Category: Knowledge work

I’ve long been a fan of Alan Kay. We met twenty five years ago as we were building a consulting firm that blended strategic and technology insight. One of Alan’s favorite observations is “point of view is worth 80 IQ points.” Choosing a better vantage point on tough problems is time well spent, especially when there is pressure to get on with it.

I’m not sure I can count the number of times I’ve heard or said that we live in a knowledge economy. That we are all knowledge workers who live and work in learning organizations. Yet, we continue to celebrate the industrial revolution in those organizations. We celebrate scale and growth and control. We worry about the problems of accelerating change but assume that working harder and longer will suffice to keep pace.

There is a better vantage point. It is to treat knowledge work as craft work in a technological matrix. Craft work integrates materials, tools, and practices to create artifacts that simultaneously embody the skill and expertise of crafters and meet the practical and esthetic needs of patrons.

Examining each of those elements from a craft perspective illuminates what it takes to become effective as a knowledge worker and remain so as change continues to accumulate. It’s our 80 IQ point move.

Materials – make them visible to make them manageable

Industrial work is built on repeatability; my iPhone 6 Plus is fundamentally identical to yours; any differences are cosmetic. Give me the same consulting report you prepared for your last client and we have a problem. The output of knowledge work derives value by being unique.

Knowledge work produces highly refined abstractions; a financial analysis, a project plan, a consulting report, a manuscript, or an article. A piece of knowledge work evolves from germ of an idea through multiple, intermediate representations and false starts to finished product. Today, that evolution occurs as a series of morphing digital representations which are difficult to observe and, therefore, difficult to manage and control.

A pre-digital counterexample reveals the unexpected challenges of digital work. I started consulting before the advent of the PC. When you had a presentation to prepare for a client, you began with a pad of paper and a pencil and sketched a set of slides. Erasures and cross outs and arrows made it evident you were working with a draft.

This might be two weeks before the deadline. You took that draft to Evelyn in the graphics department on the eighth floor. After she yelled at you for how little lead time you had given her, she handed your messy and marginally legible draft to one of the commercial artists in her group. They spent several days hand-lettering your draft and building the graphs and charts. They sent you a copy of their work, not being foolish enough to share their originals.

Then the process of correcting and amending the presentation followed. Copies circulated and were marked up by the manager and partner on the project. The graphics department prepared a final version. Finally, the client got to see it and you hoped you’d gotten it right.

Throughout this process, the work was visible. Junior members of the team could learn as the process unfolded and the final product evolved. You, as a consultant, could see how different editors and commentators reacted to different parts of the product.

Today’s digital tools make the journey from idea to finished product easier in many respects. When knowledge artifacts are digital, however, they are hard to see as they develop.

So what? Only the final product matters, right? What possible value is there to the intermediate versions or the component elements? Let’s return to the bygone world of paper again. Malcolm Gladwell offers an interesting observation in “The Social Life of Information:”

”But why do we pile documents instead of filing them? Because piles represent the process of active, ongoing thinking. The psychologist Alison Kidd, whose research Sellen and Harper refer to extensively, argues that “knowledge workers” use the physical space of the desktop to hold “ideas which they cannot yet categorize or even decide how they might use.” The messy desk is not necessarily a sign of disorganization. It may be a sign of complexity: those who deal with many unresolved ideas simultaneously cannot sort and file the papers on their desks, because they haven’t yet sorted and filed the ideas in their head. Kidd writes that many of the people she talked to use the papers on their desks as contextual cues to “recover a complex set of threads without difficulty and delay” when they come in on a Monday morning, or after their work has been interrupted by a phone call. What we see when we look at the piles on our desks is, in a sense, the contents of our brains.”

I have friends whose digital desktops have that look about them but this strategy doesn’t readily translate to the digital realm. The physicality of paper gave us version control and audit trails as a free byproduct.

Digital tools promote a focus on final product and divert attention from the work that goes into developing that product. “Track changes” and digital Post-It notes provide inadequate support to the process that proceeds the product. Project teams employ crude naming practices in lieu of substantive version control. Software developers and some research academics have given thought to the problems of how to manage the materials that go into digital knowledge artifacts. Average knowledge workers have yet to do the same.

Visibility is the starting point. Once you make the work observable, you can make it improvable. Concepts like working papers, and audit trails, and personal knowledge management can then come into play.

Tools – Every Day Carry and Well-Equipped Digital Workshops

Where craft matters, so do tools. That got lost in the industrial revolution. Tools were carved out and attached to minute pieces of process, not to the people who wielded them with skill. Meanwhile, the raw materials of knowledge work–words, numbers, and images–did not call for much in the way of tools other than pencil and paper. Mark Twain was an innovator in adopting the typewriter to improve the quantity and quality of his output. But the mechanical tools for aiding knowledge work came to be seen as beneath the dignity of important people.

There was a time when “computers” were women charged with carrying out the menial tasks of doing the calculations men designed and oversaw. It was not that long ago when executives thought it perfectly sensible to have their email printed out and prepare their responses by hand. These attitudes interfere with our abilities to be fully effective doing knowledge work in a digital world.

There’s the old saw that to a child with a hammer, everything looks like a nail. To a skilled cabinet maker, every problem suggests a matching hammer. A well-equipped workshop might contain dozens of different types of hammers, each suited to working with particular materials or in specific situations.

If our materials are digital, then our skill with digital tools becomes a manageable aspect of our working life.

There’s a useful distinction between basic and specialty tools. A basic tool in hand beats the perfect tool back in the shop or office. I’ve carried a pocket knife since my days as a stage manager in college. Courtesy of the TSA I have to remember to leave it behind when I fly or surrender it to the gods of security theater but every other day it’s in my pocket. There is, in fact, an entire subculture devoted to discussions of what constitutes an appropriate EDC—Every Day Carry—for various occupations and environments.

In the realm of knowledge work, Every Day Carry defaults to an email client, calendar, contact manager, word processor, and spreadsheet.  For most knowledge workers, tool thinking stops here. Other than software engineers and data scientists, few knowledge workers give much thought to their tools or their effective leverage. Organizations ignore the question of whether knowledge workers are proficient with their tools

If you are judged on the quality of the artifacts that you produce, you would do well to worry about your proficiency with tools. If you have control over your technology environment, set aside time to extend your toolset and learn to use it more effectively. Invest time and thought into how to design, organize, and take advantage of a knowledge workshop filled with the tools of your digital trade. Plan for a mix of EDC, heavy duty, and experimental knowledge work tools.

Practices – Design Effective Habits

Process thinking built the industrial economy. To deliver consistent quality product, variation is designed out and all the steps are locked down and controlled. If your goal is to craft unique outputs suitable to unique circumstances, industrial process is your enemy.

Where then are the management leverage points if industrial process is not the answer? McDonalds is not the only way to run  restaurant. In a knowledge work environment, both design and management responsibilities must be more widely distributed and shared. Peter Drucker captured this when he observed that the first question every knowledge worker must ask is “what is the task?”

Answering that question entails understanding the materials and tools available. From there, knowledge workers can design approaches to creating the necessary unique knowledge artifacts. Habits, routines, rituals, and practices replace rigid processes. In a fine restaurant, the day’s fresh ingredients set the menu and the menu guides which preparation and cooking techniques will be called for that evening. Line cooks, sous chefs, and chefs collaborate to create the evening’s dining experience.

The building blocks for constructing suitably unique final products are learned over years of practice and experimentation. They are passed on through observation and apprenticeship. In a volatile knowledge economy, they must also be subject to constant evolution, refinement, and innovation.

Learning as a craft practice

In the pre-industrial craft world, learning could be a simple process. Find a master and apprentice yourself to them. Time would suffice to transfer expertise and skill from master to apprentice.

We do not live in that world.

In an industrial world, learning was focused on fitting people to the work. Open-ended apprenticeship was replaced with narrow training programs to learn the specifics of where humans fit into a larger, engineered, process design.

We do not live in that world.

Integrating a craft point of view with the pace of the technological environment that now exists makes learning a craft practice to master.

We are all permanent apprentices. We are also all permanent masters of our craft. Apprenticeship must become conscious and designed. Mastery will always be temporary. Our understanding of materials, tools, and practices will always be dynamic. Learning and performing will be in constant tension.

I started this blog in the earlyish days of blogging. I was teaching a course at Northwestern’s Kellogg School about strategic uses of information technology. The blog offered a way to share thoughts with my students. I quickly plugged into a community of like-minded bloggers in education and in knowledge work in general. In time, that network connected me to Buzz Bruggeman, CEO of ActiveWords. Buzz being Buzz, we connected and have remained friends and colleagues since. That is another story in itself.

ActiveWords is a Windows utility program. On the surface, it is a text substitution tool. Type “aw,” for example and the program will produce “ActiveWords” on the screen. It does much more than that, and there are comparable products on both Windows and Mac. When I was a Windows user, it was one of the first programs I installed on every new computer. I now use equivalents on the Mac.

But this is not a software review.

The default marketing strategy for this category of tool is to emphasize efficiency.The tools invariably come equipped with tools to calculate how much time you save by typing “aw” in place of “ActiveWords.” If you are, in fact, a reasonable touch typist, those time savings are modest. Frankly, they aren’t that great for poor typists. Yet, the people who do adopt these tools often become vocal fans and evangelists. Are theses fans simply horrible typists or are they on to something more interesting?

The marketing from efficiency argument is simple to articulate and deeply rooted in an industrial mindset. Tools are good if they make workers more efficient; Frederick Taylor opined on the size and shape of shovels to improve the efficiency of strong-backed men moving stuff from pile A to box B. Knowledge workers aren’t shoveling coal. None of us work in typing pools.

These tools and their effective (not efficient) use are better understood from the perspective of augmentation laid out by Doug Engelbart. Saving keystrokes isn’t the point; redistributing cognitive load is.

Software developers figured this out long ago and designed programming languages to handle the tedious aspects of building software so that developers could focus on the tricky bits. Bob Frankston and Dan Bricklin wrote Visicalc, the first spreadsheet program, so that they could focus on setting up the finance problem to be solved and let the computer take care of the arithmetic.

There is a conflict here to be managed between knowledge workers and conventional managers. If you are stuck in an efficiency world, you must resist the temptations to cram these approaches into an industrial frame. In an assembly line, the tools are part of the line; everyone uses the same pneumatic tools in the quest for efficiency.

Effectiveness calls for a more personal perspective. You might get away with mandating a standard set of tools —Buzz would be quite happy if Microsoft put a copy of ActiveWords on every Windows machine. But you can’t impose a standard set of abbreviations, for example, on every knowledge worker in the enterprise. That process has to be tailored to each knowledge worker’s individual needs.

Let me offer a simple example. Every time I decide to use the word “individual, ” I have to stop and think about how to spell it. That interferes with my train of thought. So, I’ve taught my Mac to transform “indv”into “individual.” The program I happed to use for this, TextExpander, will happily calculate how much time I save by typing 4 keystrokes instead of 10, but I don’t care. Maintaining my train of thought is something far more valuable than 6 keystrokes.

Philosopher Alfred North Whitehead captured this calculus long before I learned to type. He observed that:

Civilization advances by extending the number of important operations which we can perform without thinking about them. Operations of thought are like cavalry charges in a battle—they are strictly limited in number, they require fresh horses, and must only be made at decisive moments.

What this does call for is learning to observe our own work and look for the speed bumps and other opportunities to redistribute the cognitive load.

Twenty-some odd years ago, I had an opportunity to listen to Colin Powell speak. The event was small enough and I was senior enough that we had a useful conversation after his talk. The question I had was “how can you benefit from the experts working for you without some understanding of what they actually know and do?”

Secretary Powell’s response was that you had to rely on your ability to judge people on a human level and trust that the enterprise you were part of was able to maintain a level of quality in how it recruited, developed, and advanced its experts. I wasn’t happy with his answer then and I’ve only become more unhappy since.

In most enterprises, for most of their history, the nature of work changed slowly. In Powell’s case his job was the same from the time he was a young 2^nd lieutenant until he was Chairman of the Joint Chiefs of Staff; defend the U.S. against the threat posed by the Soviet Union. Only the scope changed.

That world was gone when we had the conversation twenty years ago. How do you manage a sales force using Salesforce when your selling days were built around a Rolodex and a DayPlanner? How does experience interpreting focus group results prepare you to extract insight from clickstream data? Pick your domain and the flood of new knowledge obsoletes old technique and overwhelms your capacity to evaluate results on the basis of merit.

There’s a dilemma here. You can’t manage what you don’t know. You can’t know everything you need to know. What you need to know changes faster than you can keep up.

Organizations exist to solve problems that exceed the capacity of any individual. We tend to think of that as a hierarchical process. An entrepreneur hires people to carry out their vision and design. Those people are there to execute work on behalf of the entrepreneur but the implicit assumption is that the entrepreneur could do all the tasks given sufficient time.

This was Colin Powell’s world. He might not know all the details of his subordinates work but he could. He was willing to trust their recommendations because he trusted the system. What if he can’t understand the recommendations? Or the alternatives?

The military sidesteps this problem with a useful workaround—commander’s intent. Commanders share the reasoning and goals being their orders. That allows subordinates to make local decisions applying their expertise to accomplish “commander’s intent” even if that might mean ignoring or contradicting the specifics of the commander’s orders.

In our expertise saturated environment, we need to create a bilateral form of commander’s intent. Knowledge intensive work in a volatile environment comes with the requirement to teach others how to understand and make sense of your work.

“Trust me” is not an option in either direction. Success depends on getting meaningful conversation to take place about the competing claims of all the stakeholders.

Contributing to this conversation places different demands depending on your role.

If you are an expert, you must understand the organizational decisions your expertise bears on. You must then be able to articulate the assumptions and limitations that constrain your options and your recommendations. The A/B testing of copy on your e-commerce site tells you nothing about the people who never visit your site.

If you are a leader, your goals need to include sharing the reasoning behind the answers you seek. In fact, you ought to stop thinking of experts as the people who provide answers. In time-stressed settings, it is always tempting to seek focus and clarity by seeking to confirm your intuitions. Executives ask for answers to their immediate problems. The counterintuitive yet more useful strategy in volatile environments is to collaborate with your experts to articulate and explore questions you have not thought to ask.

Application and software vendors are offering more customer support in places like Facebook in addition to their more formal channels. Done well, this enlists volunteer help from users, recreating some of the feel from the earlier days of the online world where there was often a strong sense of shared community.

In those earlier days, there was a threshold level of technical sophistication that you could rely on. As the internet began to open up, that level began to drop slowly. A community ethos and slow broadening of participation led to some excellent advice on how to take full advantage of the available expertise. For my own selfish benefit, I pulled together several of the best guidelines for seeking technical advice:

• Scripting News: Writing good bug reports
• How to Report Bugs Effectively
• How To Ask Questions The Smart Way – Eric Raymond

As I reread these guides, however, and sampled the recurring questions surfacing in some of these more recent support environments, I was struck by a disconnect between today’s questions and these guides. In tech support circles, there is an old, disparaging, term about certain kinds of user interactions—PEBKAC, which is an acronym for “Problem Exists Between Keyboard and Chair.” In other words, the problem is user ignorance .

That feels a tad arrogant. It calls to mind the late Arthur C. Clarke’s 3rd Law:

Any sufficiently advanced technology is indistinguishable from magic.

and what is perhaps a more pertinent variation offered by science fiction author Gregory Benford:

Any technology distinguishable from magic is insufficiently advanced.

We operate in a world that is magical to many of it’s inhabitants. Most are content to accept that world as a place of routine magic. But too many are also content to choose to operate at Muggles; to leave understanding the magic to others. To make that choice is to reject the notion that deeper knowledge is a path to more effective leverage of the available tools.

If we accept the responsibility of learning how the magic works, we open up the possibility of acquiring greater power over our world.

Back in April I started to play with the idea of intermediate knowledge work products. I want to push that a bit farther and argue that we ought to bring back and expand on the idea of working papers.

The Limits of Deliverables

Deliverables are a powerful idea for managing knowledge work. What artifacts—report, specification. contract, presentation, analysis, application—mark the end point of a chain of work? What can you create to demonstrate to your client or manager that you’ve completed the work you promised to do?

The problem with deliverables is that they discourage the process of discovery and innovation. You deliver when you are done and the only response to receiving a deliverable is to accept it—either graciously or reluctantly, but accept it either way. This problem is aggravated by our ability to turn out work products that look like finished deliverables regardless of their actual state.

Reclaiming Working Papers

“Working papers” is a concept I first encountered in my early years as a consultant working within an audit firm. An audit is a odd process; your job is to check someone else’s work and render an opinion about whether they followed the rules. The deliverable that justifies the auditor’s bill is an opinion letter stating your conclusion. What you most desire as a client is a very short letter that boils down to “yes, you followed the rules.”

Working papers are all the analyses and evidence prepared to support that final deliverable. In a paper-centric world, this creates a problem of organizing and cataloging all of the intermediate pieces of paper so that you can trace and recreate the analysis later if circumstances warrant.

On the other hand, there was also an advantage in having everything on paper. Add a date and your signature in the top corner of a memo or analysis, stick it in the files, add a new line to the index page, and your working papers were up to date. The old joke was that the files weren’t complete until there was a least one paper placemat covered with lunch notes in them.

It’s the notion of “working” that is important here; the medium is not. Thinking and managing in terms of working papers highlights the importance of process and dialog. Working papers only exist in the context of how they support the process of interaction, whether it is the interaction between data and analyst or the interaction between stakeholders seeking to understand a problem.

Digital Limits of Working Papers

The shift to digital work makes just about every aspect of knowledge work better. Preparing a spreadsheet by hand on actual 28-column paper is not an experience I wish to revisit. But we also produce digital work products in ways that obscure and interfere with the evolutionary nature of effective thinking and analysis.

One limitation of digital work products is that you must deal with version elaboration and control intentionally. All interesting work products go through an evolutionary process. Preliminary hypotheses need elaboration. The structure of an outline morphs with feedback from potential readers. Drafts beget revised drafts. Analog products reveal this evolution in the proliferation of copies and marked up drafts.

Our digital tools obscure this evolution. The spreadsheet or report file contains only the most current version. Previous versions that were naturally preserved in an analog world disappear; it takes a conscious effort to preserve an intermediate digital version. Think of the crude control efforts revealed in file names with random dates, initials, and version numbers littering the drives of the average knowledge worker.

Software developers have built sophisticated tools to support their work of evolving a code base from idea to working application. I am hard pressed to identify other knowledge workers taking advantage of those tools or practices as they develop equally complex final deliverables.

The reason that version control matters is that final deliverables grow out of interaction and dialog. That dialog is rarely linear. Future iterations grow out of the process of building analyses and testing alternative hypotheses.

This iterative development process is an essential element of doing meaningful analysis and getting all of the participants to agree with the results. Treating analysis as a process is the first step. Deliverable centric thinking obscures this. A working paper approach puts process where it belongs.

One additional step with knowledge work artifacts adds significant value at minimal cost. Our digital tools produce outputs that resemble finished product regardless of their actual state. It can be difficult to distinguish a back of the envelope calculation from an SEC-ready filing when both are printed in 11-point Arial. Adding a “DRAFT – FOR DISCUSSION PURPOSES ONLY” watermark is a small step in the right direction. What I’ve had more success with is to use fonts in working papers that drive home their intermediate status. This is a time when a font such as Charette or Papyrus sends a useful reinforcing message about the state of a knowledge work artifact.

Using Tools to Reinforce Your Intentions

We’ve been creative and adept at creating multiple digital tools to make knowledge work easier and more effective. We’ve been less thoughtful about how to deploy and use those tools to support all the relevant dimensions of our knowledge work processes. If we want to be more effective at knowledge work, then we need to be more intentional about how we fit our tools and processes to the tasks we undertake.

It was essentially a casting call. I was interviewing retired and semi-retired executives to fill a role in a training simulation we were building. We needed someone to play the part of the client CEO and someone had introduced me to Scott. Scott was a central casting silver fox, tanned from a recent visit to Florida.

I don’t know why I noticed it, but Scott was wearing a custom made shirt and the shirt had no pockets. I remarked on the missing pocket and Scott’s response sticks with me two decades later. Here was his logic, ”My job is to delegate work to my direct reports. If I have a pocket someone will want to hand the work back to me in the form of a question or a task. Without a pocket, there’s no place to put a note and no way for that to happen.”

That was a 20^th Century view of management and work. Just as well that Scott was about to retire. But the mindset persists; there is work and there is management.

Peter Drucker invented the term knowledge worker sometime around 1959—just another indicator of his prescience. We accept that we live in a knowledge economy but grapple with what it means to be knowledge workers. Organizations remain slow to accept all the implications of that line of thought. At the core, the distinction between worker and manager is disappearing. There may still be power dynamics, but you can’t readily discern who is working and who is managing by observing the tasks they carry out.

We are all struggling to make sense of the changing nature of work. There are grand policy level analyses on the implications for organizations, industries, and nation states. At the other extreme, there is an endless supply of tactical advice and tools for tackling very specific problems.

And, there is the middle where we spend our days trying to muddle through.

Maybe it was the time I spent in the wings at the boundary between what you see on stage and what goes on behind the scenes to make the magic happen. It gave me roots in that middle space. I chose to stay there, building connections between vision and execution. That began deeply immersed in designing and building technology and information systems to answer particular management questions about aluminum cans, soft drinks, industrial paints, or construction equipment.

Working in the technology space led to questions about business and organization that I couldn’t answer. That led me back to school several times and into multiple organizations in search of more insight. The schools gave me pieces of parchment attesting to my mastery of subjects they deemed worthy; chiefly strategy, information systems, and organizational design. The organizations I worked for and created put that knowledge to practical tests and frequently reminded me that parchment and mastery aren’t well correlated.

This has played out as we’ve all grown hardened, if not accustomed, to a world of accelerating change. The theatrical metaphor that helps me grasp what this change entails is a shift from scripts to improv. In a script world, we grow by adding to our repertoire of scripts we can call into play. In an improv world, we grow by learning to see patterns that we can play with and by collaborating with other players to create magic in the moment.

“It’s always best to start at the beginning.”
Glinda, The Good Witch of the South, The Wizard of Oz

Remember, Glinda isn’t real; nor is the opportunity to start at the beginning. We always start in the middle.

We’re better served thinking like MacGyver. Step 0 should always be to empty your pockets and look around. What do you have to work with?

Pretending to take out a clean sheet of paper is well-meaning but ultimately misleading. The goal of that clean sheet is to avoid ending up with little tweaks squeezed into “the way we do things around here.”  The only way to achieve that goal, however, is to build a comprehensive picture of the “the way we do things around here” together with an understanding of why.

That clean sheet of paper is one of those business cliches that sounds wise, yet conceals more than it reveals. The point of the clean sheet is to eliminate assumptions that no longer serve their purpose. But you can’t surface those assumptions without understanding the existing environment.

It isn’t the assumptions you see that cause problems, it’s the assumptions you miss. Better to have a fully marked up sheet of where you are actually starting and know what obstacles need to be addressed than to trip over something hiding behind the whiteness.

I’ve been thinking a lot about notes lately.

That led me into a stream of research and editorializing about the tradeoffs between taking notes on paper vs. at a keyboard.

The academic research seems to have started with:

• The Pen Is Mightier Than the Keyboard: Advantages of Longhand Over Laptop Note Taking – Pam A. Mueller, Daniel M. Oppenheimer, 2014

• How Much Mightier Is the Pen than the Keyboard for Note-Taking? A Replication and Extension of Mueller and Oppenheimer (2014)

Which generated various editorializing in the general press:

• Taking Notes By Hand May Be Better Than Digitally, Researchers Say : NPR – 2016
• Laptops Are Great. But Not During a Lecture or a Meeting. – The New York Times – 2017
• Should You Allow Laptops in Class? Here’s What the Latest Study Adds to That Debate – The Chronicle of Higher Education – 2019

Predictably, the consensus appears to be a definite “it depends.”  This debate presumes that there is a correct technology choice independent of any other consideration. As soon as you phrase it that way, the question reveals itself to be nonsensical. You have to have the “it depends” conversation.

The technology choice–pen in hand or fingers poised over keyboard–has to flow from an understanding of goals and objectives  and of  context.

The research speculates that the difference in performance between pen and keyboard is a function of speed. Handwriting is slower than typing and that forces those taking notes to summarize and distill what they are hearing. Those choosing to type are presumed to be striving to create a verbatim transcript. So, the researchers are confusing a technology choice with a strategy choice. What kind of notes you choose to take dominates the choice of recording method. Unless you control for the strategy choice, your research design tells you nothing.

The second driver of technology choice here is context. What environment are you collecting notes in and how does your technology choice influence the context?

When I was writing cases, I would often be working with a professor and we would both be taking notes. Similarly, in many consulting settings, there would be more than one person conducting an interview. In those situations, we would divide responsibilities with one person primarily managing the interaction and conversation and another primarily capturing notes.

As another contextual example, consider the increasing use of electronic medical records in health care. Doctors I’ve spoken with lament that keyboards reduce the quality of doctor/patient interaction. One response has been the use of medical scribes (Scribes Are Back, Helping Doctors Tackle Electronic Medical Records : Shots – Health News : NPR) to redistribute responsibilities.

All of this simply reinforces that “it depends” is always an appropriate response when considering technology options. Few choices are binary. Even for something as simple as capturing notes.

During my first job out of college I was assigned to work as staff on several financial audits. Consulting work was slow and the firm did not believe in idle hands. I was assigned to help with the audit of a major brokerage firm.

As part of the audit process, we had sent out letters to the firm’s several hundred thousand account holders asking them to return a form acknowledging that their account statements were correct or noting discrepancies if there were any. My task that first day was to sit at a conference table and count those forms. Each time I reached 100 forms I raised my hand and waited for an audit senior to put two rubber bands around my stack and take it away. I then counted another stack and the day continued.

I was granted a promotion the next day for my diligence at counting to 100. The slips of paper I had counted the day before had only a customer signature. Other slips had comments on them from customers. Some of those comments noted a discrepancy to be investigated; they claimed they held 115 shares of IBM, not 100, for example. Other slips contained what were deemed “gratuitous” comments; observations about a broker’s parentage or legitimacy were potentially entertaining but not pertinent to the audit.

I was not asked to make such a rarified judgment call; that was a task for trained and experienced auditors. I was considered qualified, however, to deal these slips out onto the glass of a photocopier, copy the slips front and back, assemble the results, and bind them into files to be saved as part of the audit working papers.

As mind numbing as you might think this experience was, it did drive home an idea about knowledge work that still echoes four decades later.

For all the exhortations on math tests to “show your work” I believed in answers. Showing your work was what you had to do when you didn’t get it.

Outside the world of classes and tests, showing your work was also something you needed to do when someone else didn’t get it either. Clients and managers weren’t necessarily doing to accept an answer just because you offered it up. You needed to be able to walk them through how you got there.

Lawyers call it a “chain of evidence”, scientists keep lab notebooks, artists make sketches on the way to a finished work, programmers version control everything.

The path between germ of an idea and final product can be long and convoluted. We so want to reach the end of the path—the answer—that we often fail to manage the trip effectively. That management task can be eased if we are mindful about the ways we design and introduce intermediate work products that support and fold into a final deliverable.

When I was in the fourth grade, we figured out that I needed glasses. I was complaining about having trouble reading what was on the blackboard and after moving to the front row didn’t solve the problem, I was dispatched to an eye doctor. Sure enough, I was nearsighted. A few weeks later I got my first pair of glasses.

I particularly remember the sense of wonder at discovering that street signs were something you were supposed to be able to read from inside the car as you drove by. My eyes weren’t shaped to see the world in 20/20 on their own but I inhabited a world where a simple prosthetic compensated for that limitation.

I also lived in a world and a time when nuns were quite happy to provide the structure and discipline a daydreaming young boy might need to complete his lessons. External supports, innate curiosity, and a few extra IQ points took me a pretty long way.

I survived—actually thrived—for a long time because I operated in environments that offered supports matched to my deficits. I was well into my 40s before I suspected that I had ADD. As my responsibilities and environment changed, I kept trying to get closer to the blackboard until I ran out of rows. What I didn’t have was a way to figure out what constituted glasses or how to get the right prescription.

What I had instead was a story of the Peter principle in action. I had blown past my abilities. My credentials were accidental; past performance is not an indicator of future performance. Now, it also turns out that ADD and depression are often correlated, so add that to the equation.

Having a way to name what was going on was a necessary but not sufficient step. It made it possible to have productive conversations with the experts. We experimented with the various meds that worked for many, but not for me. The compensating strategies I had developed over time were matched to environments I no longer operated in. One choice would have been to return to a matching environment. Unfortunately, those environments have continued to shrink in our modern world.

So that leaves the choice of formulating a prescription that lets me see the board in front of me. The benefit of this particular metaphor is that I don’t have to be discouraged when a prescription that works for some doesn’t work for me.

The tricky part is that we talk more about what the prescription is than we do about why and how it works. When we talk about eyesight, we know how to assess and correct for myopia and astigmatism. And we know why the corrections work. When we’re trying to compensate for deficits in managing focus and attention doing complex knowledge work, we have to dig deeper and build provisional theories as we experiment.

This is clearly a work in progress. I am curious about how others might be tackling presumably similar challenges of matching their work practices to the unique demands of their environments? What metaphorical myopias and astigmatisms are you dealing with? How have you gone about designing and implementing corrections that work?