Bill Snyder on Communities of Practice

Bill Snyder, expert on communities of practice, spoke at the Learning Organization Academy last week. My notes below. For the record, Bill co-wrote Cultivating Communities of Practice: A Guide to Managing Knowledge.

The Engaged and Messy Nature of Knowledge and Learning

Knowledge, according to Bill, is not abstract, fixed, and unconnected from life. It’s “situated, tacit, dynamic;” “social;” and “practical.” It’s interwoven between and among people and what they’re doing and need to do, in the environment where they are. Correspondingly, learning is largely informal, is built on communication and connections—stories, conversations, experiences, coaching. It depends heavily on trust and reciprocity.

Communities of Practice Steward Messy Knowledge

The kind of knowledge and learning above aren’t that well-served by formal education. What works better are communities of practice–groups of people sharing a particular domain of knowledge who gather and talk about what they know and what they do. The emphasis is on social relationships and communication; communities of practice are heterarchical as opposed to hierarchical. There isn’t a rigid power or control structure; they grow up where people who share a particular passion feel a need to talk to each other. They’re voluntary. As such they stand in contrast to the hierarchical workplace, its emphasis on control and outcomes, and its investment in its own existence. They can be “natural” in that they occur on their own when a few people find their way together, and intentional, in that people actively develop them, though this is an art. They can be conceptualized using a three-mode framework: domain (or subject matter); community (the people); and practice (how they apply the knowledge they share).

Peripheral and Core Participation

A key feature of communities of practice is that they allow for a variety of ways to be involved. You don’t have to be an expert: peripheral participation, or lurking, is OK, and even seen positively (because it’s a way to enter into the field—consider the apprenticeship model).  Usually, though, a core group comprising 3 – 5% of the people ends up being responsible for most of the activity of the community; these people are generally experts and well-respected (though there is a role for some in that core group to focus on the organizational details who don’t therefore need to be a subject mater expert). Importantly, the community of practice allows you to shift from lurker to middle to core group and back—in fact, you can see that movement as a kind of sideways Zone of Proximal Development.

Distinction Between Communities of Practice and Project Teams

Bill makes a key distinction between communities of practice, which self-organize to shepherd the learning in a social group, and project teams, which are formed, usually by fiat, to achieve a particular end. The community of practice focuses on knowledge sharing, is voluntary, has a long-term focus, boundaries are permeable, and the nature of the group is often emergent; the team is different—it has a clear outcome in mind, it gathers information on whether it meets that goal or not, it ends, roles are kinda fixed, it reports back. The project team works well in the hierarchical workplace of course; but it’s not antithetical to the community of practice. A project team can peel off of a community and go work on a project then share outcomes with the community. Just don’t assign a discrete, short-term, actionable goal to the overall community.

Phases of Communities of Practice

Communities of Practice go through various stages: Potential (basic parts are there: topic, social group, desire to share); Coalescing (community begins to work together and build trust); Maturing (clarification of the subject, individual roles; identification of gaps in knowledge); Stewardship (focus on action and maintaining momentum, attracting new members, keeping knowledge up-to-date); Transformation (its work may be done; members may leave; it may go dormant to return later).  Bill notes that it’s important to accept the community where it is—the stewardship phase isn’t necessarily the ultimate goal, for instance: a community may function perfectly well and serve its members even in the early stages.

Things to Avoid

There are some things you shouldn’t do if you want your community of practice to be successful. You can’t tell it what to do—the passion has to come from the people involved (although you can find and build on existing passions). You need the domain to be somewhat practical and problematic; if it’s too superficial—that is, only about relationships and pleasantries, it won’t work. The topic also can’t be too narrow or too broad. You have to be wary as well of problems that occur in all communities: cliques and factions, and people who “squelch” or “spoil.” And a key pitfall: “impermeable boundaries”–if people can’t move from the fringes to the core group and every stage in-between, it’s not a heterarchy anymore.

Communities of Practice Improve Performance

You might think such an ephemeral structure might not result in anything tangible, but it does—those relationships and passions drive the participants to “build, share, and apply” core practices and capabilities, increasing their capability, and all that of course translates to improved performance outcomes.

Chris Jernstedt on Learning

Chris Jernstedt, Professor of Psychological and Brain Sciences at Dartmouth College, spoke Monday at the Learning Organization Academy. My summary of key points:

Learning Organizations Should Map to the Brain

If we really want to build learning organizations, they should of course take into account how the brain works; fortunately, we might already be heading in the right direction: chris notes that the literature on organizational growth and change is remarkably consistent with how the brain operates.

Learning Should Include Thinking, Feeling, and Interacting

The brain’s major regions focus on three key areas: social (watching what other people do, emulating it), executive (making decisions, plans, interpretations), and emotional processing (feeling and dealing with how we feel about things). All three are integral to how the brain works; all three should be a recognized part of a learning organization (consider to what extent cognitive / executive thought is privileged now in most organizations and higher education).

Memory and Learning are Active

“Memory and learning are something you do,” said Chris. Rather than files retrieved from an efficient archive, the process of remembering is more similar, for Chris, to an archeological dig (!). Each memory is a product of reconstruction and re-interpretation (!) of a bunch of scattered bits. And the same for learning: rather than receiving knowledge as a jukebox might receive coins, we’re actually building the things we know association by association.

The Brain is Not Neat

“The brain is built to be sloppy,” Chris said. There’s a trade-off between the kinds of mental structures and processes that make for efficient memory and the kind that allow for creativity; the brain allows some sloppiness and inefficiency so we can make new connections, associate unlikely things, invent our way out of a tight corner. But in exchange we’re imperfect warehouses.

Engage or Forget

The most important thing in remembering or learning something new is to use the information actively. Engagement is even more important than overall time spent. Talk about it, write about, do something with it. Otherwise it’s gone in 24 hours, says Chris; 60 to 80% of your learning should require you to be engaged, he said; and he therefore suggested we use symbols to capture the key points of his talk (writing or images). He also stopped every few minutes to challenge us in groups with a provocative question or two. “The person doing the talking is the one doing the learning,” he said.

Prompts

The brain uses prompts and incentives to help it learn. Prompts relate to its powerful predictive ability: to survive we need to know what effects follow from what causes; we’re so good at associating effects with causes that after even one highly-charged cause-effect sequence, the brain will subsequently predict the outcome of any similar cause and feel and act as if the effect had happened, even if it hadn’t. Every time you see a certain person, they frown at you? After a while you start to feel frowned-at just by thinking of that person. Good learning understands this strong promptability and tries to unpack and discharge prompt-associations that impede learning, and kindle positive ones that encourage it.

The Three Rules of Feedback

Incentives work on the other end of the cause and effect sequence–a positive outcome makes the brain feel good, and it remembers what it did to get that; then it’s more likely to do that thing later. This process is what makes feedback work so well; as long as feedback is useful, consistent, and rapid, you can effectively learn just about anything. Including to control anything the body does–even lowering high blood pressure certain degrees at your will, slowing down or speeding up your digestive tract, or keeping sperm (if you have them) from swimming. These body-related learnings require a biofeedback monitor of some kind and are done in the lab, but still: if you can control the speed at which food passes through your intestines, you can make all sorts of changes in any of your behaviors.

Transfer Requirements

For learning in one situation to be called upon in another, thus achieving the famous holy grail of “transfer,” Chris notes that the first situation needs to be as simliar as possible to the second. And practicing it three times before the transfer helps, too.

Extrinsic Motivation Doesn’t Work; Neither Does “Espoused Theory”

No change will come of telling people what they should do, says Chris. Rather, you have to “give them what they want when they do it.” A useful and speedy reward or some kind of feedback that tells their brain that what they just did was good. A second problem with extrinsic motivation is that the brain isn’t fooled by rhetorical positions, claims, values statements, plans, that are different than the real behavior of the individual who promotes them (see Chris Argyris’ famed “espoused theory”). People’s brains will “see” that a given leader isn’t listening to them, even if he or she espouses an open-door policy (and maybe even if they consciously believe that policy).

Stories are Important 

According to Chris, the story you create is more powerful than truth. If you’re given some pictures and told to tell “false” stories about them (that is, stories that don’t truthfully reflect the contents of the pictures), you’ll remember the stories and not the pictures themselves. Which suggests how important it is that we include stories and narratives in our understanding of the workplace environment.

The Unconscious is Powerful

“Most of what you do,” says Chris, “is unconscious.” As much as 98% (!).  Chris referred to research that shows our brain can solve math problems well before we actually know it. The conscious mind, driving to a speedy conclusion, or incapable of processing all the data, can even impair the whole brain from working: Chris noted a study that showed people who were given some minor task to occupy their conscious mind actually solved complex problems faster than people who were consciously thinking about the problem, showing that the brain has a way of drawing on problem-solving capacities we don’t know about. “The brain knows,” said Chris. The way you tap into this power is to give yourself time. Add periods of unscheduled time into the routine; places for reflection, etc.

The Box, The Trellis, and the Marketplace

We invited community members to come talk about about IT Governance and help us figure out the right way to go about it in our school. As I was listening to the conversation, it occurred to me there were two ways to look at it.

For the record, IT Governance refers to a structured process for campus-wide decision-making about IT policies and services. Like what your LMS is, or how long you should wait before your desktop computer is refreshed, or whether your department or a central unit pays for your copy of Chem Draw Ultra 12.0. When governance works, everyone knows what the campus IT policies are and how decisions are made, and everyone feels she or he can have input into the decision-making process. Even if a particular decision didn’t go your way, you at least know the reasoning behind the decision.

IT Governance as a Box

When you first hear of things like “governance” or “committees” or “organizational structures,” you might tend to think of them as restrictive, top-down organs of control. Your lizard brain throws up images perhaps of misty, star-chamber-like, inscrutable rooms and byzantine processes issuing strange unilateral edicts that are action-oriented and constraining, and focus on products, stress “implementation” and “projects,” and use mysterious jargon that makes you feel like there’s something you’re supposed to know but you don’t.  Things that seem safely removed from the more organic ebb and flow of your daily life, yet there’s a nagging anxiety in the back of your mind that the decisions might sort of pop up at the 11th hour and disrupt what you’re working on—you might discover, that is, that a new presentation software became the campus standard the night before you’re set teach using your well-tried PowerPoint deck, and it no longer works, and now you look crazy in front of your class, etc.

This dread vision is what you might call IT Governance as product-oriented instead of people-oriented. As a system that limits decision-making for efficiency’s sake to a few people, doesn’t include everyone, doesn’t allow for a lot of input, and doesn’t really seek to understand what people do on a daily basis and what their needs are. It’s not about helping people grow; on the other hand, it constrains, no matter how well-intentioned it is, as a box might. I have to admit such an image popped up in my own head at one point, but there’s another way to view IT Governance.

IT Governance as a Trellis

As part of our conversation, we looked at such other IT Governance processes as were easily available on the web. Some systems of decision-making out there are (as you might suspect) amazingly complex; some are less so. Significantly, though, many have features that do not fix the star chamber model. For example, Western Carolina University calls IT Governance an ongoing conversation, that “will occur not just within the governance meeting structure.” Salem State University’s IT Governance web site takes the time to explain the various “sources” of project ideas, which can come through formal channels or even “casual conversation between department heads” (and hopefully other people, too . . . ). The University of Texas at Austin lists the six cardinal values imbued in their governance process, and “transparency” and “communication” top the list.

A conversation? Something that allows for sharing of ideas between equals, that could happen in a formal setting, or in an informal setting? Among anyone? Emphasis on the messy beginnings of new ideas, lurking on the edges of existing projects, that might come from anywhere? Unabashed promotion of communication and transparency? This all suggests a desire to admit a constant stream of destabilizing novelty (or what I call an Information Sluice)! The opposite of the bureaucratic sublime. That’s a governance process that includes people as they are, in their actual walks of life, and invites their input. That’s a governance process that has change and growth built into it, a structure like a trellis, that allows for a plant to bloom in the new, vertical dimension. Not a black box.

IT Governance as a Marketplace

My local community is headed in this direction, too. When we talked about what we want to achieve with our IT Governance structure, the primary idea expressed was “more communication.” “We don’t know what’s going on,” “there needs to be a better way to talk to each other than email,” and “we need people who can serve as nimble liaisons negotiating agreement between areas of disciplinary knowledge and areas of technical knowledge,” were the kinds of things we said.

And we decided that to help with this communication we need a “marketplace,” or an easy way to know what everyone else is doing and see what solutions and problems other people are creating and dealing with. So that we can better build on and integrate our various local initiatives, instead of creating new, parallel, redundant, isolated projects. Such a marketplace, we thought, should be easy to search and easy to add to.

This marketplace sounds a bit like the kind of “ideation platform” or “idea stock market” I’ve mentioned in previous posts. Sounds a bit like the Internet itself, in fact, used as a metaphor of facile connectedness, of grass-roots, horizontal, non-bureaucratic engagement, with low-threshold entry requirements, applied retroactively unto the world itself, the child teaching the parent.

IT Governance as Email Fixer

Just a thought about email, which we thought was the kind of thing IT Governance could help us change. I think it’s a commonplace that our current use of email is less than satisfying, seeing that it is co-opted by everyone for every kind of communication: official institutional pronouncements, lightweight invitations to lunch, your mom to check in on you, your department to remind you about an upcoming talk, to let you know your water bill payment went through, to ask you to come to the PTA meeting that night, to share the project management charter, to ask your boss for time off, to tell you to check in for your flight, not to mention the inundation of unsolicited business-related emails, spam, etc. There’s so much crazy stuff in there opening the inbox is like our own personal version of Fibber McGee’s hall closet gag.

Email is a social problem as well as a technological problem. One where we have to talk to each other and agree on the parts to fix and try things out and adjust those things and ask ourselves to honor new conventions of behavior and give ourselves feedback on how we’re doing and so forth: pieces both mechanical and behavioral, individual and communal. Now if IT Governance can help that to be fixed (as we seem to think it can), that’s a different kind of governance. That’s not about circumscribing behavior. That’s a way to identify and heal problems that go deeper and broader than technology, that’s a meta-view on the way we live life and talk to each other, that’s about finding well-being together wherever we can, that’s about community, that’s about getting issues out into the open, that’s about being vulnerable and trusting each other, that’s the kind of thing that makes life worth living. That’s the kind of IT Governance we need.

Alan Kay, Systems, and Textbooks

Alan Kay give a talk called “Is Computing a Liberal Art?” yesterday at the 2012 NITLE Summit. Here I discuss his key idea: that systemic thinking is a liberal art, and I explain a corollary idea, that textbooks suck.

Kay is attuned to how ideas evolve and are instantiated in the culture and the mind. For him a key piece in this process is the relationship between ideas and the categories we have for them; the relationship is this: if you don’t have a category for an idea, it’s very difficult to receive that idea.

Kay says we’re born with 300 or so preexisting categories that the species has evolved to know it needs to think about to survive, and we’re wired to be looking around for thoughts in those categories (food, shelter, pleasure, etc.). But the story of the last few hundred years is that we’ve quickly developed important ideas, which society needs to have to improve and perhaps even to continue to exist, and for which there are no pre-existing, genetically created categories. So there’s an idea-receiving capacity gap.

Education’s job should be, says Kay, to bridge this gap. To help, that is, people form these necessary new idea-receiving categories–teaching them the capacity for ideas–early on in their lives, so that as they grow they are ready to embrace the things we need them to know. Let me say that in a better way: so that as they grow they are ready to know in the ways we need them to know.

Said he, “If you have a new idea come in and education won’t teach people it from birth, you get a pop culture.” Pop culture! A harsh but fair critique of our society. More on that pop culture below.

For now, what are the ideas or categories, or what capacity for ideas should we now be teaching? Kay has one major thought in mind. He wants us to cultivate the ability to conceive of, work with, create, understand, manipulate, tinker with, disrupt, and, generally, appreciate the beauty of systems. This he hails as perhaps the most important of all the liberal arts.

It is the zeitgeist of the last 100 years that everything now appears as a system that was but a piece of a system before–or everything is now multi-dimensional that was linear before—thinking of the body as a system, the environment as a system, economics as systems, computers as systems. It’s why we talk about gamification so much–because a game, or a simulation, thought of as a thing we might create (rather than a thing we only act within), is a visceral example of systems thinking. (If this sounds familiar to readers of this blog, it’s because I’ve written about seeing systems before, in The Age of the Gums, or in Errol Morris and Spirals of Learning, or in Pieces of an Ecology of Workplace Learning, or even in The Conduit Metaphor, for instance. It might be all I write about.)

Seeing systems is an epistemology, a way of knowing, a mindset. As Kay said, “the important stuff I’m talking about is epistemological . . . about looking at systems.” It’s the Flatland story–that we need to train our 2D minds to see in a kind of 3D–and Kay’s genius is that he recognizes we have to bake this ability into the species, through education, as close to birth as possible.

One main point implied here is that we’re not talking about learning to see systems as an end point. Systems thinking is to be conceived of as a platform skill or an increased capacity on top of which we will be able to construct new sorts of ideas and ways of knowing, of more complex natures still. The step beyond seeing a single system is of course the ability to see interacting systems – a kind of meta-systemic thinking – and this is what I think Kay is really interested in, because it’s what he does. At one point he showed a slide of multiple systems–the human body, the environment, the internet, and he said in a kind of aside, “they’re all one system . . .” Compare that to the advanced stages in Bob Kegan’s constructive developmental psychology: “At Kegan’s sixth and final stage . . . there is a dawning awareness of an underlying unity that transcends human and environmental complexity.” (That from Philip Lewis’ work on Kegan, The Discerning Heart: Just happened to read that on the Metro on the way back to the hotel, as I was passing through Arlington National Cemetery).

Kay’s complaint is that higher education does not cultivate the particular epistemology of systemic thinking. We don’t teach integrative ways of knowing; we instead dwell within our disciplines, which dwelling you can see as being trapped within an arbitrarily chosen system. The point is to be able to see connections between the silos. Says Kay, the liberal arts have done a bad job at “adding in epistemology” among the “smokestacks” (i.e. disciplines).

Ok, so we’re not teaching systemic thinking. So what? What happens if you don’t teach people systemic thinking?

Then, Kay says, you’re allowing them to be stuck in whatever system they happen to be in, without thinking of it as a system. What happens when you’re stuck in a system? You don’t understand the world and yourself and others as existing in constant development, as being in process; you think you are a fixed essence or part within a system (instead of a system influencing systems) and you inadvertently trap yourself in a kind of tautological loop where you can only think about things you’re thinking about and do the things you do and you thus limit yourself to a kind of non-nutritive regurgitation of factoids, or the robotic meaningless actions of an automaton, or what Kay calls living in a pop culture. He sees this problem in higher education, where even faculty, experts in their own fields, are uneducated, in the sense that they can make no meta-connections among the fields, such that (as he said) hardly anyone exists who can understand the breadth of thought in a magnum cross-functional opus like the Principia Mathematica. And yet our future will be built on such integrative meta-connections as Newton’s.

By way of conclusion, I’ll now tell you why textbooks suck, according to Kay. A downside of being epistemologically limited to thinking within a system is that you overemphasize the importance of the content and facts as that system orders them. If you’re a teacher, you limit your students to processing bits according to a pre-ordained structure, to being a program, if you will, instead of learning to write a program. It would be better to use the system itself as the information students act upon when they construct their knowledge, and to find a way to get students to build new systems and even systems of systems. We teach students vocabulary within one set of grammatical rules, with the rules as the endpoint, say, but if we were disciples of Kay we would allow students to make grammars of grammars and languages of languages, with spirals of increasing complexity of thought looping into infinity and no endpoint in sight. That’s the order of consciousness Kay is after. Most textbooks, however, are on the stuck-within-the-system and vocab-and-grammar level. Which is why they draw Kay’s ire.

About the Future of Work

Malcolm Frank of Cognizant and William Taylor of Fast Company gave complimentary key notes at the Olin Innovation Lab #6 last evening; both touched on changes they see happening in the workplace today; I concatenate and summarize them here.

1. Growing Ideas. Organizations are beginning to understand they need to invest in and cultivate the “ideas” in their workplace as a routine part of their work; ideas are to be managed with different methods than the industrial processes that allow you to make stuff. In part, you have to involve staff in the creative thinking that fuels the strategic direction of the organization—things like “ideation” platforms and “idea stock markets” are de rigeur.
2. The Hive Mind. Organizations need to encourage and capture ideas from whatever direction they come, from any individual in the team, from partners, from customers. They’re entering into new relationships with staff and customers and other partners to find these ideas—an example is “prosumer” relationships, where customers actually help you design your services (as in helping you build an app). In part this puts a kind of network of minds at the service of the organization where before there was a limited hierarchy of thought.
3. Email RIP? The way we interact with information at work needs to come to feel like our interaction with information outside of work. As Frank says, “Monday morning needs to feel like Sunday night.” That is, we need to be mobile, engaged, interactive, inventing ways to do things, and choosing our content streams at work, just as we do at home. Old enterprise apps like Email and LMS are insufficient.
4. Removing the Place from Work. Virtualization of the organization will continue: because you don’t need to be in the same space to collaborate, workplaces will continue to increasingly allow for mobility, outsourced jobs, work-from-home; these things allow you to draw from a bigger pool of workers working in different places. And there’s less overhead.
5. The New “IT Stack.” The changes above are built on a new, four-part constellation of IT tools and ideas, or “IT Stack:” mobility, social tools, analytics, and the cloud. Organizations will begin to build on these tools to engage their customers, organize their staff, manage their innovation, allow the virtualization of their organization.
6. It’s About People. Changes to move in the directions above require IT innovation linked with cultural change, and lots of attention to the people and the relationships; idea stock markets will flop, for example, as tools to let people think together, if people don’t want or understand how to think together.
7. It’s About Millennials. This change can be seen as a shift from a Baby Boomer management mentality–of genius at the top and heavy control, epitomized by Steve Jobs–to a millennial model of collaboration, entrepreneurism, risk-taking, sharing, experimentation, exemplified by start-up cultures.
8. It’s About How Work Should Feel. All of the above implies that attention will need to be paid to the culture of the workplace, to the way staff minds are engaged, to the “feeling” of working well together—workplaces that engage their staff in the design of their work will be more successful.
9. Radical is the New Normal. In the traditional economy, everyone was basically equally competent, and the way you distinguished yourself was in some incremental process improvement that gave you an operational advantage. In the new world, the successful model is to rethink the business model; your competitors will be changing the rules of the game as quickly as they can. In that context being operationally competent and seeking incremental improvements won’t distinguish you but will lead to failure. You have to radically change the way you do things–regularly–just to be in the business.

Top Ten Lessons of Learning Organization Research (Part A)

Colleen Wheeler, Gina Siesing, and I presented the “Top Ten Lessons of Learning Organization Research” this week at NERCOMP 2012; an excerpt of our presentation begins below.

If you agree with us that the time has come to cultivate learning in our organizations in a systematic, holistic way, as a kind of cognitive enterprise infrastructure—you may be interested in some other opportunities:

• The Learning Organization Academy (LOA). We have been researching organizational learning as we build out NERCOMP’s new, intensive professional development program, designed to support you as you design and implement projects to improve learning in your organization. LOA premieres this July in Wellesley, MA, at preposterously low cost to you: if you’re interested, the enrollment pages will be opened on the NERCOMP site any moment now.
• The Workplace Learning Survey: You may also like to take our provocative, associated Workplace Learning Survey; results of this survey will be reported on in the near future, stay tuned!
• The Workplace Learning Road Show. For those who want to start to apply the lessons of workplace learning immediately, Collen, Gina, and I will come to your workplace and conduct a half or whole-day program with you and your colleagues that includes an introduction to the Organizational Learning literature, your own results on the Workplace Learning Survey, focused sessions on understanding your own culture and targeting areas of improvement, and sessions on surfacing individual and team-based belief systems. Write to me if this sounds fun.

Top Ten Lessons of Organizational Learning Research

10. Learning is key during times of change, yet organizations don’t learn well.

Everyone agrees that during times of change, the way to stay relevant is to learn, adapt, evolve. And we more or less have a sense of what it takes to do this—to significantly change our organization and its performance—it’s a big deal, yes, a three-year process, emotional, etc., but it can be done. That’s for changing once, though: retooling the production line to produce a new model, then just producing that model for a while.

The trick is that we’re now in an environment of constant change, so we need to forget the idea of alternating between periods of change and stability and design our organizations to be in a constant state of learning, of intentional, self-directed learning, and not just waiting for the world to intermittently force us to learn. It’s about managing a self-renewing learning ecosystem, not a factory.  This kind of always-learning organization is a higher order of learning, a much more complex structure, involving sophisticated management that we don’t really know how to do.

Complicating the problem is that we’re not particularly good at even the old change-once model of institutional learning. People by default come to act in organizations according to Argyris’ “Model 1:” they protect themselves from vulnerability, defend their teams from external destabilization, they don’t share, and they don’t trust. Which all means they don’t learn well.

9. People develop

We used to think you stopped learning at around age 21, and that after that point (when formal education generally stopped, too), you pretty much just coasted. This idea has fallen from favor; recent leaps in brain science let us see that the brain is constantly linking neurons to neurons right up to the end; Robert Kegan’s research also shows that adults can grow in cognitive sophistication over their lifetimes, changing the way they see the world in deep, meaningful ways, becoming increasingly able to deal with complexity and ambiguity. Which is good, because we’re talking about the need to teach ourselves how to grow and manage sophisticated learning ecosystems.

The catch here is that many of our behaviors and cultural structures still assume you don’t really develop. Things that focus on changing behavior rather than mindset or belief system (like performance reviews or New Year’s resolutions) are an example: they assume you can consciously decide your way through life, while the truth is that to really learn you often need to grow your consciousness itself. Another example is the cookie-cutter way we tend to understand each other and our organizations: more as changeless and rigid caricatures and less as subtle ontological and epistemological structures in constant state of flux and growth. Don’t we often identify a job and then look around for who can do it? In a learning organization we’d probably do something more like identify a job and ask what we need to do to help someone to grow into the ability to do it.

Carole Dweck’s work is telling. Her research reveals that if you think of yourself as “fixed,” say, as in “good” at something, you will avoid situations that challenge you, because you fear you’ll discover that you are not good. However, if you don’t worry about whether or not you’re good, but you focus on getting better, and if continuous improvement is your identity, you’ll crave any situation, especially the challenging ones, that can help you improve. Succeeding at getting better is of course better than failing at remaining good.

Even an institution built on improving people sometimes misses the point. Take the university. Here we dump enormous resources into the development of students, but nothing (relatively) goes to develop the staff or faculty.  But in an ecosystem every part influences every other part—investments in faculty and staff will help create a virtuous circle that lifts everyone.

8. People learn with loops and groups

Two very basic elements of learning can be summarized as “loops” and “groups.”

By loops we mean feedback loops. The basic learning cycle made famous by Kolb involves some planning, some action, some reflection, and then it starts over; this little sequence basically repeats itself in learning at a myriad of levels microcosmic and macrocosmic, in individual learning, and in team learning.

By groups we mean groups of people. Learning is a social happening (whether we think we’re alone or not). On the theoretical level Vygotsky’s famous Zone of Proximal Development sees in the social context the maximum growth potential of the individual. On the mundane it makes sense, too–clearly you can protect the vulnerability of learners and foster great conversations (important in forming loops!) when a small group of like-minded people are learning together.

An organization thinking about how it can improve its learning will thus likely spend a lot of time looking for places it can create feedback loops and add reflection to the ubiquitous planning and action cycles in the workplace. And when it’s not thinking about loops, the learning organization will be looking at its teams, how they function, how learning happens in them, and thinking about creating new learning teams or reinforcing existing teams.

7. Learning makes you vulnerable

One of the difficulties of learning in the workplace is that (as we saw above) we learn fast not to be vulnerable in the workplace.  But learning requires you to be vulnerable. On a basic level in any cognitive domain you have to be a beginner before you can be an expert: yet the workplace is obsessed with expertise and the appearance of expertise—to be thought of as less than expert, or incompetent, is perhaps the worst thing that can happen to you.

The problem is compounded for a team learning to do something new—in what we call the “double incompetency” problem, if you’re shifting resources from the old thing to the new thing as you ramp up to produce the new behaviors, there will be a point where you are insufficiently doing the old and not yet expert at the new. You’ll be liable to be called incompetent in both areas. From a traditional production perspective you should be fired.

But from the learning perspective the incompetence is required, and not welcoming that incompetence would be more or less immoral. So a learning organization will have to deal with this tension—protect the learners by retooling their expectations and the environment’s expectations, etc. And a learning organization that is in continuous dynamic development will have to learn how to also be in continuous dynamic insufficiency.

6. Learning makes the unconscious conscious

The reason we hinted above that structures that expect you to change your behavior by willpower don’t work is that we all have deep belief systems—both on an individual and social level—that govern those behaviors.  And if we want to behave differently (that is, if we want to learn), we have to adjust those belief systems.  This is the thinking behind Robert Kegan and Lisa Lahey’s work, and it emerges in Schein and Argyris as well.

You can change these belief systems, fortunately, and that is indeed the way we evolve through life: but to change them you need to “surface” them. You need to “see” the frame through which you saw the world, and in so doing you can make a new frame capable of handling more complex information.  It requires a king of penetrating self-examination and honesty in conversation that we don’t normally see in the workplace, though. Kegan and Lahey evolved a process, “Immunity to Change” that can guide you and your team in this journey; for Schein, protected conversations in safe “islands” are required to get at these deep beliefs. In either case looking for places you have conflict with the expectations of others is not a bad starting place, and fortunately, that sort of conflict is rife in work, where all our assumptions are basically thrown together and jostled about daily.

(continued in Part B)

Thoughts from Olin Innovation Lab #5

Post number two coming out of today’s is Olin Innovation Lab #5. Other ideas inspired by the day:

Thoughts about Ideation Platforms

• Businesses are recognizing the importance of innovation and the challenge of innovating from within an organizational structure designed to support established operations. They’re developing platforms to support internal innovation. The structures, called innovation management systems, or ideation platforms (!), solicit ideas for new initiatives from staff in various ways and shepherd those ideas through some development, evaluation, prototyping, and ultimately funding. Intuit has a famous process called Brainstorm; even 125-yr old Johnson & Johnson has something similar.
• Why would you want a platform and process to support and encourage innovation? Because it doesn’t happen easily otherwise. Some of the challenges are simple: one key one is just staff time. If you’re busy working, you don’t have a lot of time to think of and develop ideas that might not work out (and in fact you might get in trouble). Another challenge is funding–the purse-string holders are operations-focused–and even though they know it’s important to innovate, they still lean towards the things they know and toward reasoning from the things they know: keeping the machines and systems running, the people happy, and looking for incremental change and improvement. Innovation threatens to disrupt those things, even if it succeeds.
• Innovation in Higher Education. Basically, we should have our own ideation platforms. Easy enough to imagine applications of new technology in education–we’re pretty good at rolling technology out quickly. We’re good at research innovation, too; in fact, it’s the nature of research that we are encouraged to think of and follow-through on a variety of novel ideas and questions. But it’s not quite as easy to innovate in the curriculum, in the development of courses, in the organizational structure that supports that curriculum. Whereas we should probably be rapidly prototyping new ways to teach and learn.

A Couple of Other Ideas:

• Augmented reality is still there–a big splash a year or two ago seemed to be followed by a kind of lull, but with interesting new apps that translate messages you see on the fly (Word Lens) or analyze your golf swing (iSwing) the promise seems to be coming to fruition. I still want my augmented reality app for my library, so that I can annotate the library space and resources and see others’ annotations . . .
• According to today’s speakers, analytics is about to take off (even more), particularly in the mobile space. More data about the things people do are being collected than ever before, and the tools for analyzing that data in interesting new ways are almost ready.
• Businesses are now shifting from investing in mobile apps and creatively taking advantage of the digital age for their customers to now similarly empower their employees. It’s surprising but apparently true that business have heretofore been creative with their customers but offered their employees rather less fun.

Roy Rosin on Innovation

Joanne Kossuth and Thornton May organize a meet-up of business and higher education innovation leaders twice a year at Olin College. I go whenever I am allowed. Today’s is Olin Innovation Lab #5. At it, Roy Rosin, VP of Innovation for Intuit, shared a variety of thoughts on encouraging innovation in your organization. They were fun. My notes:

• Innovation starts with people immersed in the details of operations. In the field. Looking for ideas, problems, thoughts, puzzles, curiosities.
• For the ideas you get from the bullet above to go anywhere, you have to create a mindset that craves diverse ideas. “Savoring surprises,” Roy calls it. You need a discipline around developing a multiplicity of perspectives and fighting against premature “anchoring,” or fixing on an early idea to the detriment of others. Roy mentions a famous Chinese engineering firm that requires 6 alternatives be created before any solution will be approved.
• For the two bullets above to work, you have to empower people in your organization to change your organization, or why would they bother to share their ideas? This is unusual, but important. As Roy says, surprisingly, nobody can actually tell what a good idea is–not even your senior managers. Which means you should drop the wizard, “gatekeeper,” or manager-knows-best system, get all your folks thinking, and replace your approval-by-star-chamber process with fast prototyping of lots and lots of options.
• Which brings us to prototyping. Apparently nobody can really understand an idea unless they can see it and touch it. You therefore need to rush to a real, if cheap, attempt to instantiate whatever it is you’re thinking of. Use the bits and pieces of things sitting around; whip something together in a day or two. Once you’ve done this, people get better at being able to assess the goodness of the idea, and the idea’s role in your operations gets clearer. And, incidentally, you can improve it.
• Because, to continue from the last bullet, rapid prototyping lets you (of course) improve your prototype quickly. By the time you would have only written the technical requirements for a new tool (according to the old model) you can have pushed through five or six prototypes of that same tool (if you build them quickly and cheaply). Instead of a nice plan that might then get funded, you would have the thing itself, if perhaps in an imperfect state.
• A key in the shift away from the “gatekeeper” model of idea approval is to get the gatekeepers to start thinking about growth assumptions rather than existing problems. Instead of saying “what’s wrong with this” (which is the usual approach and which depresses the people with the ideas to no end, something you don’t want to do) you can ask people of your idea, “What do you like about this, and what would it take for it to succeed?” Your assumptions about success can then be tested with some prototypes.
• Finally, to what Roy calls the “Art of the pivot.” It ends up that most successful initiatives–like new business–change completely from their initial plan, recreating themselves from the ashes of their own failures a few times before hitting gold–this is now a recognized fact from venture capitalists who look for the ability to “pivot” (or learn from rapid tests) in the companies they found.