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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How can I join the conversation?

“Keep me in the loop.”

This all too common expression is – or should be – the bane of anyone trying to implement, or just use, a social media approach to collaboration and communication. What it really means is…

“I want to know what’s going on with your project, but I don’t care enough to actually spend my own time keeping up with what’s going, so please take time out of your own busy schedule and figure out what information I need to know and then make sure you get it to me. I may or may not bother to read it once you’ve sent it to me.”

The next time someone asks you to “keep me in the loop”, let them know where the conversation is happening and offer to grant them access. If they don’t take you up on it, then they don’t really care. If they do take you up on it, they may never join in. But they might, and their participation will be that much more valuable because they are there intentionally, not accidentally.

Of course, this goes both ways. Next time someone talks to you about a project that you are interested in, don’t ask them to keep you in the loop. Instead, ask them, “How can I join the conversation?”

What we need are knowledge curators, not managers

The concept of “knowledge curator” has been creeping slowly from the back of my mind to the front over the past couple of years, and received a couple of jolts over the weekend that resulted in one of those elusive “aha moments”.

What we need are curators of knowledge,
not managers of knowledge.

First, I noticed the blurb “curated content from Flickr” when I used the Flickr module on a Squidoo lens.

Second was a quote from Liz Danzico (that I found via Signal vs. Noise blog).

A portfolio of work is a curated experience. … but oftentimes, a portfolio only contains final pieces, as applicants are overly concerned about presenting perfection. Polish doesn’t communicate process though, and therefore I’m left with only part of the story. Messy problems — and how applicants work through them — can show a great deal more in a portfolio than one finished, airtight solution.

I didn’t know it at the time,but this all started back in November 2005 with an article titled Technology makes it easy to ‘remember,’ the trick is learning how to forget, in which I wrote:

My early days in Knowledge Management included a lot of time developing, deploying, and getting people to use “knowledge repositories.” (At least trying to get people to use them.) … I finally realized one day that the problem has become not, “How do we remember all this knowledge that we’ve learned?” but rather, “How do we forget all this knowledge we’ve accumulated that we no longer need so we can focus on what we do need?”

I also noted a quote from the book The Trouble with Tom by Paul Collins related to the need to “eliminate” memories:

Memory is a toxin, and its overretention – the constant replaying of the past – is the hallmark of stress disorders and clinical depression. The elimination of memory is a bodily function, like the elimination of urine. Stop urinating and you have renal failure: stop forgetting and you go mad.

It was this latter quote that was in my mind last summer when, in The importance of forgetting,  I wrote about John Medina’s thoughts on the question of memory and forgetting in Brain Rules:

The last step in declarative processing is forgetting. The reason forgetting plays a vital role in our ability to function is deceptively simple. Forgetting allows us to prioritize events. Those events that are irrelevant to our survival will take up wasteful cognitive space if we assign them the same priority as events critical to our survival.

As I noted then, this is no less true in the organizational context of knowledge/concept work.

Simply capturing everything in document repositories and best practices, without the ability to forget – or supercede – any of it, takes up a lot of “cognitive space” that organizations could be putting to other wise good use.

The trick is figuring out how to forget, and how to figure out what to forget.

Simplifying the execution of complexity

My review of Atul Gawande’s latest book The Checklist Manifesto focused, by design, on the broad scope of the book. Within that “big picture” lesson, though, are many smaller, more specific lessons to be learned.

For example:

No, the real lesson is that under conditions of true complexity – where the knowledge required exceeds that of any individual and unpredictability reigns – efforts to dictate every step from the center will fail. People need room to act and adapt. Yet they cannot succeed as isolated individuals, either – that is anarchy….

[U]nder conditions of complexity, not only are checklists a help, they are required for success. There must always be room for judgment, but judgment aided – and even enhanced – by procedure.

During this discussion, he refers back to what he had learned from the skyscraper-building industry, that they had figured out how to put an understanding of complexity into a series of checklists. That they had, in Gawande’s words, “made the reliable management of complexity a routine.”

What makes this even more fascinating is how the checklist, the lowly checklist that Steven Levitt had no interest in (until reading this book), can help simplify the execution of complexity even when the team members have never before worked together.

Just think what they could do for a team that works together all the time.

Are you just acting, or do you really know what you are doing?

The Ultimate Matrix CollectionI love the Matrix movies. All three of them. (Four if you count Animatrix.) As someone interested in learning and knowledge management, I find the whole idea of being able to simply download knowledge and really, truly learn how to do something very cool. Need to know how to fly a helicopter off a roof and across the city? There’s an app for that.

Compare this to the process that the actors went through to be able to provide convincing performances of these skills.  The actors trained for several months in order to obtain a sufficient level of physical readiness, then learned some basic martial arts skills. Hong Kong director and fight choreographer Yuen Woo Ping created the fight sequences, which the actors then learned.

From a knowledge management perspective, this is an excellent comparison of tacit vs. explicit knowledge.

The fight choreographers developed the fight scenes, then made the “knowledge” of the fight (in this case the choreography) explicit so the actors could “learn” the fight. But, and here is the important part, the actors did not learn “how to fight” but rather “how to perform the fight” for the film. They were acting on explicit knowledge, but it never really became “tacit.”

On the other hand, the stunt men portraying the bad guys obviously had the tacit knowledge of how to fight – you can see it in how they carry themselves and the weapons. For them, it was a matter of taking the new choreography and incorporating it into what they already knew.

From a learning perspective this shows the difference between what Carol Dweck refers to as performance goals and learning goals. Quoted in Dan Pink‘s new book Drive Dweck says, “Both goals are entirely normal and nearly universal, and both can fuel achievement.”

Inside the Matrix, the goals are learning goals. The characters need to actually learn the skills they need. For the actors, the goals were performance goals. Not what you’d call easy, but much easier than actually learning the martial arts and engaging in fights with other masters.

In your job, are you  an  “actor”, trying to provide a performance that follows the script and meets the approval of “the audience.” Or are you a master, continually learning and improving and getting done what needs to get done?

Some new thoughts on “my dad is a knowledge worker”

Several years ago (has it really been almost 5 years?!?) I wrote a somewhat tongue-in-cheek blog post entitled “My dad is a knowledge worker“:

While I was reading Martin Roell’s Terminology: “Knowledge Worker”, a TV commercial I saw a while back came to mind: elementary school students were telling the class what their dads did for a living, and after a couple of well defined jobs (policemen, construction, etc.) were announced one boy proudly stood up and stated, “My dad’s a pencil pusher!” I don’t remember what the commercial was for, but the imagery stuck with me I think for the same reason Geoffrey Rockwell, as described by Martin, doesn’t like the term “knowledge worker”: the job title gives you no real idea of what the job is.

Apropos of what I’m not entirely sure, but this old post came to mind earlier today when I was thinking about some ideas related to Work Literacy.  It occurred to me that calling someone – say a Systems Engineer like me – a “knowledge worker” would be like calling Albert Pujols an “athlete”.  (Not that I’m comparing myself to Albert!)

Sure, he is an athlete, but he is a very specific type of athlete, in a sport that requires a very specific set of skills and experiences. You can not get across what he does, or what he must be able to do, with a generic description of “athlete”. Like all athletes, though, there is a core set of skills and abilities that Pujols must have simply to be able to consider participating as an athlete in his specific sport. Fitness, endurance, flexibility, etc., all things common to most athletes.

In the same way, each individual knowledge/concept worker is a very specific type of k/c worker, requiring a very specific set of skills and experiences in order to do the work they do.  But like athletes, there is a core set of skills and abilities that anyone who would be a k/c worker must have. And that core set of skills and abilities is, I believe, what the term “work literacy” should encompass.

The question then, of course, is what makes up this core set of skills and abilities?

(As you may be thinking, I am not the first to raise this question – visit for more on the subject. On completing this post, I realized that it was simply my way of putting the question into a context that made sense to me.  I hope it makes sense to you, too.)