Category: Knowledge work

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?

Tomorrow’s healthy organizations must make innovation routine. That’s a natural consequence of organizations becoming increasingly knowledge intensive while the half-life of knowledge also continues to shrink.

Routine innovation requires a shift from scripted responses to widely distributed improv capacity.

At first glance this is a straight reversal of organizational best practice. Organizations succeeded and scaled by transforming craft into standard operating procedure. The logic of the industrial revolution was anchored in scripting and standardization. We programmed technology and people to produce products and services at scale. We programmed people when the technology was too expensive or insufficiently flexible. As the technology evolved, we dispensed with the people whose work was now programmable.

Over time, this increases the proportion of people in organizations whose work is to do the design and programming; the script writers flourish until there are no more scripts to write. Concerns about AI and robotics boil down to script writers—programmers, analysts, data scientists, advertising creatives, etc—anxiety over whether or when they will write their final script.

What happens when the audience—or the market—demands performances faster than the scripts can be written and produced? There are three answers. The first is to speed up the writing and producing of scripts. The second is to settle for lower quality scripts. The third is to learn how to work without a script—to improvise.

The first approach seems to be business as usual for most organizations, the second, sadly, is appearing more and more frequently. It is the third which most interests me.

There’s a classic piece of career advice offered to those starting out, “fake it until you make it.” This is advice rooted in a scripted world where experts are thought to be those with the most robust collection of scripts. I think a more relevant view of expertise comes from a definition offered by Nobel Laureate Niels Bohr, “an expert is a man who has made all the mistakes which can be made in a very narrow field.”

From this perspective, an expert is someone who knows how to improvise safely in new situations.

If you grant this as a working definition of an expert, then experts are not those with the largest collection of memorized scripts. Beyond the scripts they have accumulated, they have learned a meta-skill. Beyond a deep understanding of multiple scripts, experts understand the structure and components of scripts so well that they can invent a new script in the moment in response to particular situations and moments. In short, they can improvise.

One of the mistakes that brought me around to this line of thought happened during a visit with a highly desired prospective client. We had gotten an introduction to this Fortune 500 organization through an academic colleague. Cracking open this account could keep multiple teams busy for years; we brought three partners and our CEO to the meeting.

After introductions and some talk about our general qualifications, one of the prospective client executives laid out a problem they were wrestling with. We pulled out our solving a strategic problem script and started working the problem in the meeting. Actually, a pretty solid way to showcase our expertise.

But, we were in script mode. The script runs all the way to an answer to the problem, which our CEO divined and promptly shared. We launched into a soliloquy when being fully in the improvisational moment would have led us back to a dialogue about the relationship we both desired not the transaction in the moment.

We never did any work with that client. We learned an immediate lesson about script selection. I’m still teasing out the implications of taking an improv point of view. I believe that the improv perspective is more suited to the mix of problems we now face. I believe that perspective is learnable. I suspect that it is not teachable but may be coachable.

If we’re lucky we connect with good mentors during our careers. I first worked with Mel in the late 1970s. Our paths intertwined over the years; I moved from Boston to Chicago to become one of his partners in the consulting firm we founded in 1994. He was CEO and holder of the central vision of what we became. I was Chief Knowledge Officer and Chief Learning Officer, which was a very grand title when we were 25 people; it became more representative as we grew to over a thousand in the next several years.

One of our points of disagreement crystallized on a drive home after another long day. His critique was that I cared too much about insight. As he put it, “95% of the people in most organizations are just pulling on the oars, they don’t need insight.” My response was to ask where did sails come from if everyone was pulling on the oars?

Mel was anchored in a classic individual contributor/hierarchical manager model of organization. Success depended on faithful execution of the scripts; managers monitored and controlled, contributors rowed. New ideas appeared infrequently and by magic; after careful vetting, new scripts were written, rehearsed, and deployed.

Organizations that survive and thrive do so because they are well-adapted to their environments. When environments evolve slowly, so can organizations.

Those environments don’t exist anymore. The current term of art is that today’s environments are VUCA—Volatile, Uncertain, Chaotic, and Ambiguous. Yet the show must go on; the curtain rises each day and the audience awaits.

The usual response is to row faster. A new script is written—or found, quick rehearsals take place, and we hope the audience is tolerant of the cast and crew’s mistakes.

The better answer is to reorient to an improv mindset and learn how to act more responsively and in the moment. This demands more of everyone in the organization. No one can be content to simply learn their lines or wait to execute their cue.

In the old scripted world, you could set up the joke and plan the special effect. It is a place of grand vision broken down into tactical execution.

An improv, VUCA, world exists between those two poles. The grand vision must relate to the audience/market’s interests and responses in the moment. Tactical bits must be selected and sequenced to move in the general direction of the evolving vision.

This calls for performers who can straddle the divide and support crew who can assemble platforms, bridges, and illumination in real time. Developing skill and competence in this dynamic performance demands more capable performers and practices designed to be adaptable.