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My wife is a photographer. Quite a good one, in fact. One sure way to annoy her is to ask what kind of camera she uses after admiring one of her photos.. It’s her eye, not the camera, that recognizes the perfect shot. The tool may well be the least important element in the mix.

My own photography has gotten better courtesy of time spent in apprentice mode by her side. Photography is also an example of a knowledge work capability that can shed light on performance improvement in a knowledge context. The primary performance metric is whether you can capture the image you envision. Secondary metrics might include meeting time, budget, and other constraints on the image. In some settings, you may also need to be able to articulate the logic for why the image you eventually capture meets the criteria set.

If your goal, for example, is to capture a simple selfie to demonstrate that you were there at Mt. Rushmore, anything with both you and the mountain in frame and in focus will suffice. As you goals evolve, you also acquire new concepts and vocabulary; composition, depth of field, light conditions, focal length. exposure.

Meeting those goals may lead you to exploring and adopting new tools. A better camera might well enable you to capture images that weren’t possible with starter tools. But the functions and features of more sophisticated tools might just as well not exist if you don’t have the corresponding concepts to work with.

These concepts and the tools all need to be in service to creating the images you imagine. You don’t learn them in theory or in isolation. You learn them by doing the work and getting feedback. Over time, you also learn to give yourself better feedback.

Ira Glass has an excellent series of short videos on storytelling that fit here and fit knowledge work in general. The whole series is worth your time and attention–Ira Glass on Storytelling – This American Life. The nut graf, however, is something to keep close at hand as you work at your craft:

Nobody tells this to people who are beginners, I wish someone told me. All of us who do creative work, we get into it because we have good taste. But there is this gap. For the first couple years you make stuff, it’s just not that good. It’s trying to be good, it has potential, but it’s not. But your taste, the thing that got you into the game, is still killer. And your taste is why your work disappoints you. A lot of people never get past this phase, they quit. Most people I know who do interesting, creative work went through years of this. We know our work doesn’t have this special thing that we want it to have. We all go through this. And if you are just starting out or you are still in this phase, you gotta know its normal and the most important thing you can do is do a lot of work. Put yourself on a deadline so that every week you will finish one story. It is only by going through a volume of work that you will close that gap, and your work will be as good as your ambitions. And I took longer to figure out how to do this than anyone I’ve ever met. It’s gonna take awhile. It’s normal to take awhile. You’ve just gotta fight your way through.

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Between can be a difficult location. Cast or crew. Analog or digital. Quant or sales. Worker bee or management. Head or heart.

If you choose to reject the standard either/or logic and opt to stake out territory at a boundary or junction, the most likely result is ridicule and rejection. No matter how continuous reality may be, we insist on carving it up.

When I first moved out of the tech crew and into the stage manager’s shoes, I thought I was taking a small step. What I was doing was choosing to live in a DMZ. I became the referee when the lighting director and the choreographer both wanted the stage at the same time.

There was a time in one especially difficult production when I had had it with both the Producer and the Director. I can’t even remember what the argument was about. I left a note in the office that I was going back to school and they could finish the show without me.

A friend in the cast found me ten hours later in the one place I figured no one would think to look. I was in the third subbasement of the university library. Probably the first time I had set foot there since September and it was now March. I was coaxed into going back to the production, after apologies from the Producer and Director.

This was the earliest incident I can recall working to reconcile conflicting perspectives and demands to pull off a vision. Carpenters wanted to build, electricians wanted to light, dancers wanted to stretch, and actors wanted to run lines. All of it had to come together for the curtain to go up on opening night.

Over time, my interests have migrated to how to balance technology opportunities and organizational limits. But the reluctance of most to look outside the boundaries of their playgrounds remains. My head likes the challenge of figuring out the differing sets of details and their interactions.

Most players pick a side. They choose to belong to one organizational clan or the other. They commit to being management or to being a machine learning expert. Fewer choose to work as simultaneous translators; to learning the language and theories of new technology and of deep strategy.

Our systems are built around slotting people into speciality roles. What often gets lost is that someone has to work at being the glue fitting key elements together.

Managers do not solve problems, they manage messes
– Russell Ackoff

I’ve long been a fan of the late Russell Ackoff. This was one of his observations that continues to stick with me. As much as we like to think of the world as a set of discrete problems to be solved, reality insists on  being interconnected and messy. As I seek to understand and improve my own knowledge work practices, this is one of the pieces of wisdom I try to keep in mind.

One of the sources of mess that has been on my mind lately is scale. Things that seem obvious and simple always get messy as they get bigger. For example, I’ve just wrapped up a course on how to do requirements analysis. We run it as a field based course which means we work with local organizations to tackle a real problem. But it has to be a small enough problem that we can fit it into a semester’s worth of work.

I can require student teams to prepare the same work products that would be expected of them on the job but the problems aren’t big enough to make the need for some of those work products to be evident. Students do the work I ask of them, but they don’t really believe me when I assert that all of those products are relevant and important.

I’m probably irretrievably tainted by my early days in public accounting when I hung out with auditors. Now, this was so long ago that spreadsheets were still actual sheets of paper with rows and columns preprinted on them. Audits generated piles and piles of paper. The most natural thing in the world for an auditor faced with managing a stack of spreadsheets was to prepare another spreadsheet to serve as an index into the stack.

The physical scale of stacks of paper made this solution fairly obvious. Turn those stacks into bits, however, and the need to manage that scale problem disappears or, at least, fades into the background. If you can no longer see the mess, it won’t occur to you that it needs to be managed.

On a project team, there is often enough friction in dealing with multiple team members trying to coordinate their work that you can impose some level of control over the growing collection of digital materials being produced. But the usual pressures to “get to done” work against efforts to manage the mess. Persuading team members to give some thought to what they name that Excel file gets lost in the rush to work on what’s inside the file.

A sufficiently OCD project manager might prevail over a project team. Certain regulated environments can force the mess to be managed. But for individual knowledge workers, there are few incentives to deal with, or even recognize, the problems of managing the mess that is a digital work environment.

Getting work outside of your head is only a first step. Doing so gives you the capacity to take on problems that are too big to fit inside your head. Your reward for increasing your capacity is a set of bigger messes to manage.

I’ve been on a quest over the past year or so to understand the importance of getting outside of your head if you want to be more effective as a knowledge worker. The inciting incident for this quest was reading How to Take Smart Notes by Sonke Ahrens (my review is at 布谷加速器好用吗？免费下载:2021-5-19 · 布谷加速器提供海外多个线路，美国，日本，新加坡等多个地区。是一款永久免费的加速器软件，支持所有流行网络游戏进行加速的一款软件，绿色环保，隐私保密确保会不泄露真实IP。). I think I’m past the “refusal of the call” but I don’t know that there is a mentor to be found, although there do seem to be many others walking similar paths. Ahrens tells a story about Nobel physicist Richard Feynman that I traced back to James Gleick’s biography of Feynman (Genius: The Life and Science of Richard Feynman). Gleick tells it this way:

[Feynman] began dating his scientific notes as he worked, something he had never done before. Weiner once remarked casually that his new parton [In particle physics, the parton model is a model of hadrons] notes represented “a record of the day-to-day work,” and Feynman reacted sharply. “I actually did the work on the paper,” he said. “Well,” Weiner said, “the work was done in your head, but the record of it is still here.” “No, it’s not a record, not really. It’s working. You have to work on paper, and this is the paper. Okay?”

This is what my math teachers would label a “non-trivial” insight. However, if they made that point when I was studying math, it sailed right past me. Sure, you could sometimes salvage credit on a problem set by “showing your work” but it never occurred to me that “showing” and “doing” your work was the same thing. I always felt that the work was supposed to be going on inside my head, that the goal was to get everything inside my head before exam time rolled around. Certainly the testing and evaluation systems reinforced the notion that you were supposed to keep the important stuff in your head; storing it elsewhere was likely to land you in serious trouble if you got caught referring to that external storage during the exam.

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Once you start to look for it, you do see that smart people have been offering good advice about how to deal with the limitations of your unaided memory and brain. Think of Anne Lamott’s advice to write “shitty first drafts,”  Peter Elbow’s practice of “freewriting,”  Tony Buzan’s advocacy of “mind mapping,” or John McPhee’s ruminations on “Structure.” All of these are the kinds of techniques and practices that can make us more effective at creating quality knowledge work artifacts. But it isn’t clear that we encounter this advice as early or effectively as we should.

If we do stumble across this category of advice and fold it into our work practice, we can gain a meaningful edge. We’ve taken elements of the work out of our heads and into our extended work environment. We’ve increased the range and complexity of material we can now draw on to create better deliverables.

I’m in the midst of working this out for myself. I actually think that this is something that each knowledge worker is going to have to design for themself. I’m suspicious of claims that someone’s new tool or application contains the secret answer. Right now, I’m investigating various sources with an eye toward identifying design principles and ideas worth extracting or reverse engineering.

Some of the more interesting trains of thought include:

• §Taking knowledge work seriously (Stripe convergence talk, 2019-12-12) | Evergreen note-writing helps insight accumulate | Executable strategy for writing
•  Tool for Thought – The New York Times
•  stevenberlinjohnson.com: Tool For Thought
•  The Incredible Creative Power of the Index Card – Forge
•  Here (with 2 Years of Exhausting Photographic Detail) Is How To Write A Book
•  Why Roam is Cool – Divinations
•  Getting compound interest on your thoughts with Conor White-Sullivan
•  The One Thing You Need to Learn to Fight Information Overload
•  Berners-Lee: Talk at Bush Symposium: Notes
•  This is how I did it: created the best reference manager set up for research & writing – Natural Resource Ecology Laboratory at Colorado State University
•  Drawing Diagrams in the Head and with Technology: Benefits, Cognitive Mechanisms, Artificial Intelligence, Apps, and Sleep Onset Dreaming – CogZest
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•  How to Write a Note That You Will Actually Understand • Zettelkasten Method
• Building a Second Brain: An Overview – Forte Labs

The late Peter Drucker continues to be a source of insight and inspiration for me.  In 1999, he published “Knowledge-Worker Productivity; The Biggest Challenge” in the California Management Review. I’ve written about it before (Knowledge work and productivity). I want to explore the following observation:

The crucial question in knowledge-worker productivity is: What is the task? It is also the one most at odds with manual-worker productivity. In manual work, the key question is always: How should the work be done? In manual work, the task is always given.

I’ve started to think of this question as “Task Zero.”

The invention of zero was one of the great advances in mathematics; perhaps we should respect that power. One of the curious things you learn as a computer programmer is to start counting from zero rather than one. Certain things become easier when you do.

One of the reasons I’m drawn to starting at zero is that it frees up my thinking. If you think of yourself as starting from zero on a map or a coordinate system, you are free to move in any direction. Starting at one immediately commits you to a direction.

That’s tempting because a direction gets you moving. There’s a great observation from Cory Doctorow that reflects this:

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We like movement; it feels like progress. But they’re not the same thing. Take a closer look at Doctorow’s quote; he’s advocating movement in “the direction of your goal.”

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It’s worth giving this task an identity separate from the tasks that follow. It’s like that pregnant moment at the end of a countdown to launch just before movement begins.

I was usually good at the  stuff that gets rewarded in school. Good enough to  get away with also being a bit of a smart ass. The problem was that school came easily enough that I rarely had need to develop good study habits. Not a problem that I worried about at the time. The bigger problem was that I never saw the connection between study habits and effective work habits after you left the classroom and wandered into real life.

For a long time, this wasn’t actually a problem because there wasn’t a deep connection between schooling and real life. The only habits taught in school that mattered for later were to show up on time and do what you were told.

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Today, there’s increasing attention to the notion of learning how to learn and there’s lots of advice and material on note-taking techniques, or memorization tricks, or 豆荚加速器官网下载. But, it’s all secondary. We let the superficial differences between the classroom and the real world obscure the deeper alignment we could be exploiting.

That’s a missed opportunity. The content we learn will become obsolete, but the practices will retain their value. The classroom should be where we develop the habits and practices we could continue to employ when doing knowledge work for a living.

Moving classes online back in March triggered a new emphasis on the notion that the knowledge work we do is better and more easily done when you get it out of your head and somewhere in front of you where you can see it and improve it. This is a position I’ve come to only after a long process of fighting the notion in practice and gradually coming around to that notion and working to update and adapt my own work habits and practices.

Practicing what you preach is always much harder than the preaching part. As part of convincing myself to work harder on improving my practices, I went back and gathered up some of the key moments in the evolution of my thinking if only to shame myself into more practice and less preaching. It occurs to me that assembling these pieces in one place may be useful to others as well.

• Review – Sound advice on managing collaboration in teams – There’s a particular point in this piece about evidence that teams charged with creating new ideas always seem to revisit and replan their efforts somewhere near the midpoint of their work.
• Balancing Uniqueness and Uniformity in Knowledge Work – Most of what we have to say about work emphasizes uniformity and predictability. My Toyota Prius and yours should be substantially identical. Knowledge work is the opposite; the work in only valuable to the extent that it is new and different
• Managing the visibility of knowledge work – In a technology dominated economy, knowledge work is effectively invisible and that makes it harder to manage.
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• Crumbling pyramids; knowledge work, leverage, and technology – Organizations built around knowledge work are also built on apprenticeship models both functionally and economically, Technology is making apprenticeship harder to manage and sustain.
• Doing and Managing Knowledge Work: TUG2010 Keynote Reflections – This was the place where I first started to talk about the notion of “observable work”
• Showing your work- intermediate knowledge work artifacts – We need to move beyond the notion of deliverables and make the processes of knowledge work visible throughout
• Bring back working papers – Paper intensive work practices threw off useful intermediate artifacts. Now we need to design those intermediate artifacts
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• Communications Divides Within the Organization; Look to Homer – Here’s some rumination on a distinction first proposed by a Jesuit priest named Walter Ong. His thesis was that writing gave us a new way thinking quite different from the oral thinking that represented much of early civilization.

In 1992, Larry Prusak and I were working for Ernst & Young exploring the links between information technology and strategy. We thought it would be a good idea to organize what we knew and turn it into a book. We put together a short proposal, pitched the idea to the powers that be, and landed a contract with John Wiley & Sons to deliver a manuscript. Being a diligent project manager, I sat down to plan the effort. We had worked out a chapter outline, so I started with that classic planning strategy of working backwards from the deliverable.

I wish I could lay my hands on that outline and the plan I wrote from it. We reorganized the book from top to bottom multiple times between that first outline and the final manuscript we delivered. My first reaction was to blame myself for being a much worse project manager than I claimed. My second reaction was to focus on the estimating error of not factoring in the multiple revisions and rewrites that happened with each chapter.

It took a long time to recognize the deeper lesson hiding in plain sight. Successfully working backwards from a target deliverable depends on how clear a picture you have of that deliverable. There are always pressures trying to convince you that your picture is sharper than it is.

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How do you draw on the work you have delivered in the past, without succumbing to the temptation to phone it in? How do you fold in knowledge of prior deliverables without blinding yourself to this problem’s new, and possibly unique, questions? Rely on prior deliverables too heavily and all you do is create variations on a theme. Ignore the lessons contained in prior work and you are no more valuable than any random smart person.

Assuming you bring a threshold level of professionalism to the task, what else can you do to avoid being led astray by old answers when you are facing a new problem? One thing is to distinguish between how far you can see and how clearly. Working backwards is a useful strategy, but that doesn’t mean you are in a position to work backwards from the finish line. Thinking through deliverables is only one tool in your kit.

Some pointers to prior thoughts on deliverables

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– Knowledge work improvement – black box, white box, and deliverables

– Deliverables – the fundamental secret to improving knowledge work

– How better thinking about deliverables leads to better knowledge work results

I often find that I give myself pretty good advice as long as I remember to revisit what that advice was.

Two years ago I read Peter Morville’s Planning for Everything: The Design of Paths and Goals and managed to post a review here—Review: Planning for Everything: The Design of Paths and Goals.

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There’s a separate discussion to be had about whether there are better strategies than rereading. I’ll save that for another day.

Morville observes that “while a plan may be defined as a series of steps, planning itself is nonlinear.” This is something that you come to understand over time, but is easily overlooked. You can forget it as an experienced planner because it is down at the level of muscle memory; it happens too fast to be noticeable. It can be harder to discern when you are learning how to plan.

We tend to focus on the artifacts of planning; project charters, statements of work, work plans, schedules, Gantt charts. We gloss over the complexities of developing those artifacts as our understanding of a problem evolves.

This is akin to when we are learning to write complex arguments. How many of us wrote the outlines to our papers after the fact? That’s because we didn’t recognize then that the struggle to find and impose order on our notes and research  or the multiple iterations of our opening paragraphs were essential to the creative process. We were inclined to see them as accidental complexities that threatened to reveal our ineptness when, in fact, they were essential to the creative process.

Perhaps this simply reveals my naïveté, but for many years it never occurred to me that books weren’t written in the order that we read them. How did Orwell dream up “it was a bright cold day in April, and the clocks were striking thirteen,” out of thin air?

Our first encounters with plans are much like our first encounters with writing; we see the finished product neatly ordered and polished. The iterations, false starts, and multiple revisions don’t show up in the final product, but they are essential to getting there. Learning to plan, like learning to write, requires rolling around in the messiness. We need to acknowledge and accept that.

Becoming adept at planning is as much about attitude and expectations as it is about technique.

Back when I was a Chief Knowledge Officer, I struggled with the problems of how to better tap the collective knowledge and experience of an organization filled with extraordinarily smart people. There were the technical problems of what to collect and how to organize it. There were the organizational change problems of how to persuade those same smart people that sharing their expertise my way was in their best interest.

I had an epiphany when I came to see knowledge management less as an organizational problem and more as a problem for individual knowledge workers. From that problem, the first task was to figure out how to get better at sharing knowledge with yourself. Which led me to the notion of observable work. Dave Winer’s thinking on narrating your work was an excellent entry point to that train of thought.

During that process, I sketched the following diagram as I collected my thoughts:

Scarcely rocket science but it was helpful to me. The next step was to think about what larger scale patterns or clusters might be discernible That led to this picture:

I thought it could be useful to revisit this and unpack it from the perspective of more experience and insights culled from other smart people. Let’s start with generating a new list of “Stuff” that seems to have something to do with knowledge:

 

10K	Data Flow Diagram	Log	Speech
10Q	Data Record (row)	Lyric	Spreadsheet
Abstract	Database	Manuscript	豆荚加速器官网注册
Acronym	Database Query	Map	Statistic
豆荚加速器注册	Database Schema	Mathematical model	Statistical Model (Regression)
豆荚加速器注册	Dataset	Melody	Statistical Test
豆荚加速器首页	Descriptive Statistic	Message	豆荚加速器官网注册
Appointment	Dialog map	豆荚加速器注册	Subroutine/Module
Bibliography	Dictionary	Musical Score	Syllabus
Block diagram	豆荚加速器首页	豆荚网络加速器破解	Synopsis
Blog	豆荚加速器官网注册	Note	Term Sheet
Blog post	Encyclopedia	Notebook	Theory
Blueprint	Equation	豆荚网络加速器注册	Threaded Discussion
Book	豆荚加速器官网注册	Outline	Time Series Analysis
Book Series	File	Poem	Timeline
Bookmark	File Folder	Phone Call	TLA, ETLA
Bug Report	Financial Schedule	Phone Number	Transcript
CAD Drawing	豆荚网络加速器破解	Photo	Trip Report
Calendar	Forecast	Podcast	Tuple
Card Catalog	Formula	Précis	Tweet
豆荚加速器首页	Gantt Chart	Presentation	豆荚加速器注册
豆荚加速器官网注册	Glossary	Presentation Slide	Url
Chat message	Graph	RACI Matrix	Use Case
Chat log	Group Calendar	豆荚加速器官网注册	Voice Recording
Chord Progression	Hyperlink	Report/White Paper	Video Clip
Citation	Index	Resume/CV	豆荚加速器官网下载
Code	Infographic	豆荚网络加速器破解	Webpage
Code Repository	instant message	Scene	Website
Computer Program	Interview Notes	Schedule	Wiki
豆荚加速器官网下载	豆荚加速器官网注册	豆荚加速器官网下载	Work Breakdown Structure
Concordance	Issue Inventory	Search query	Work Plan
Conference Call	Journal Article	Search results	Working Draft
Consulting Report	Journal Entry	Simulation model	Working Paper
Contact record	Journal/Diary	Sketch
Contract
豆荚加速器官网下载
CRUD Matrix

You could continue to add to this list. Or, you could explore what subsets organized by discipline—mathematics, economics, programming—might reveal. I think the broad distinctions between notes, working papers, and deliverables remains useful I’ve been looking at those questions myself of late (notes, working papers, deliverables). My advice used to be to start with deliverables and work your way backwards. That grew out of years of consulting work focused on the needs of clients.

Lately, I’ve been wrestling with the problem of managing at scale either as an individual or as a larger group. Techniques and practices that work for a single project or a handful of clients/projects break down as both time passes and numbers grow. Organizations address these problems by dedicating resources to them. They create and enforce the rules that annoy individual knowledge workers who haven’t yet run into scale problems in their own work.

These kinds of problems often surface in data management settings. The simplest example that springs to mind is sorting a list of names and addresses. Someone setting up a spreadsheet to invite friends to a surprise birthday party might set up one column for name and another column for phone number. Simple enough. Someone who’s been burned before will start by splitting the name into separate columns for first name and last name.

The point is that the “obvious” solutions to knowledge work data management problems have lots of unanticipated flaws that don’t surface until you cross scale thresholds. It seems perfectly reasonable to file project deliverables away by client and project until you have a hundreds of clients and projects and none of that information helps you track down the regression analysis you did sometime last year for one of three clients but you can’t recall just which.

Zettelkasten advocates make a compelling argument that the classification schemes natural to a knowledge manager actively inhibit the creativity meant to be the defining characteristic of knowledge work (豆荚网络加速器注册). There is more worthy thought and discussion about categories of notes and emerging structural layers of notes.

The conclusion that is slowly emerging for me is that part of being an effective knowledge worker is a need to design your own knowledge management environment and that this design needs to anticipate that your needs and understanding are a continually evolving driver of that design.