Is there a problem here?

Solving a problem that you know has a solution may require knowledge, but it is knowledge that already exists. Unfortunately – or, if you prefer, fortunately – many of the problems that are worth solving, that need to be solved, don’t come with that level of certainty.

In his book, How Life Imitates Chess (which, by the way, I highly recommend), Garry Kasparov has this to say about uncertainty:

Knowing a solution is at hand is a huge advantage; it’s like not having a “none of the above” option. Anyone with reasonable competence and adequate resources can solve a puzzle when it is presented as something to be solved. We can skip the subtle evaluations and move directly to plugging in possible solutions until we hit upon a promising one. Uncertainty is far more challenging. Instead of immediately looking for solutions to the crisis, we have to maintain a constant state of asking, “Is there a crisis* forming?”

 

On the path of knowledge creation

ThiagiIn his foreword to Marc Prensky‘s book Digital Game-Based Learning, Sivasailam “Thiagi” Thiagarajan (@thiagi) recounts the following (emphasis is mine):

Early in my life, my mentor explained to me the three paths that lead to the creation of knowledge. The analytical path, where philosophers reflect, meditate, and make sense of objects and events; the empirical path, where scientists manipulate variables and conduct controlled experiments to validate reliable principles; and the pragmatic path where practitioners struggle with real-world challenges and come up with strategies for effective and efficient performance.

Each of these paths can be taken in isolation from the others, we see that every day. It is also common to see these paths taken one after the other: analyze -> experiment -> implement.

More challenging, and much more powerful, is to integrate these three trails into a single path that allows you to go from trail to trail as needed to get you where you want to go.

What if your organization functioned like a video game

My earlier post on games got me digging through my archives (yet again), where I found two posts looking at knowledge management and knowledge work through the lens of games. Both of these posts are based on James Paul Gee’s book What Video Games Have to Teach Us About Learning and Literacy.

This second post looks at the role affinity groups play in learning through video games, and compares this to how many organizations work.

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Although James Paul Gee’s What Video Games Have to Teach Us About Learning and Literacy is primarily about how individuals, especially kids, learn, there is a lot in the book that can be applied to how organizations learn. This list describes what Gee sees as common features of what he calls affinity groups and their implications. Those familiar with knowledge management concepts will recognize these as traits of a good community of practice.

  1. Members of an affinity group bond to each other primarily through a common endeavor and only secondarily through affective ties, which are, in turn, leveraged to further the common endeavor. Implication: Affective ties and sociocultural diversity can be dangerous, because they divide people if they transcend the endeavor, good otherwise.
  2. The common endeavor is organized around a whole process (involving multiple but integrated functions), not single, discrete, or decontexualized tasks. Implication: No rigid departments, borders, or boundaries.
  3. Members of the affinity group have extensive knowledge, not just intensive knowledge. By “extensive” I mean that members must be involved with many or all stages of the endeavor; able to carry out multiple, partly overlapping, functions; and able to reflect on the endeavor as a whole system, not just their part in it. Implication: No narrow specialists, no rigid roles.
  4. In addition to extensive knowledge, members each have intensive knowledge – deep and specialist knowledge in one or more areas. Members may well also bring special intensive knowledge gained from their outside experiences and various sociocultural affiliations (e.g. their ethnic affiliations) to the affinity group’s endeavors. Implication: Non-narrow specialists are good.
  5. Much of the knowledge in an affinity group is tacit (embodied in members’ mental, social, and physical coordinations with other members and with various tools, and technologies), and distributed (spread across various members, their shared sociotechnical practices, and their tools and technologies), anddispersed (not all on site, but networked across different sites and institutions). Implication: Knowledge is not first and foremost in heads, discrete individuals, or books but in networks of relationships.
  6. The role of leaders in affinity groups is to design the groups, to continually resource them, and to help members turn their tacit knowledge into explicit knowledge, while realizing that much knowledge will always remain tacit and situated in practice. Implications: Leaders are not “bosses,” and only knowledge that is made explicit can be spread and used outside the original affinity group.

As most of us know all too well, most organizations today operate in ways very different from how these, often self-forming, groups operate. Some thoughts, item by item:

  1. The common endeavor in most organizations is dictated from the top down. Members of the organization don’t usually join the organization because of the ‘endeavor,’ rather they accept the endeavor because they have joined the organization.
  2. In most organizations (in my experience), specific functions are highly structured into departments and sub-departments. Successful cross-functional activity is the exception rather than the rule.
  3. Because of the highly structured nature of organizations, most people know only their area. Because the ‘endeavor’ is not their own, there is very little incentive to understand the ‘big picture.’ Those who do try to understand the big picture are often seen as ’stepping out of their lane’ and put back in their place. After all, how can they be doing their job if they are worrying about what someone else is doing.
  4. This is what most organizations expect of their members – a high skill level in their specific area.
  5. More and more organizations are recognizing the tacit nature of knowledge and the value of network relationships is sharing information. More than any of the other items in this list, it is this area that is receiving much of the attention in the field of knowledge management. It is hard, though, for individuals and organizations to get over the cultural expectation of knowing everything yourself, the ‘not-invented-here’ syndrome, and the sharing – freely – of what you know with others so they can be successful.
  6. Most ‘leaders’ are still just bosses.

Looking back over my list, I think I may be a bit pessimistic, but I’ve been involved with knowledge management, social networking, etc. for almost 10 years now and am still amazed, and frustrated, at how many organizations still don’t get it. Those who know me know that I’m really a glass-half-full kind of guy, and I must admit that I do hold out hope that things will change.

Maybe it will just take the current generation of young gamers, Marc Prensky’s digital natives, to finally get us there.

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Knowledge work, video games, and learning

My earlier post on games got me digging through my archives (yet again), where I found two posts looking at knowledge management and knowledge work through the lens of games. Both of these posts are based on James Paul Gee’s book What Video Games Have to Teach Us About Learning and Literacy.

This first post looks at the learning aspects of knowledge management and knowledge work. It could use a little updating, especially the part about “managing tacit knowledge” (which we all know can’t be managed), but I’m still pleased with it overall.

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After reading (and writing aboutMarc Prensky’s Don’t Bother Me, Mom, I’m Learning!, I picked up James Paul Gee’sWhat Video Games Have to Teach Us About Learning and Literacy. I was expecting a book about video games and the potential ‘good’ they offered. And the book does discuss this.

But the book is really about how video games are an example of how good learning can be enabled, encouraged, and accomplished in any environment. His area of choice is K-12 science education, but the learning principles – 36 of them– can be applied in many other areas.

In fact, Gee compares the environment that players of modern computer and video games inhabit to the world of what is commonly known as knowledge work. In the process, Gee describes a couple of key concepts and processes that those who work in the field of knowledge management will be familiar with.

Because Gee looks at these topics from the perspective of learning, his depictions are a bit different from what I’ve typically seen. For example, here is how Gee describes ‘tacit knowledge‘ (emphasis is mine):

Finally, the Intuitive (Tacit) Knowledge Principle is concerned with the fact that video games honor not just the explicit and verbal knowledge players have about how to play but also the intuitive or tacit knowledge – built into their movements, bodies, and unconscious ways of thinking – they have built up through repeated practice with a family of genre of games. It is common today for research on modern workplaces to point out that in today’s high-tech and fast-changing world, the most valuable knowledge a business has is the tacit knowledge its workers gain through continually working with others in a “community of practice” that adapts to specific situations and changes “on the ground” as they happen. Such knowledge cannot always be verbalized. Even when it can be verbalized and placed in a training manual, by that time it is often out of date.

What stood out to me was the emphasis on the importance of the “community of practice” in the development of an individual’s tacit knowledge and the fact that tacit knowledge is dynamic, never fixed. Tacit knowledge is, in my experience, typically addressed as something unique to an individual, something static. And while it is true, I suppose, that individuals do possess a certain amount of truly unique knowledge that never changes, to be useful most tacit knowledge must be flexible enough to be useful as the individual interacts with the environment.

A key challenge in the field of knowledge management is how to manage this tacit knowledge. Understanding both the individual and social nature of tacit knowledge is an important consideration to keep in mind. In fact, the social aspect, the tacit knowledge of the group if you will, may well be more important than the tacit knowledge of any one individual.

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Life skills for knowledge workers

In his post Some qualities of a knowledge worker, which I also mentioned yesterday, Jack Vinson (@jackvinson) mentioned a few skills needed by knowledge workers and notes

These are things that aren’t part of the standard training curriculum.  Maybe these things should be in the next generation of “life skills” classes they teach in high school.

This gets right at the heart of a question I’ve pondered for several years: How do knowledge workers learn how to become knowledge workers?

Is “knowledge work” something that should be taught in school, in high school as Jack mentions or maybe in college? Or is this something that individual workers need to learn on the job, as part of their professional growth, as part of their development of their craft?

Schools are, for the most part, set up for you to learn the skills/knowledge that you need (or they think you will need) to do your job. But they don’t really teach you how to actually do the job. (It’s been a while since I’ve been an undergrad, so maybe this has changed somewhat?) I think, though, that with a little bit of thought and a lot of effort these skills could be incorporated into a schools curriculum, either formally or informally by individual teachers. The case for social media in school provides some good ideas on this front.

The other approach is to look at knowledge work as a craft. Obviously, “knowledge work” is much too general of a description to be a craft in and of itself [my dad is a knowledge worker!]. But just like the trades – plumbing, carpentry, electrician – you can look at the various forms of knowledge work as a craft – accountant, engineer, lawyer, software developer.

If the idea of knowledge work as craft sounds familiar, it’s not because of me. I first remember coming across that idea several years ago in Jim McGee’s (@jmcgeeKnowledge Work as Craft Work.

All along the way in this old style process, the work was visible. That meant that the more junior members of the team could learn how the process unfolded and how the final product grew over time. You, as a consultant, could see how the different editors and commentators reacted to different parts of the product.

More recently, Jim has written about this in the context of observable work (#owork). His recent post Finding knowledge work practices worth emulating and adapting has some excellent insights that expand on the idea of craft work, putting it in concrete terms of knowledge work, in this case the “trade” of software development.

My brothers both work in a trade (plumbing and electrician), and I’ve had many conversations with them about the process within the trade unions of developing young plumbers and electricians from apprentice through the master grade. It’s made me wonder how I ended up where I am, how I learned to do the job I do. A bit less structured than their experience, that’s for sure.

How did you learn how to be a knowledge worker? Did you spend your early years in an “apprenticeship” or were you just thrown into the fray? How do we help new knowledge workers learn their craft? How do we get knowledge workers, new or otherwise, to accept their profession as a craft? And how do we, as experienced knowledge workers, become even better at it?

For knowledge workers, solving problems is the easy part

I read – and highly recommend – Garry Kasparov’s book How Life Imitates Chess a couple of years ago, and am thinking I should pick it back up again. If not to read in its entirety, then at least to skim through my dog-ears and margin notes. There are a lot of good insights into the nature of work today, especially what we call knowledge-work.

For example, Jack Vinson’s (@jackvinson) recent post Some qualities of a knowledge worker reminded me of the following excerpt:

Knowing a solution is at hand is a huge advantage; it’s like not having a “none of the above” option. Anyone with reasonable competence and adequate resources can solve a puzzle when it is presented as something to be solved. We can skip the subtle evaluations and move directly to plugging in possible solutions until we hit upon a promising one. Uncertainty is far more challenging. Instead of immediately looking for solutions to the crisis, we have to maintain a constant state of asking, “Is there a crisis* forming?”

Solving a puzzle that you know has a solution may require knowledge, but it is knowledge that already exists. Figuring out if there is a solution to a problem, or even if there is a problem at all, requires the manipulation of existing knowledge, the gathering of new knowledge / information, and the creation of something new.

This is when knowledge work becomes art.

Retaining knowledge in organizations – a contrary view

Yesterday’s #kmers chat focused on the topic Retaining the Knowledge of People Leaving your Organization.  Quite a bit of discussion around the topic, including questions about whether you should try to capture knowledge from those leaving, how you should do it, etc. etc.  Personally, I agree with V Mary Abraham (@vmaryabraham) when she says:

Ideally, move to system of #observable work. Then people disclose info & connections as they work & before they leave.

That way, the knowledge that is shared is in the context of a current action and not just information sitting in a repository somewhere.

This is a question that I – and many others – have wrestled with for many years now. Here is something I originally posted in Sep 2004 on the question. This is an unedited copy of that original post; I may come back later and give it a fresh coat.

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For many years now I’ve read about and been involved in discussions about the impending retirement of baby boomers, the effect this will have on institutional memory, and what can be done about it. Most of my interest in this at the time concerned the impact on the federal government workforce, which will be very hard hit since the retirement age is a bit lower than the populace in general.

Though I’ve not yet read it, the book Lost Knowledge by Dave DeLong addresses this problem in great detail (more on the book can be found here, here, and here). A snippet from the book’s website:

Dr. David DeLong, a research fellow at MIT’s AgeLab, has just created the first comprehensive framework to help leaders retain critical organizational knowledge despite an aging workforce and increased turnover among mid-career employees.

Like most discussions of the topic I’ve been involved in, the book seems to focus on the negative aspects of people leaving, and taking their knowledge with them. However, I have been reading James Surowiecki’s The Wisdom of Crowds and think that we may be missing out on an opportunity to actively reinvent the corporate knowledge as we try, probably in vain, to keep the old knowledge around.

Granted, there is some information and there are many processes that must be recorded and retained. This the basic infrastructure of how an organization functions. But if you simply take the knowledge of people who are leaving and transfer that to the people that are replacing them, you are effectively eliminating the value of the “new blood” coming into the organization. Or, in the words of Surowiecki, you are maintaining homogeneity at the expense of diversity.

Organizational memory, like human memory, can be a stubborn thing to change and often results in the this is how we’ve always done it syndrome. An excellent description of memory formation can be found in Tony Buzan’s The Mind Map Book (sorry for the lengthy quote, but it bears repeating in whole):

Every time you have a thought, the biochemical/electromagnetic resistance along the pathway carrying that thought is reduced. It is like trying to clear a path through a forest. The first time is a struggle because you have to fight your way through the undergrowth. The second time you travel that way will be easier because of the clearing you did on your first journey. The more times you travel that path, the less resistance ther will be, until, after many repetitions, you have a wide, smooth track which requires little or no clearing. A similar function occurs in your brain: the more you repeat patterns or maps of thought, the less resistance there is to them. Therefore, and of greater significance, repetition in itself increases the probability of repetition (original emphasis). In other words, the more times a ‘mental event’ happens, the more likely it is to happen again.

When you are trying to learn something, this is obviously a good thing. However, the very nature of this learning process makes it more difficult to learn something new, especially if it is very different (“off the beaten path”). By pointing new people down the paths of the people that are retiring, you are ensuring that the well known paths will continue to thrive and that it will be harder to create new paths through the forest.

That’s fine if your goal is to continue on the path you are on, but it brings to mind an old proverb I saw somewhere: If you don’t change the path you are on, you’ll end up where it takes you.

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