to? This pokes a hole at the dominant model of organizational development that suggests that promotions work vertically (including the entire thinking about why we need directions to move, embedded in the term “promotion”). When you’re the best salesperson on a team doing something you love and are good at and you get a “promotion” does it mean pulling you off the sales team into a management position, which may rely on a completely different skill and mindset? Does this really make sense?

Regarding point 2: If you have a real linchpin, your task is creating a dynamic, exciting environment to let them do their thing well. After all, they are linchpins precisely because they are good at what they do. You’re always in an “untenable position” of not being able to replace them because they are, by definition, unreplaceable. Do you have a work culture that brings in unique talent and nurtures it to allow it to succeed or do you try to create positions that are defined by a set of duties that can be done by anyone?

Myatt’s argument is counter to what Linchpin is all about in its approach. If you create standards and clearly defined roles and evaluate solely based on those standards, which is the position that is being argued from, you will suffer under a linchpin promotion strategy.

Maybe. At least, your business model will suffer.

But that misses the bigger point: Why build an organization around such a model to begin with? Maybe the system needs to change as much as the individuals within it. Maybe then, a linchpin promotion strategy doesn’t look so strange or problematic.

design thinkingpsychologyscience & technologysocial mediasocial systems

Creating Sticky Networks

 

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

But more can also be a problem.

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

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

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

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

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

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

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

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

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

1.      Create frequent opportunities for interaction;

2.      Ensure frequent and regular interactions between agents;

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

4.      Interactions are minimally competitive;

5.      Interactions are maximally cooperative;

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

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

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

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

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

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

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

education & learningresearchscience & technology

Innovation & Education: Solutions?

 

The last couple of days I’ve been posting on issues of discovery and innovation and its ties to higher education pointing to a lot of the problems associated with the way that the scientific enterprise has been organized. These are complex problems because there is no one solution to them and no single cause. A confluence of policies, practices, assumptions accompanied by a culture that is rather resistant to change (despite being in the business of research, which is all about creating NEW knowledge).

It is one thing to identify the problems, another to articulate their scope and impact, but nearly all of that is moot if there isn’t action for change and some strategies for moving forward (or at least some other direction). So what are some ways in which we can take the current system, work with its strengths, and propose something different that shifts the standards, while doesn’t provoke such pushback that it can’t move forward without an unreasonably high amount of energy?

Any examples out there of examples where universities and research institutions (including funders) have got it right?
I’d love to hear your ideas while I look for some solutions and examples of my own.

design thinkingeducation & learningpsychologyresearchscience & technology

Innovation and (Higher) Education

 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

education & learningscience & technologysystems thinking

Scientific Discovery, Innovation, Creativity and How We’re Killing It

 

The black hole visualization above might be more than just a depiction of something in the outer regions of space, it could be an apt metaphor for what is taking place in our research institutes and universities as far as young scientists are concerned. As a young scientist and innovator(?) (* I’ll come back to that term later) this is a deeply personal issue so keep this in mind as you read on. I am also an educator and responsible for training a new group of scientists, health practitioners, and social innovators in public health — our the future discovery agents — and it is in this latter role that I am most upset and passionate about the issue that is befalling scientific research:  a systematic strangling of opportunities for young people.

Jonah Lehrer recently explored this topic in his column in the Wall Street Journal and on his science blog (“The Frontal Cortex“) and I’m very glad he did. Lehrer points to the widening gap between those who have funding and those that do not (the rich getting richer) and how this trend is hurting researchers at the very beginning of their career —  the time they are most likely to make breakthrough discoveries.

In 1980, the largest share of grants from the National Institutes of Health (NIH) went to scientists in their late 30s. By 2006 the curve had been shifted sharply to the right, with the highest proportion of grants going to scientists in their late 40s. This shift came largely at the expense of America’s youngest scientists. In 1980, researchers between the ages of 31 and 33 received nearly 10% of all grants; by 2006 they accounted for approximately 1%. And the trend shows no signs of abating: In 2007, the most recent year available, there were more grants to 70-year-old researchers than there were to researchers under the age of 30.

My personal experience in Canada is that this pattern is not much different. As the available grant opportunities decrease or stagnate, the pie continues to remain relatively stable in size while the number of people wanting to eat from it grows. And to compound the problem, more researchers are staying longer in the field. As Lehrer notes: if you’re 70 or older you’re more likely to get an NIH grant than someone under the age of 30.What does that say to young scholars?

In order to be more competitive in grant competitions and for jobs, students are considering post-docs and spending a longer time training, paying money into an education and deferring potential employment-related income, with the hope that it will pay off. Recent National Science Foundation data shows this trend:

New doctorate recipients are increasingly likely to take postdocs, and that is evident in the 2006 SDR data: among all SEH doctorate recipients, 38% had held a postdoc at some point in their careers (table 1). More recent cohorts were more likely than earlier ones to have held a postdoc: 45% of those earning the doctorate within the last 5 years compared with 31% of those who earned the doctorate more than 25 years ago.

TABLE 1. Percentage of SEH doctorate recipients who have held one or more postdocs, by years since doctorate and broad field of doctoral study: 2006.

If that payoff is a stable research position and the ability to start up your own research group then they are likely to be disappointed, as Lehrer notes:

The age distribution of NIH grants has significant implications for American science. It has become much harder for young scientists to establish their own labs. According to the latest survey from the National Science Foundation, only 26% of scientists hold a tenure-track academic position within six years of receiving their Ph.D.

Jason Hoyt discusses this further and illustrates the trends in grant funding and asks whether we have too many PhD’s in the first place given this trend? Good question. But perhaps a better question is whether we’re killing off innovation, discovery and creativity by stifling the ability for people in their most creative years to do the work in the first place? And are we discouraging the next generation of young scientific leaders by making life for early career researchers so difficult that talented, creative people self-select out of the applicant pool for graduate school and faculty posts?

The issue of tenure mentioned above is not a moot point. To those outside the academy, the concept of tenure surely seems something anachronistic in uncertain economic times and I certainly appreciate that there will be little sympathy for non-tenured scientists and professors among the public. However, it is worth pointing out that the science and innovation done in research has a time horizon that is not the same as other jobs. A grant takes months to prepare, months to adjudicate (a recent grant I applied for had a deadline of October 15th and the decision will not be rendered for the competition until April), and then requires anything between a year to five to do the research (if you’re so lucky to have funding last more than a year or two), and then at least a year to publish your findings. This rests on the assumption that you get funded the first time and that your manuscripts get accepted the first time around. Neither of these are reasonable assumptions. Yet, grants and publications are the #1 things used to assess success. And if people think researchers get paid too much, consider what 14 years of post-secondary education and training gets you according to Hoyt:

With a PhD, a postdoc can expect to start, at most, US $42K a year in academia and $52K in industry.

I made $36.5K as a post doc and as an assistant professor at a major research university, I make less on an hourly basis than all but my part-time data entry clerk (this includes my graduate student research assistants) considering the number of hours I have to work each week to get everything accomplished. My reasons for doing this work isn’t about money, but at some point for most young researchers who have a mountain of student loan debt from a decade and a half of accumulated education and opportunity costs, it has to be.

The tenure gap also points to another shadow in the system and that is the idea that scientists raise their own salary. Thus, scientists and professors are spending an ever-increasing amount of time writing grants to pay themselves so that there is someone to do the research. In the United States, there exists mechanisms to put salaries into grants, however in Canada this is a relatively rare occurrance. The assumption is that universities and research institutes pay salaries and funders pay for research, which simply doesn’t hold true. Imagine having most of your creative talent spending 1/3 of their time applying for funding to support them in…writing more grants to support them in writing more grants. When does the innovation happen? And when are scientists supposed to be doing all of that knowledge translation stuff that they’re increasingly expected to do?

Another problem for young researchers (and tied to the tenure or long-term contract issue) is that the value of an innovation is only really seen in hindsight, therefore any profession based on innovation requires methods of promotion, retention and acknowledgment that somewhat fits this horizon (even if that is imperfect, particularly in basic sciences where the innovation isn’t always obvious for many years). How can you reasonably judge someone’s contribution based on a short period of time?

Here we have a system that espouses language of innovation without any mechanism to support it or worse, an entrenched pattern of behaviour designed to prohibit it. How much sense does that make?

behaviour changedesign thinkingenvironmenthealth promotionpublic health

Thinking: Why the Word Matters to Systems and Design

 

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

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

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

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

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

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

education & learningemergencepsychology

Social Innovation: Lessons from the Wizard of Oz

After Star Wars, the Wizard of Oz was perhaps the most captivating movie of my early childhood. My Aunt and Uncle were the first people I knew for years who had a VCR (actually, they had a Betamax machine, but you know where I’m going with this) and these were the two movies that I wanted to watch more than any others. Both movies were ‘game changers’ in that they transformed the way we watched films, whether it was the use of special effects, the design of the sets and costumes or the timeless narratives that both stories employed, these were remarkable films for their time and there are many reasons why both are still viewed and loved today. The other thing that these two movies have in common is remarkable characters. Although I could devote an entire blog to Star Wars alone, The Wizard of Oz is more appropriate to invoke when considering social innovation and how we encourage it in our society. [Spoiler alert: If you haven’t seen the movie by some strange chance and don’t want to know about the plot, stop reading here].

The main character, Dorothy, is an amalgam of the three (four, if you include Toto the dog) supporting characters: The Tin Man, the Scarecrow, and the Cowardly Lion (and the spunky, bold, dog: Toto). Their collective journey through peril leads them to seek counsel from the wise Wizard of Oz, who embodies his own paradox of being truly wise underneath a veneer of superficiality and obfuscation. Dorothy is also a representative of social innovation in practice. She is confident, challenges the orthodoxy of the current system, takes responsibility for her actions and for improving the betterment of her world, and works collaboratively with others in the spirit of partnership and goodwill to achieve a much larger, collective set of goals beyond just her own.

However, what makes her actions so powerful is that she, unwittingly, reveals the very best and the truth in those around her. After scouring Oz for a brain, a heart and courage, the Scarecrow, Tin Man and Cowardly Lion find that they had these things all along. Somehow circumstance supported by a larger system made them believe that they no longer had such things. Dorothy, because she wasn’t a part of the system that created these beliefs (having come from Kansas, not Oz), believed otherwise and throughout the movie challenges her friends to see that they really are smart, capable of love, or courageous. She shows the value of being the outsider or thinking differently.

Social innovators are very much in the same situation. They are often told by others who have been tricked by a system to believe that what they are doing is foolish, can’t work or isn’t really good business, or real research, or worthy of spending your best energy on. Yet, because of the Dorothys in the world who don’t “know better”, the flame continues to get lit and the torch carried (forgive the 2010 Olympic metaphors here). When I was doing my Masters degree training in community psychology I recall having a senior colleague, one with many more years of experience than me, laugh and say to me: “you’re so naive and still believe that the system is capable of change. One day you’ll see otherwise”. She meant well. She wanted to save me from banging my head in the wall and getting frustrated and disheartened and confused. I had peers, some faculty, and other leading members of my community say the same thing to me; all with the same good intentions.

Fortunately, I had a mentor in my job who managed to create an entire career of being a “maverick”, or as something I’d call a social innovator. He basically confirmed what the first person told me about innovation being a recipe for frustration, hard work, few traditional rewards, and failure. But he also told me about how it was a recipe for personal and social transformation, how it helped you sleep better at night and wake up enthusiastic in the morning, and how the world would never change if we all believed that it could not, and how it was just plain fun. He believed otherwise and I saw firsthand the good things that he did and the impact that he had on people. Yet, by traditional measures of success, he probably didn’t score all that well.

At least, when you looked day-to-day.

When viewed over the course of a lifetime with the kids, trainees, and staff he mentored and taught? His impact was immeasurable and transformational. Just like Dorothy. Seth Godin would call him a linchpin.

Think about the movie: Dorothy alienates her family, kills the White Witch, manages to put her friends lives at risk, and destroys the cherished secret of the Great Oz that the entire Emerald City believes in all in a couple days work. If we evaluate Dorothy’s actions in the movie, while it happens, she’s pretty destructive. If, however, we evaluate the impact of her actions when looking at the bigger picture, we see someone who brought about the end of tyranny and liberated thousands of Winkie soldiers and flying monkeys from the Wicked Witch of the West, empowered three leaders to realize their fullest potential, and enabled the Great Oz himself to become true to himself while freeing the Emerald City residents to trust in themselves not some great, false prophet. She also found out how much she was needed and loved by all of those back in Kansas. Not bad.

I like this story. It is much like Frank Capra’s “It’s a Wonderful Life” in many respects. It reveals many truths that are not obvious in the moment and lessons that we are fortunate if we can learn in our lifetime.

So will you be a Winkie soldier, waiting to be liberated? Will you allow yourself to find the strengths you have inside and resist the system that tells you that they don’t exist? Or will you lead and teach others that freedom can come and that there is much more inside of you than is often recognized and be the change agent no matter how many Witches fly the skies above your house?

And, despite those witches, remember that those naysayers and ‘enemies’ had a start somewhere and, most always, they were made and not born. And because of that, they can be unmade. (anyone interested in the ‘back story’ of the Wizard of Oz will love Wicked on Broadway or in print).

 

Ironically, just like Star Wars and Anakin Skywalker / Darth Vader.