A Concise and Brilliant Peer-Reviewed Article on Writer’s Block

I’m passing this along from Bob Sutton’s blog (which you ought to be reading if you care about management and leadership in today’s enterprises).

Below you can see an entire article (including a reviewer’s comment) that may look fake, but is legitimate. It was published by Dennis Upper in the Journal of Applied Behavioral Analysis in 1974, and is funny, true, and inspired — and a great demonstration that "brevity is the soul of wit."   Academics, especially the editor’s of our journals, have a well-deserved reputation for being humorless assholes (note I edited a couple academic journals and include myself in this swipe), so I give these editors a lot of credit.  A big thanks to Thomas Haymore for telling me about this masterpiece and to Professor Brad DeLong for publishing it on his blog a few days ago.


A Concise and Brilliant Peer-Reviewed Article on Writer’s Block
Mon, 06 Dec 2010 17:52:26 GMT

Sugata Mitra on designing systems for learning – TED talk

I’ve finally gotten around to the following TED video that’s been queued up in my "to read/watch" stack. In it, Sugata Mitra describes his "Hole in the Wall" experiments that placed internet connected PCs into New Delhi slums and watched what happened. It’s worth 20 minutes of your time.


Mitra’s conclusion is that you can get a lot of learning for very little investment, particularly in the trappings of formal education that we tend to take for granted. People are wired to learn and appear to do so best in small groups of like-minded learners. They need access to resources and encouragement. They don’t particularly need someone more expert to guide them; their natural curiosity works as well or better. Mitra’s view is that education is best treated as a self-organizing system.

Digging into how learning works versus how we naively think it works is important in the world we find ourselves in. Individually and organizationally, we are faced with ongoing challenges to learn. Neither we nor our organizations can afford the necessary learning time if it has to be in the form of conventional settings. Following the threads worked for the kids in Mitra’s experiments. We need to follow a similar path. We also need to experiment with integrating those learning paths into the demands of day-to-day work.

Where IS Health Care Going? Technology Leader’s Presentation

Last week, JoAnn Becker  and I ran an interactive discussion with the monthly TLA Manager’s breakfast meeting here in Chicago. We had a lively and excellent debate among a group of technology executives, health care executives, and other smart people about the real challenges of successfully deploying information technology to improve productivity and quality in delivering health care in this country.

That, of course, is an immense issue and would could barely scratch the surface in the hour we had. For those who are interested, we’ve uploaded our slides to Slideshare.


We used two recent TV ads from GE and IBM to kick off the discussion. On the surface, each provides a sense for the promise of information technology to make health care more effective:

GE TV ad – Doctors
IBM TV Ad – “Data Baby”

In the tradition of all good technology vendor advertising, both also completely gloss over the complex organizational adaptation and evolution necessary to bring these hypothetical worlds into being. They also gloss over the existing institutional and industry complexity that needs to be understood and addressed through a combination of design, leadership, and management.

Fred  Brooks, professor of computer science at UNC and author of The Mythical Man-Month : Essays on Software Engineering, draws a critical distinction in the final chapter of the book, which is titled "No Silver Bullet," between accidental and essential complexity. His point is that software is so difficult to design and develop because it must successfully model the essential complexity of the domain it addresses. Technology and software efforts can stumble on a variety of barriers and roadblocks, but failing to understand and address essential complexity is the worst.

Health care provides its own mix of accidental and essential complexity. If the decision makers aren’t careful to draw distinctions between accidental and essential, then a great deal of time and effort will be expended without corresponding returns. On the one hand, we may simply succeed in "speeding up the mess" as my friend Benn Konsynski so liked to put it. Or, we may obliterate  essential complexities in a quest for uniformity and productivity that is blind to those complexities. Or, finally, we may invest the appropriate level of design time and talent in systems that account for essential complexity and eliminate accidental complexity.


We drew on a variety of excellent resources in preparing for this talk and wanted to make them more easily available here.

Here are several books that provide useful context and background

Here are pointers to a variety of health care related web resources worth paying attention to:

Collaboration, games, and the real world

I’ve been thinking a lot about hard problems that need multiple people collaborating to solve. There’s no shortage of them to choose from.

This TED video from Jane McGonigal makes a persuasive case that I need to invest some more time looking at the world of online gaming for insight. Watch the video  and see if you don’t come to a similar conclusion.


Nine years and counting here at McGee’s Musings

Today is the ninth anniversary of my first post here. It remains the primary place where I work out my thinking about the challenges of knowledge work in today’s world and how to operate at the boundaries between technology opportunities and organizational reality.

It’s also a place that continues to introduce and connect me to other people wrestling with the same kinds of questions. The human connections that flow from this effort remain the real reward.

I would like to ask a few questions from those of you who find this valuable in some way:

  • What would you like to see more of here?
  • What would you like to see less of?
  • What topics would you like to see me address that haven’t been addressed here yet?
  • What else would make this a better resource for you?
  • Who else should I be listening to?

Doing and Managing Knowledge Work: TUG2010 Keynote Reflections

I’m back from last week’s Traction User’s Group meeting, TUG2010, where Greg Lloyd graciously asked me to do the opening keynote. I’ve posted the slides on Slideshare and wanted to add some further commentary here.


First, one caution; when I do use slides I don’t design them to be standalone documents. There are too many bullet points in the world as it is. What I’d like to do here is highlight and elaborate on some of the key points I was trying to make.

Peter Drucker first called our attention to the importance of knowledge workers decades ago. The rest of us are slowly catching up to his ideas. One shift in focus that I’ve begun to emphasize is toward the knowledge work itself and away from the notion of knowledge worker as somehow distinct from other kinds of workers. Trying to distinguish who may or may not be a knowledge worker as opposed to some other kind of worker simply perpetuates pecking order games that do little to further the mission of an enterprise. We all do knowledge work  to some degree or another, we are all doing more knowledge work than before, and the important question is how to do that work more effectively.

The notions of visibility and observability have been central to my thinking for some time now. The evidence is clear that dealing with complex problems and thinking requires a certain amount of corresponding complexity and mess in our working environments. To those whose focus is on stability and operational control, mess, of course, is disturbing. So disturbing that we ridicule those who deviate from the presumed ideal. We do so at a greater organizational cost than we realize, however, when we ignore the complexity in the environment that is driving the mess.

I introduced the following simple map to suggest just how unavoidably messy the real world of knowledge work can be. The x-axis maps the inherent structure of the knowledge “stuff” we encounter; the y-axis maps the degree to which knowledge stuff is individual or social. It didn’t take long to identify a multitude of items and objects that you might routinely encounter as you go about your work.


It’s tempting to simplify this reality in some way. Many years ago P&G was famed for teaching its managers to distill their arguments into one-page memos. Too many consultants and speakers opt to squeeze all of their output into slideuments; which merely transfers the problem somewhere else. Senior executives rely on staffs to filter the stream at the risk of filtering out the essential insight or data point that truly informs.

The strategy I prefer is to accept the fundamental messiness and seek ways to tame it enough to make it manageable. Part of that relies on exploiting the natural pattern-seeking, pattern-matching capabilities of the human mind. Part relies on enlisting the pattern management capabilities of the other human minds in the system to supplement your own capacity. Both of which also need to be tempered by appreciation for the limits of those same capabilities.

Taming the mess breaks into three layers of practices:

  1. Hygiene. The proliferation of objects in a physical office offer a host of clues about their contents and relative importance; size, shape, color, location on a shelf or desktop, position in a stack, etc. In a digital environment you need to provide the equivalent of those clues explicitly and consciously. Seemingly mundane decisions about the file names you choose, for example, can make large differences when you are later scanning through a page of search results. Most of today’s systems provide little real assistance in this arena; you and your teams need to develop their own standards for naming files, managing versions, and other details of the knowledge stuff they work with.
  2. Metadata. i wish there were a more homespun term for this layer. One of the central tricks to taming the flood of data and information that constitute your digital world is to add more data to the flood. The ability to tag the items you create or encounter with labels that are meaningful to you greatly leverages the other tools at your disposal. Merge those tags with the tags of those in your social network and you shorten the path to finding what you are searching for still further, either on your own or through your network’s help.
  3. Context. One of the least appreciated aspects of messiness in the physical world is the context it provides. There’s a story attached to each pile and object; a story that can be triggered by its context. The power of this context is why students do better on tests when they take them in the same classroom they took the course in than in a random room. A filename in a directory listing or a document displayed on  a monitor lack this ready context and are poorer for it. The alternative is to become more mindful of the importance of context and make an effort to capture it explicitly and contemporaneously. This is rationale behind such notions as narrating your work, and developing a digital portfolio.

There is a payoff to all of this for both individuals doing knowledge work and the organizations they contribute to. Once again Peter Drucker said it first; “the most valuable asset of a 21st century institution will be its knowledge workers and their productivity.”  Economic growth in this century depends on our ability to improve knowledge work productivity; until you can see it, you can’t improve it.