Category: Knowledge work

My fascination with the space between technology and organization is something that grew slowly. When I went back to school to get an MBA, I fell into the group that understood the quantitative and structured material. I had spent the previous years designing and writing programs to count things up and calculate answers. Half the curriculum made sense.

The other half–about markets and organizations and people–often bordered on mystifying. But mysterious can also be enticing. The mystery eventually brought me back to school for the third time. I still wanted to understand how to take advantage of technology but the answers were buried in the intricacies of humans in organizations.

One of the things you learn dealing with technology is that technology does only and exactly what it’s told to do. When technology behaves in unexpected ways, then there’s a mistake in your programming. You have to examine what’s going on around you as you look for clues and never forget that you are also a key part of environment your are exploring.

This is an interesting perspective to bring over to the task of understanding organizations. While you’re engaged in deepening your grasp on how organizations work in the abstract, you are also embedded in a complex organization environment.

While you are trying to acquire the tools and concepts to make sense of structure and power and leadership, you are simultaneously engaged in a live-fire exercise with the institution you are a tiny piece of.

I recall a conversation with one of my thesis advisors about a fairly nasty tenure fight that was going on in her department. Rather than get sucked into a Machiavellian swirl of intrigue, her option was to be very clear and explicit on her plans and objectives and then do exactly what she said.

Simple and classic advice.

One of the things you learn with technology is to look for simplicity. There’s plenty of sources of complexity. Your job is to not add to the problem. Combine technology and organization and you’re now in the realm of combinatorial complexity. Don’t make things worse by trying to be clever. Be predictable.

After church yesterday, I had a quick conversation with a relatively new parishioner. I had learned that Ben was from St. Louis, as was I. This was a perfect opening to ask the first question that always gets posed whenever two St. Louisans meet: “Where did you go to school?”

In St. Louis, this is actually a question about what high school you attended. The answer is meant to pigeonhole anyone precisely on a clutch of dimensions – religious, socio-economic, political, cultural. I got the one answer from Ben that I would never have expected. We had both graduated from Priory. We are separated by enough years, that his classmates were the children of my classmates.

The answer was unexpected because Priory is a Catholic, Benedictine, school and we were in an Episcopal Church. First pigeonhole broken.

I’ve been thinking about pigeonholes and sides. And the experiences from my middle school/high school years bounce off that quintessential St. Louis question in odd ways. The question is usually pretty reliable because St. Louis is a pretty reliably stratified environment. If you grew up in the environment, you knew where you fit. By the time you reached Priory at age 11, you knew where you belonged.

I was dropped into this environment as an outlier. We had only just moved to St. Louis and I had no previous connections or pigeonholes that mattered. I lived a fair distance from the school which complicated matters further. My classmates didn’t know where to pigeonhole me either. But I had to be categorized and sorted if I wasn’t to disrupt the natural order of things.

I grasp the fundamentally tribal nature of humans. I’ve spent a good portion of my professional existence dealing with it. But back then I was simply a piece on the board as others were choosing up sides in a game I was only dimly aware of.

I was in an environment where I had strengths that qualified me for multiple roles. I was bright. I was decently athletic. I was quick witted and fast tongued. I was valuable, albeit naively so, to multiple sides. Gradually, I learned to move between sides. What I discovered was how committed people were to fitting smoothly into a primary pigeonhole.

That commitment to fitting in one category often blinds us to the degree of commonality that actually exists between categories. We invent new language to emphasize differences and distinctions. The path to fame in many settings starts with inventing new terms for old ideas. It’s a temptation that is hard to ignore. There’s less reward for revealing shared concepts hiding behind language invented to sharpen differences. There’s deep wisdom hiding in the tagline to the movie WarGames; “the only winning move is not to play.”

“But, you’re not an asshole!?”

A client I was working with had just discovered that I have a Harvard MBA.

More recently, I’ve taken over a course from a colleague and I’m starting with his slides so that I can focus on delivering the material and not get bogged down in the details of course design. He had an opening slide with his academic credentials and I copied in mine. It’s causing the annoying problems I could have predicted.

I don’t hide my background but I’ve become guarded about what and when I reveal facts about myself. That guardedness causes its own set of problems.

I used to think the explanation was about belonging; about being on the inside or on the outside. I got into Princeton and Harvard because I did well on tests and in classrooms but I came from a different world. Big family, Midwest roots, Catholic boy’s school, technologically adept, socially awkward; not quite Eliza Doolittle but not a bad approximation.

Skip ahead several decades and the rough edges have become reasonably polished.

Belonging isn’t the right way to think about it.

It’s about being between; of sitting within the overlap of a Venn diagram and working to make the shared space bigger. Not just for me but for everyone. Making the between bigger is about building bridges, creating shared language, and committing to learning about the other circles in the diagram.

The primary circles that draw my interest are organizations where humans band together to pursue human goals and technology where tools amplify human capacities. I believe that there is an enormous amount of overlap to be found there. The counter-belief feels more like warring camps in trenches with a shell-pocked no-man’s land in between.

I know from personal experience that the overlap is real. What I intend to explore over the next several weeks is what it might take to traverse the between safely.

There’s a story of the two watchmakers that Herbert Simon tells in The Sciences of the Artificial to illustrate the relevance of intermediate structure and hierarchy. Here’s the story

There once were two watchmakers, named Hora and Tempus, who made very fine watches. The phones in their workshops rang frequently and new customers were constantly calling them. However, Hora prospered while Tempus became poorer and poorer. In the end, Tempus lost his shop. What was the reason behind this?

The watches consisted of about 1000 parts each. The watches that Tempus made were designed such that, when he had to put down a partly assembled watch, it immediately fell into pieces and had to be reassembled from the basic elements. Hora had designed his watches so that he could put together sub-assemblies of about ten components each, and each sub-assembly could be put down without falling apart. Ten of these subassemblies could be put together to make a larger sub-assembly, and ten of the larger sub-assemblies constituted the whole watch

Simon uses the story to illustrate why structure and hierarchy emerge in complex systems. Or why good designers build  intermediate structure into their systems.

One interesting aspect of this fable is that Simon talks of two levels of intermediate structure. This suggests that there are criteria to invoke when making design choices about the size and complexity of intermediate structures.

I’ve been thinking about intermediate structure lately in the context of how to be more effective in doing knowledge work. I’ve touched on working papers recently and I wanted to revisit the topic from the perspective of stability and intermediate structures.

I’ve been blogging for a long time and writing at multiple lengths–blog posts, teaching cases, articles, books. I use or have used all sorts of tools in the process

• mindmaps (both by hand and by software),
• outlines (again, both by hand and by software)
• word processors
• text editors
• bibliographic/reference management software
• wiki software
• specialized note taking tools (Evernote, nvAlt, etc.)

The space between glimmer of an idea and finished product is what draws my attention now. Although I’ve been nibbling around the ideas of working papers, most of what I’ve discovered and examined has talked about writing process. Freewriting, shitty first drafts, mindmapping techniques. What’s starting to come into view is the structure side of the question.

For the longest time, I’ve worked and thought in terms of deliverables and working backwards from some vision of an end product. That works well enough for blog posts and most client reports. At the longer scales of a book, on the other hand, working backwards breaks down. You know that the outlines and mindmaps are  necessary but they morph as the process unfolds and as your understanding of the deliverable evolves.

The notion of a permanent and evolving collection of notes and treating those notes as “first class objects” that should be designed to stand on their own is a new to me. When I started blogging the idea of a commonplace book was one idea for an organizing container for developing ideas and lines of thinking. Jerry Weinberg’s Weinberg on Writing: The Fieldstone Method is an approach that I’ve worked to understand and adopt. I’ve certainly recommended it to many colleagues. More recently, Sonke Ahrens’s How to Take Smart Notes: One Simple Technique to Boost Writing,  Learning and Thinking drew me into the subculture of Zettelkasten.

All of these new ideas still focused mostly on process advice. They fell short on offering insight into the structure of the data and information that you created through the processes. They slide past the data half of the equation and I’m only know coming to see how that has been holding me back.

A collection of permanent notes is a handy thing to have around. But, without attention to intervening stable structures we are still fighting the problem of building a 1,000 piece watch in a single step.

There are some hints scattered in what I’ve found so far. The Zettelkasten sub-culture references the notion of special forms of structure notes, for example. In my own work. I’ve started to recognize the emergence of recurring themes and am trying to develop techniques to capture and track them.

I feel I am at the stage of recognizing that there’s a problem to be addressed. I can see the gap between a collection of random notes and the organized flow of a final deliverable. Now I’m looking to design or discover stable structures that can serve as waypoints where I can pause before I have worked out what the final deliverables might be. Is this a problem that others have also encountered? Are there concepts and structures I can learn and adapt?

There’s been a recent cluster of articles on the productivity benefits realized from capping working days and working hours. Earlier this week Cal Newport penned an op-ed in The NY Times picking up on this theme.

Newport has been arguing that current approaches to complex knowledge work are poorly conceived. He argues for the importance of learning how to do “deep work” and advocates for the value of digital minimalism. Here he turns to a well-worn comparison. Manufacturing work did not realize meaningful productivity gains until Henry Ford made the transition from craft approaches to a carefully designed and engineered assembly line.

All too often the next move in this argument is to immediately conclude “craft bad/engineered process good.” I doubt that Newport would support that conclusion but this short circuit occurs often enough that I want to slow down for a moment and focus on it.

Concluding “craft bad/engineered process good” is the wrong answer to the wrong question. The lesson to be drawn from the Henry Ford is not that Ford found the right answer, it is that he found a better question.

That better question was “How do we design a process that will produce consistent, quality results?” His answer, in a stable and predictable environment, was an engineered process operating within tight tolerances to produce standard products of uniform quality.

We do not operate in “a stable and predictable environment.” Nor are we expected “to produce standard products of uniform quality.” How do we begin to answer that design question given those constraints?

We don’t do it by copying Ford’s answer.

I continue to believe that developing new answers starts by thinking in terms of craft. Recognizing that the goal is no longer “standard products of uniform quality” is a first step. I’ve talked about it as balancing uniqueness and uniformity.

The harder question is how to think about process without falling into the trap of engineered rigidity. I think getting answers to that questions needs to start in the field, watching how effective knowledge workers practice and think about their craft. I would like to get something more concrete than the classic consultant’s response to any request for advice of “well, it depends…”

I’ve often railed against the standard marketing trope of “here’s our proven system for solving problem X.” Proven systems pitches classify problems as simple to solve and, by implication, those with problems as either ignorant or lazy. My objection is that this offers little help for hard problems and we live in a world with lots of hard problems.

Suppose your interests lie in attacking hard problems? Call them wicked problems or management messes, these are the problems that constitute more of our agenda.

One answer is to acknowledge that answers to hard problems have to be custom crafted, with solutions tailored to the environment and the circumstances. Can we glean some value from the “proven systems” hawkers even as we recognize that our problems of interest don’t fit their premises?

MacGyver provides the essential strategy here. The point is to treat a proven system as design input to crafting a custom solution. To do this effectively, the first step is to reverse engineer the proven system. First, to understand the assumptions about the problem structure and environment driving the system design. Second, to extract the components and subsystems comprising the system. Third, to pattern match between the problem characteristics of the two systems—those of your problem and those built into the assumptions of the proven system. Fourth, to adapt and apply the subsystems that apply.

This approach depends on recognizing that you own the problem. That means rejecting an implicit premise of the proven systems perspective that you can transfer ownership and responsibility to the system.

I’m fundamentally lazy so I’m always looking for tools to simplify whatever task I’m trying to accomplish. I’m currently teaching a course in project management and we’re working through how to build good project plans. In project management circles, there seems to be an infinite set of options for software tools to support project execution. Tool support for earlier stages receives less attention.

Most project management tools presume that you already have a plan to manage; how you create that plan is an exercise left to the reader. The tools treat the capture of phases and tasks as a data entry problem not a creative one. I see a project plan as an outline of tasks arranged and organized into a sensible order.

Creating that sensible order, however, is not an orderly process. It’s a thinking and writing task that of necessity proceeds in fits and starts, where order emerges only gradually. You don’t write a project plan starting at step one and marching along to step n anymore than you write a novel by starting with “It was a dark and stormy night…” and plowing ahead.

My preferred tool for the creative stage of project design and planning is a mindmap. Back in the day, I drew the initial maps by hand. Today, we’ve got software tools to make the process of creating and evolving plans smoother. I work primarily on Macs these days; my tools of choice include Scapple, Xmind, and MindManager.

There are plenty of other choices on every platform. Any of them is better than jumping straight into a tool built to manage project execution. And any of them is better than limiting yourself to a word processor or text editor.

I don’t worry about whether I am following the “rules of mindmapping” or have found the one perfect mindmapping tool. The key payoff is that I am using a tool whose fundamental design principles match the problem I am trying to solve.

The Fall term is settling into its rhythm. I’ve shared my usual story of my own academic transcripts containing at least one of every possible letter grade. I was a natural, but undisciplined, student. I paid attention to meeting prerequisites for subsequent courses and meeting the requirements of my major but I didn’t think about the practicalities of how what I was learning flowed from one course to the next. More broadly, I gave little thought to the connections between what I was studying now and what I would need to know later for any value of later beyond the final.

My unexamined assumption was that whatever I learned in one class would somehow stick in my brain to be drawn on in the next class or in the future. Notes were what you did to pay attention during class and had no evident value once the exam was done. I suppose textbooks had some value in my mind as I kept those for a while. On the other hand, I don’t think I ever did much to refer back to them in subsequent classes or in the workplace.

Now, it could simply be that I was lazy. There are those who would argue for that hypothesis. Maybe everyone else was more organized and more disciplined than I and I failed to notice their better disciplines. But I suspect not.

I’ve written about the general problems of the shrinking half-life of knowledge. What’s on my mind today is the question of how to cope with that world. We have access to better tools and more processing power than I ever did in my student days. What strategies and practices for leveraging that power are possible that work in both the immediate context of a single class or a single project and contribute to knowledge that’s valuable in the longer term?

There are examples that address this question of continuity beyond the problem at hand:

• Harold Jarche has been working on the notion of Personal Knowledge Mastery.
• Jerry Michalski has been using The Brain software to build Jerry’s Brain over the last two decades
• German sociologist Niklas Luhmann’s Zettelkasten  note-taking and management system was a paper-based system that seems to have spawned resurgent interest in some arenas.

Doug Engelbart’s seminal work on augmentation ought to bear on this as well. But my sense is that Engelbart doesn’t directly address the question of continuity. Time for another reread—which is itself indicative of the problem.

I’m still at the agenda setting stage. Stay tuned.