But wait.  While mind-numbing as so many organizational rituals can be, aren’t these status meetings a chance to think?  To question status updates that may contain a hint of shift?  To think is to learn.  To think is to be intentional about questioning our predictions.  If the world around us presents us with unexpected information, it gains our attention.  This is how we are wired, but our attention is generally focused only on this ‘exception handling.’  We have to exert ourselves to devote attention to the status quo, to look for minor signs of shift.  Our brains are fantastic at predicting the effects of our movement through our immediate environment, most likely the purpose for this predictive ability, but are famously also able to trap us in bigotry, mistaken assumptions about abstract concepts such as economics or love, or to help us miss out on opportunities to learn.

The picture here represents one of the great corporate slogans from over 100 years ago: Think.  In all things, focus the mind on questioning its assumptions, its expectations.  Our world is famously unpredictable, thinking moves us from reacting to the potential for proactive change – to a place where we notice the quiet signals in our environment that deserve our attention and imagine change.

Today we honor a man who shared his Dream with humanity.  Who demanded we think about our actions, our assumptions, and to change the nation’s ways towards a moral path.  To dream is to think.  To think is to question.  What do you question today?

The author goes on to posit that our social capital management is probably the same offline as offline.  All these efforts to identify behaviors and set expectations for enterprise social behavior is misguided, we’re making things too complicated.  Invariably, (although not in the piece I reference here), we come to impugn the motives of those who are “making things complicated.” The author, as I say, does not fire that bullet, but sums up thus: “Maybe we are just doing what we’ve always been taught to do, to share and cooperate with one another.  If we tap into these simple ideas, all enterprise social software is doing is taking advantage of the way most of us were brought up.”

Ahem.  In addition to reflecting almost none of the case studies of enterprise social software, the author of this piece misses two critical points: your workplace is not your neighborhood, and the cup of sugar examples fails because sugar-sharing is a 1:1 endeavor, while the Word problem work-around sharing is 1:n.

Taking the second point first: You are much more likely to share assets, resources, knowledge, etc., when approached and asked within the context of an individual’s need – than you are to “share” with no immediate reciprocity or other statement of value.

In other words: you may give your neighbor a cup of sugar upon request, but I doubt you place cups of sugar outside your door on a regular basis.  Nor would you drive to the mall and leave a cup there.

The mall?  To my first point: Yes, the mall is another created social construct, just like your workplace, that drives certain behavior.  When we place ourselves into purposeful social constructs, such as a mall or a workplace, our identity / role / time management (etc.) all change.  The mall is designed to facilitate retail commerce; dropping bags of sugar hither and yon would, among other things, violate the intention of the sugar merchant therein.  Similarly, in your workplace, you are motivated by what is measured and valued. For many reasons, there is a gap between the rate and quality of what is should be shared for organizational value and what is actually shared.

Understanding the organizational incentives, and the degree to which they force us away from our natural good nature sugar-sharing selves, is critical to solving this gap. Social constructs and contexts matter, and comparisons invariably fall down when they ignore the context.

But on this day, I answered the phone.  On the other end I found an individual conducting a survey on behalf of Freddie Mac and Fannie Mae.  For reasons I can neither recall nor fathom, I listened and agreed to participate.  Once told of the subject, I told the person that I had no connection or experience with these organizations.  It turned out, that did not matter.  She continued to ask me questions about the firms (whose names she read en toto for each question for the next ten minutes); probing all around my completely vacant perception of them.  I wondered aloud how useful this information was, and briefly considered making up outrages or plaudits just to make her day more interesting.

Today, there are new stories about these firms’ attempts to improve their branding and message.  I suspect my interview was part of that, and no doubt rolled up and considered insight into the public mind.  Some unnamed (and named) consultants made serious coin analyzing these results and suggesting ideas to improve the numbers.

How does my experience resemble political polls, which today make up approximately 67% of all news stories? (Statistics are fun to make up, try it yourself!)  How do people respond to questions about how they will vote in a little less than a year?  How many of them take that call as seriously as I took my Fannie Mae / Freddie Mac survey?  How is it so many people still use landline phones, apparently the only method by which these survey firms reach people?

A student of mine opined recently on the qualitative method by declaring it inferior, only useful for setting up the hypotheses for more grownup quantitative methods.  These quantitative methods feature, often, scientific polls with established margins of error.  Far better to consider the aggregate of poll results, careful diced and analyzed; over the anecdotes and full narrative of experience.  Such is the domain of the soft science.  Where “data” relies on those people who are eager to give honest answers to a stranger interrupting their day with a ten-minute questionnaire.

I don’t mean to impugn completely the survey method.  I just wonder how much of what passes for ‘data’ should be taken with a few grains of your favorite seasoning.  Layering time-honored mathematical models on top of an individual’s representation of their thoughts and intentions may not affect, it turns out, the quality of that information.

On occasion, I am honored to present a three-hour course on decision science as part of a regular seminar for senior feds who are in important jobs.  I once heard a comedian remark that absolutely nothing is worth doing for more than two hours, but while the gentleman obviously is not a football fan – in general I have to agree.  I always approach these speaking engagements with some trepidation, knowing how little I enjoy sitting through multi-hour training sessions or other Festivals of Talking Heads.  One of the compelling things about the Ignite series is the fact that speakers have to be off the stage in five minutes.  TED talks are worthwhile partly because their speakers take up no more than twenty minutes of your time.

Plenty has been written about PowerPoint etiquette, how some styles actually prohibit retention.  This comes about when you put a lot of text on a slide, and then compound the injury by reading the text to your audience.  This almost guarantees low retention, as the brains in your audience do not know whether to focus on reading or listening.  More often than not, they tune out.

Relying on the good work from Garr Reynolds (“Presentation Zen”) and Nancy Duarte (“Slide:ology”), as well as other research on how brains behave, I try to follow a few rules when I can.  One is to surprise the audience every ten minutes or so – although I can’t promise I always succeed at this one. The other is to use eye-catching photos and very little text.  My presentation at this seminar consists, for the most part, of embedded videos (it’s always nice to give your audience a break from you) and slides that are mainly a photo with a pithy phrase.  I don’t even read the phrase on each one, preferring to tell a story or anecdote that demonstrates the point of the slide – or sometimes offering the dry theory with a pointed reference. “Emotion plays a central role in decision-making, when we ask an expert to relate the decision logic they used in a specific situation, they lie. They don’t mean to, they can’t help it because so much of their personal decision process is unknown to them.”

What drives me to write this on a rainy football Sunday?

Well, I wanted to share with you the result of an experiment I ran this past week.  Mindful of the retention theory, I chose to demonstrate it in practice.  Since I didn’t think of it until the morning of the presentation, I went without a net.  At the end of the three-hour presentation, I showed photos from the course without any text.  One at a time, five in all. “Tell me what you learned while this slide was up.”

During the breaks, a few students asked if there was a reason for the strange approach to PowerPoint (I didn’t have the heart to tell them it was Keynote).  I had set this up perfectly, and the disappointment would be crushing. I dreaded silence, blank looks.

The class knew every slide.  By the third one, they were answering in unison.  This wasn’t just the eager students at the front of the class; every one of the 20 or so in the audience could speak to the message given on slides they had seen once, briefly, and then not again for over two hours.

I had a conversation last week with someone on Facebook who argued for the ‘standardized’ project brief format.  We all know this one.  The position was that every project used a standard brief format, the information was on the slides, and the briefing team did not spend excessive time creating unique content.  I sympathize with this approach, but cannot escape the fact that my little experiment demonstrated the theory.  If you think the ‘creative’ approach to slide-ware is not worth your time, so be it.  But if you are briefing people with some interest in having them retain your information, I dare you to repeat my experiment.  Be careful if you do, however.  Now that I’ve seen this work in person, it’s going to be hard to go back to boring my listeners.

——

Photo from Rob Lee’s collection on Flickr: http://www.flickr.com/photos/roblee/374517948/

Far more heard the phrase and thought:  Since when does America fight from the back of the pack?  Leading from behind makes no sense!  The mental image was a platoon where the leader is marching behind his troops, or placing a steering wheel in the rear of the car.  The metaphor was jarring and we stopped listening to one another.  Not only did the phrase fail to trigger upsetting mental images for me, I failed completely to appreciate how many people would respond to the strategy.  Having immersed myself in the implications of complexity in policy analysis for several years now, I no longer hear things the same way as before.

I am Beltway.

This is a town that lives on the shared metaphor – We declare war on drugs, war on poverty, and consider the energy crisis the ‘moral equivalent of war.  For a President to fight an actual war in a way that sounds ‘unAmerican’ violated a shared metaphor for many of us.

What’s the role of metaphor in our understanding?  Lakoff & Johnson claim that understanding ‘takes place in terms of entire domains of experience and not in terms of isolated concepts.’  We cannot separate our understanding from context, and our context is extraordinarily personal.  You can try to influence how someone understands your message, but you cannot enforce the metaphor they use to understand it.  Nevertheless, you should be at least aware how your words may trigger a metaphor broadly shared everywhere in the nation – except for inside BeltwayTown.

I’ve been away from blogging for most of 2011’s summer.  A summer that found Beltway Town struggling to place their policy objectives into metaphors that would stir the voter – or at least the voters who are called by pollsters.  We heard of hostage-taking, credit card limits, and blank checks.  Marketing and politics seek to establish shared metaphors in order to persuade.  Some decry the language and wonder why we cannot just agree on data used for our self-governance experiment – including yours truly – but this leaves the metaphor-fit exercise to the individual voter.  It is inevitable that as our politics become increasingly divisive (a regular campaign season event), the effort to enforce and influence a shared metaphor will increase as well.

The effort to navigate through personal metaphor is a personal one, and requires intention.  The effort to avoid triggering unintended and unflattering metaphor requires understanding on all sides.  More to the point, understanding requires continued conversations with those who do not share your viewpoint.  Challenge your metaphors by conversing with those with whom you disagree – lest your personal context obscure truth.

—-

Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. Chicago, IL: The University of Chicago Press.

Outside the workplace, people and technology have co-evolved.  We Facebook,” we text, we tweet, some of us “check in,” all while listening to music that is streaming to us on customized or micro-segmented “radio” channels.  We connect with friends long moved away, we coordinate over space and time and find projects and opportunities – and occasionally love (authorized and not).  These are not the people we were five or ten years ago.  Certainly not the people we were twenty years ago.  This is not a good or bad thing, despite regular claims that Google or Facebook or Twitter is the latest thing “making us stupid.”  It just is.

For example, I own a Pizza Acquisition Device.  No, really.  I speak into it, saying “nearest pizza” and it shows me the phone number to the pizza place nearest to where I am standing. One click, and I’m talking to the nearest pizza professionals. It’s pretty cool, you probably have one too.  Thanks to a simple mash up of my “phone’s” microphone, GPS chip, and internet connection with Google’s use of computational linguistics, machine learning, voice recognition, massive geocoded databases, etc. – plus the dialing function of my phone – I can always find the nearest pizza.  (This is not strictly true, as the nearest real pizza is 250 miles away in Brooklyn, but go with me on this.)

Imagine if someone came to me with the need to gather functional requirements.  “I understand you want us to build a pizza acquisition device.”  The result would be, I imagine, a fairly expensive and clunky unit that I would wear in some fashion.  It would not be as elegant as my iPhone, because it would begin with what I think I need absent the technology experience.  The difference between a platform and a point solution is salient here, but I am making a different case:  I am co-evolving with the technology around me.

I saw an article recently detailing how Google spent some time considering how their voice search would work, presuming that people would speak to it as if it were a friend, in full sentences.  Turns out they need not have worried – we’ve already been trained to speak in search terms.  I don’t say, “Hey, I’m standing here in downtown DC, do you know where I can find pizza?”  Automatically, without thinking about it much, I instead say; “nearest pizza,” because I know how search engines work.  We all do.  Google found that the majority of their voice searches are framed in short phrases, as if they were typed into a search box.  Google has trained us on how to speak to the Google machine.

If we are trying to ‘engage stakeholders,’ let’s start with where they are, and recognize that they are evolving based upon their regular interactions with consumer technology. (Keeping in mind the ever-present but often overlooked ‘digital divide,‘ not everyone has the opportunity to evolve at the same pace.) In the public sector, this means understanding that even “non-technologists” have become masters at using smart phones, auto navigation devices, music streaming services, etc.  Ignoring this means you are starting not on the 1-yard line, but from somewhere out in the stadium parking lot.

If we are trying to ‘gather requirements,‘ well, let’s begin with the understanding that they are not lying about on the ground like swollen grapes.  Your users aren’t waiting for you with a list of requirements that you can capture and transcribe. In fact, it’s time to retire the verb “gather” with respect to requirements and move from the hunter-gatherer to an agricultural model of civilization: We need to cultivate requirements based on the evolutionary path of users as they interact with emerging and interconnected technologies.  Put more simply: We need to co-design solutions with users who are often unaware of their status as cyborgs.

This is not the first paragraph to question process improvement, this is not some original Eureka moment.  This is a personal journey, and the enormity of the mistake is beyond what I had considered previously. Friends, more erudite than I, have used similar words before – but for some reason I’m realizing, only recently, a simple truth: the implications for the baseless faith in the machine-based approach to management and the firm are global and profound.

A process-heavy enterprise isn’t cold and impersonal – because humans are still warm and social.  Instead, a process-heavy enterprise creates the need for larger social networks.  Formal processes do not capture the natural evolving paths people take to confront their tasks.  In response, people do what is natural, they use their social network to navigate the workplace – looking inward to find others who have succeeded despite the process.  We know that excessive time spent focused inward leads to burned-out employees, who must work the “second eight” to comply with organizational reporting and the like.  On a larger scale, this wasted effort presents – at the limit – an opportunity cost for the enterprise as a whole.  Perhaps the path to efficiency is to set the conditions for processes to emerge at the point of need, rather than Six Sigma-ing the (majority of) tasks that require creativity and agility.

In the famous early mistakes in business process re-engineering, managers believed once their processes were “streamlined” and “documented” (and embedded in enterprise software tools), they could realize savings by reducing the number of humans.  For routinized tasks, this may be a reasonable assumption – however, what percentage of your workday is routine?  Look to your own environment – do you rely on your social network to find the informal work-arounds for corporate process?  When faced with a challenging problem, do you find solace in the documented process?

Work to Rule. In labor relations, there is a term called “work to rule.”  Simply stated, this means that union workers have a negotiating tool that enables them to paralyze an enterprise – by merely doing only what is considered ‘by the book.’  No creativity, no work-arounds, no focus on task accomplishment – just fealty to the process.  Consider this message:  the way to crash some enterprises is to do what is expected by procedure manuals and process charts.

Business Development. In one company, I observed a set process for preparing contract proposals:  with clear roles, authorities, assignments, formats, and process steps.  Chokepoints were established along the way, when “pencils” down would precede a murder board review to assess the quality of the proposal against the procurement specifications.  These comments were returned to the writing team, who would tackle their task anew. The information technology consisted of shared folders, and the writers laboring over each section would be required to post their documents in the appropriate folder at the required hour.  The work was intense and draining, writers were often unaware of each other’s work, and the review team invariably excoriated the team for the lack of a “single voice” or “storyline.”

In another company, the proposal response was visible at all times to the entire proposal team.  In a shared online space, the sections were worked in parallel, each writer able to observe the other’s ongoing work.  The team met daily to talk through issues, but kept in touch throughout the process through instant messaging and email. There were roles and authorities, assignments and formats here as well – but the process was determined by the writing team, and emerged and adapted based on the demands of the work and the schedule.  As the storyline evolved transparently, there were fewer surprises, people were able to lend value across the work throughout – and the end product was coherent and compelling.  This without a review team’s intervention.

Software Development. In software development, Agile methods are triumphing over waterfall or other linear methods – users are happier because their approach to their work changes as they learn what is possible from the technology solution.  The human and the software evolve together.  The old approach was to gather what people thought they needed, build the software according to specifications, and then train the humans to operate the solution.  There may be a correlation between how much training is needed and how disconnected the solution is from how people work.  When software methods allow the humans and technology to co-evolve, when humans are co-designing the solution during “development” – we seem to have happier humans.

The thoughts bouncing in my head now are:  what needs to be in place to allow for emergent processes? Formal process has a small place – compliance processes dictated by, for example, government regulation come to mind.  However, value-creating processes must emerge from the interaction of the work and the humans.  They cannot be formalized absent the humans or the situational context – if they are, then humans will circumvent them, creating a more inefficient enterprise… or follow them to the letter, and destroy value.  In a real sense, process improvement should be replaced by process enablement.  Let the approach to work emerge from the situational context.

Our holiday toasts often feature a few seconds of silence.  We aren’t grasping for words, we are connecting to memories that predate you.  We mist up easily for the same reason.  We smile at soiled toddlers because we remember the stress when we were first confronted with tiny people – you.  (Also, we are no longer responsible to remove said soil. Our joy in reminding you of this is unceasing.)

I found myself at a large sing-along last week in a small town North of Boston.  A dear friend has hosted these gatherings for over 15 years, such that now their 18th century home bursts each holiday season with guitars, pianos, a harp and violin, and nearly one hundred voices.  I was privileged this year to be holding one of those guitars, and was therefore provided a front-row seat to enjoy these many souls.  Their ages ranged from six to eighty.  The young teens sprawled like puppies for a third of the room, while the adults stood towards the back, nearer to the wine selection located back in the kitchen area.  The smiles were shared: for one evening there was no toddler whine, no teen angst, no mid-life crises, no fears of mortality, no tears of sadness.  There was only laughter, music, warmth, and love.

While all had a good time, the Olds had a better time.  Only looking back through years can one appreciate the joy of connection.  In looking across the room, I saw myself at each age – from the shy child, to the teens who only gain confidence in groups, to the later awkward attempts at self-expression, to the college students, to the young fathers, to the truly confident Lions at the peak of their game, to the Olds.  We all wonder what is next, but for the Olds that question has been answered many times.  For this one magical evening, there were no questions of what is next – there was a sharing of magic, song, and later, dance.  The season features moments like this.  When all ages are joined in the same laughter, when a stranger wandering into the home would feel right at home.  Only the Olds appreciate how rare and wonderful such evenings are.

Here’s to the holiday. Here’s to the child on Christmas morning, the young teens exiled to the kid’s table, the older teens laughing too loudly at play, the Lions reveling in their ability to sustain a home.  But more than all, here is to the Olds.  Who have lived each phase, and only now fully understand we are all One.

In the never ending search to know “what works,” we have a few choices.  We can look to theories, i.e., this ‘should’ work; or we can look to data.  Often the latter choice is considered backward looking, or stripped of context.  Data autopsies are conducted with the results analyzed and presented as a ‘case study.’  Here is what happened with BP, or Enron, or the 111th Congress.

The former choice, relying on theoretical principles, is considered by some more noble and can be expressed simply:  spread democracy, protect the borders, cut taxes, etc.  Theories that are believed to represent fundamental levers of reality – when pushed in a certain direction, desired outcomes result.  These theories are often referred to as ‘common sense.’  Of course, yesterday’s common sense included such principles as racial inequality, ignorance to environmental stewardship, ever-rising housing prices, sexual preference as a preference, etc.  It takes frightening shocks to the system to shake our faith in such levers.

Yet, ever hopeful, we press on to learn what levers control our universe.  What works, and why?  And how can we scale it?  The answer, I believe, comes from data.  But not just any data.  And not through data autopsy and case studies.

Take education.  We can approach improving education as a principled journey, applying common sense: reduce class size, return to single-gender classrooms, dress them up in uniforms, etc.  Or we can turn to data.  Yes, we can do both, but levers must be informed and confirmed by data.  As a friend tells me: The data must precede the framework.

In education, however, we have a paucity of data.  In a conversation with a senior official at the Department of Education last year, I discussed our shared idea of data platforms until he stopped me mid-sentence:  “You’re assuming we have the right data.”  No, I didn’t, but he was right.  I was designing the platform before taking on the fight to tease out relevant data about student performance.

Even that phrase, student performance, is loaded with assumptions.  Performance as measured by what? Standardized tests?  Only last year did the majority of U.S. states agree to a common set of performance standards – and only then applicable to middle-school math and English.  As to how students are assessed against these standards?  That remains in debate, currently there are two clusters of states reviewing approaches to common assessment regimes.  We are years from a U.S. approach to these fundamental levers for K-12 education:  What is the standard against which student performance is measured, and how is that performance measured?  (I should acknowledge a competing theoretical construct that opposes any national approach to education – again, I seek the data here.)

It gets worse.  Institutions of higher education find an increasing number of applicants, year over year, lacking in the skills needed to succeed in their first-year studies.  The resulting ‘remediation’ classes are nothing more an extension of high school.  However, talk with those in the field of education, and they will tell you that K-12 schools have no common tasking from higher education regarding what is considered an acceptable skill set.  While we work to get to a U.S. approach to these fundamental levers for K-12 education, this effort is not coordinated with the expectations of universities and colleges – who themselves do not agree on the answer to that basic question.

It gets worse.  A recent study by IBM surveying CEOs found that the most pressing challenge is the complexity of their enterprise and industry, and the most necessary skill is and will be creativity.  The ability to think critically, understand variables, and make decisions amidst uncertainty.  Meanwhile, the fundamental levers we believe are necessary for K-12 education are descendants of the Trivium – the triad of grammar, logic and rhetoric developed first to shape medieval liberal arts students.   A consortium of technology companies are working to develop the definition of ‘21st century skills’ they believe are necessary for their incoming labor force – but in the radically localized Education field, there is no King to accept their input.  One large government contractor laments:  we would like to remain an American company, but we need 70,000 engineers over the next ten years.  How can we accomplish both goals, when only one represents shareholder needs?  A senior education administrator meekly suggests the adoption of international standards, PISA, as a baseline for common standards only to be scolded by a peer; “But this is America!”

How do we untangle education?  By fighting over which fundamental levers matter, or turning to relevant data?

There is hope.

A student returns home from a day struggling to master Algebra as her teacher struggles to increase comprehension, while not ‘teaching to the test.’ The results of this test will drive the reputation of, and government investment in, the school district.  The reputation of the school district will drive housing prices, and shape neighborhoods. All are exhausted by the end of the school day, but the data collected at the point of learning remains tiny ovals filled in by a child’s number two pencil.

Returning home, the student unwinds by loading up a multi-player online immersive video game.  The players navigate a complex environment, their interactions driving the direction of the game, as the game algorithms respond to player progression through the landscape.  Each move is measured, assessed, and the game evolves along one of a thousand paths – this path of learning is determined by the player’s interactions, both with their computer environment and with one another.  The players are connected via voice connections, as they work as a team to navigate the game’s landscape – often matched up against a set of adversaries, a mirror-image team tackling the same challenges and competing with them.

The next morning, the student loads her textbook-laden rucksack and trudges off to sit in a classroom designed during the Victorian-era, hoping to color in the ovals correctly before Christmas.

Which experience better prepared her for the ability to think critically, understand variables, and make decisions amidst uncertainty?  What data matters in this story?

Let’s start here.

Yeah, I was appalled too.  Turns out it’s called there “The Learning Sciences,” and while I don’t know when it started to gain traction, people in education somewhat recently started to compare the education system we have with the stuff we’re learning from cognitive science, sociology, etc.  Pretty exciting stuff, and I can’t help but compare this welcome attention to interdisciplinary studies to the breakthrough in economics when – RECENTLY – leading economists began to realize that people are messy and don’t have consistent utility functions.  (In both cases, the system failures become a tad obvious using this lens.)

So the world is changing.  All around us.  One meme in education making the rounds is, attributed to The Learning Sciences:  “All learning is social!”  As someone mentioned this weekend on Twitter: The learning that isn’t social, isn’t worth our time studying. This remains controversial – what about human instinct, core behaviors, the idea that some of our personality traits may be inherited?  Surely these aren’t learned! But then we read that an infant, long before she can understand a language, is able to discern WHICH language is spoken by her tiny tribe.  And before she understands that she belongs to the same animal group as her parents and siblings, she can discern individual faces among primates.  Once she learns that she is one of the naked apes, the individuality among chimpanzee faces becomes invisible to her, as it is to us.

Ponder that one for a minute.  Heady stuff.

This weekend, I was struck by a logic stick.  If all learning is social, is all social learning?  We know this is not automatically so, learned that in the intro to Logic, Sets and Numbers (an actual college course I took in the 70’s).  But when we engage in a social setting, online or offline, are we ever not learning?  Let’s add in a third statement: we are constantly learning.  Even while asleep, some research indicates, the brain assembles and makes sense of what it experienced that day.  There isn’t a time when our brains aren’t rewiring themselves based on input from our environment.

We learn something from every experience.  If events occur as predicted, we reinforce that cognitive pattern for the next use (naturally, we have the ability to learn the wrong things here).  If they do not, we reconsider our pattern assessment logic.  We descend the stairs at 3 am differently once we learn the fourth step from the landing squeaks now – and will subsequently do that in another’s home without thinking.

So we’re constantly learning, and all learning is social.  (Is it?  We learned that squeaky stair avoidance thing on our own, didn’t we?  Hint:  No.)

Enter social media!  What is your social media strategy?  Does that question even make sense anymore?  Or should we ask now:  What is your learning strategy, and what role is played therein by social media, happy hours, phone calls, email, downtime, etc.?  If all social is learning, shouldn’t any associated strategy for socializing tools be focused there?

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24 Nov: Update, thanks to the great comments I’m getting here.  Here is a another great resource exploring this notion that all learning is social, and questioning the value of corporate training methods as a result: http://www.lifescapes.org/Papers/0212_from_training_to_learning.htm