You are always part of the system

A lifelong reading habit and skill with numbers meant that standardized tests were relatively easy for me. That plus marginal social skills helped me handle the first several hurdles in formal schooling with relative ease. I ticked off a succession of steps in a name brand educational resume and equally name brand early career stops. Come my early thirties, my new bride and I decide to shift from the corporate ladder climb to the academic path. I reach out to a favorite professor and apply to a doctoral program in business.

This is a qualitatively different process and experience. Instead of being one of hundreds or thousands competing to fill one of a thousand spots, I’m one of dozens seeking a handful of openings. To this point, the question has been “do we think you will turn out to be a representative example of the product we turn out?” Now the question becomes “do we want to let you into our club?”

Perfect scores on standardized tests are common. Transcripts with failing grades are not. Now, a relationship with a favorite professor takes on greater significance. To an admissions committee I am a potential risk. With an advocate, there is a compromise path. Leave your consulting position and take a position as a case writer working for your advocate. Prove to the admissions committee that you can produce quality work and they will reconsider in a year.

I did and they did.

What this became was an early step and an exemplar experience in a journey from connecting the dots to solving for pattern. An experience I lived through before I had the vocabulary to describe it.

Rather than rattling off answers to a standard question or teasing out a picture already concealed in a set of existing dots, I was learning a new process. One of formulating and posing questions to see what they might reveal.

A crucial aspect to this change in perspective is that you need to account for yourself when you are solving for pattern. You are part of the system you are trying to understand.

Exploring how to better solve for pattern

Over the next several weeks I’m taking a deeper dive into a phrase that’s held my attention for some time—”solving for pattern“. It’s from an essay by Wendell Berry. Berry was writing about farming as an exemplar of complex systems. What I know about farming is largely courtesy of Berry; complex systems, however, have been at the core of my work for decades. The systems I pay attention to are embedded in organizations; comprised of people, processes, and technology. 

Solving for pattern is a more powerfully evocative phrase than the one I more often encounter “connecting the dots.” Connecting the dots is trotted out as a way of simultaneously claiming cleverness and suggesting that everyone else is slightly stupid. Solving for pattern suggests a more appropriate degree of complexity and depth to the process of understanding. 

I’m planning on cheating a bit to get this exploration underway. Over the next several weeks I plan to piggyback off of a set of prompts provided by Megan Macedo. Megan organizes and coordinates a writing challenge about this time each year. She collects an eclectic group of writers and doles out a set of prompts over the course of the next several weeks. I’ve folded this into my calendar each of the last five years. This year’s overarching topic is about “letters and correspondence.” 

I think I can see a way to hijack that to my purposes. 

Organizational systems are built on top of conversations that have history and unfold over time. Sometimes those conversations lead to deep insight; sometimes they devolve into chaos. Let’s see whether we can keep mostly to the insight side of the ledger. 

There is no physics of human systems

An occupational hazard of acquiring a Ph.D. is adding lots of fancy new words to your vocabulary. Too often, these new terms devolve into weapons in status games. Sometimes, however, they clarify assumptions you didn’t realize you were making. “Nomothetic” and “idiographic” are terms you don’t pick up in casual conversation. They represent two distinct perspectives on making sense out of the world that explain a journey I’ve been on for years.

Let’s start with how the terms are defined;

  • nomothetic – relating to the study or discovery of general scientific laws.
  • idiographic – relating to the study or discovery of particular scientific facts and processes, as distinct from general laws.

Physics is all about the nomothetic; E=mc2 is true regardless. Economics aspires to be nomothetic, experience with trickle-down economics notwithstanding. Understanding Amazon or Apple, however, depends very much on the particulars of Jeff Bezos or Steve Jobs.

My own intellectual journey has been from the nomothetic to the idiographic. I was comfortable with mathematics and the hard sciences. Identify the problem, select the appropriate equation, crank the numbers and pop out the one right answer. 

I thought I would study psychology as an undergraduate but opted for statistics instead. I told myself this was because I was more interested in studying people than pigeons or rats. In retrospect, I wasn’t ready to accept that the messiness and particularity of human behavior as something you could study as a scientist.

Computer programming and systems design were holding actions trying to cling to the general and the universal. Debits and credits worked for all organizations and all situations. I could treat the vagaries of individual executives as mere noise within a larger system of order and predictability. 

I might have held onto that illusion if I hadn’t garnered a spot in the MBA program at the  Harvard Business School. Now I was at the center of the case study universe; the particulars anchored every discussion. I still didn’t have the words in my lexicon but I had begun the journey from the nomothetic to the idiographic; from the general to the particular. 

My comfort with individual courses correlated closely with where they fell on the spectrum from conceptual to concrete. Economics and accounting made sense, so did operations and finance. Marketing was a puzzle. Organizational behavior was mystifying; why did people insist on doing irrational things? 

My personal life was largely irrational at this point. Courtesy of wise friends I was getting professional help for that, but I still clung to a fading vision of systems and order. I went back to consulting and systems design. There were right answers to be developed and deployed. Resistance to those right answers was an aberration (if not an abomination) to be suppressed and eliminated. 

I could have pursued a classic strategy of accumulating enough power to impose my answers over the objections of weaker players. I’ve watched “my way or the highway” work (for certain values of “work”). I chose another path. I went back to sit at the feet of people smarter and more knowledgeable than I. What more could I learn from those who started by accumulating stories and case studies? I’ve written about this before 

This was where I finally learned of the distinction we’ve been talking about between nomothetic and idiographic. It’s comforting to discover that you are not the only one engaged in an important struggle. 

How we come to know things isn’t a conversation that happens in the average business context. In a world dominated by knowledge work and innovation, however, it’s a conversation that needs to move center stage. 

Organizations push for standardization and uniformity – this solves problems that organizations have to deal with. In the realm of knowledge work we have been too quick to assume generality before we’ve gathered enough data and insight about the richness and variety of actual practice.

In Ph.D. speak, nomothetic claims about human systems have to be filtered through an idiographic lens. 

That isn’t a sentence I would want to utter in a boardroom. What I would advocate instead is to drop one common phrase and substitute another. 

Stop talking about “connecting the dots.” Buried in that phrase is an assumption that there is already a right answer hiding in plain sight. The only work to be done is correctly recognizing the picture that exists. The particulars of this situation, in this moment, are mere noise obscuring what should be readily obvious. 

If you’ve come to hold the particulars in higher regard, then you will be better served to frame your task as that of “solving for pattern.” I’ve written about this shift of perspective before

There are no equations that we can plug data into and expect a clear answer. But for all the particulars in any new case, there are regularities and patterns we can use in shaping effective responses.

Increasing Knowledge Work Discipline

I stumbled across an interesting opinion piece in the Washington Post recently; want kids to learn math? Level with them that it’s hard. Learning to do knowledge work, like learning to do math, takes disciplined work. Tiago Forte is one of the people putting in the necessary work and sharing what he’s learning with the rest of us. In this piece, Forte turns to the kitchen and the realm of professional chefs for insight. Particularly, their obsession with order and preparation; mise-en-place.

Knowledge work lessons from the kitchen

Forte explores the following mise-en-place practices for relevant parallels to knowledge work 

1. Sequence

2. Placeholders

3. Immersive vs. process time

4. Finishing mindset

5. Small, precise movements

6. Arrangement

“Sequencing,” for example, looks at how decisions about the layout of tools and ingredients aids or hinders the flow of execution. You don’t want to be rummaging around for a whisk when you need one. Thinking through the process before executing will surface opportunities to sequence work to your advantage. 

Forte’s riff on “immersive vs. process time” may be the most interesting. Forte maps immersive time to Cal Newport’s deep work distinction. Process time on the other hand encompasses settings with a time component that runs independently of your attention and focus. In cooking, process time might be the 15 minutes it will take for rice to cook regardless of when you start the process. It may only take a minute of your attention to launch that cooking process but you want to take that minute of focus when it will do the most good. Start the rice now and it will be ready when you need it later. Wait, and you delay the entire process while you watch the rice cook. 

There are times when the back burner is the right place for the rice to be cooking while you pay attention to something more important. In knowledge work, the example that springs to mind is Stephen King’s advice to stick a freshly finished manuscript in a drawer for six weeks while you attend to something else. Doing that is taking advantage of your subconscious mind’s capacity to work on creative tasks without your input or attention. 

A sticky sequencing problem

Forte has been developing and sharing his system for managing knowledge work for several years now. His Building a Second Brain training course is highly regarded. Although I haven’t sprung for the course, I do pay for access to his other materials and have read his books. I’m picking on Forte here in much the same way that Alan Kay once described the Mac as the “first personal computer worth criticizing.” Whatever it’s flaws, his analysis sparks responses that move the entire argument forward. 

There’s a bit of a sequencing problem in his own analysis, here, because he’s invested so much time in his own systems. His analysis of mise-en-place is unavoidably influenced by the design decisions he’s already made and internalized. 

Here’s an example of where Forte’s current thinking distorts his analysis of mise-en-place. Talking about the role of sequencing tasks, Forte asserts;

Once we realize the importance of sequence, it becomes apparent that not all moments are created equal: the first tasks matter much more than the later ones.

I will grant the first part of his claim; all moments are not equal. It does not follow, however, that “first tasks matter much more than the later ones.” Forte wants to make a point about the importance of first tasks; that’s pretty conventional wisdom in multiple traditions and settings. But I think it is a hill too far to make a blanket assertion that first tasks always matter more than later ones. In fact, Forte contradicts his own point a bit later when he talks of the importance of a “finishing mindset.” 

You encounter ideas in the order you encounter them. The best you can hope for is to be cognizant of that and temper your assessments and enthusiasms for related ideas as you discover them.

A more troubling flaw in the argument

There is a lot to like in Forte’s exploration of mise-en-place. There’s a critical step in his argument, however, that I object to. Forte turns to the world of professional chefs because

It’s time that we had a working system for the mass production of high-quality knowledge work

“Mass production of high-quality knowledge work” is a nonsensical proposition. As a diner in a restaurant, my serving of Coquilles St. Jacques Provencale had better well be identical in all important respects with my dinner companion’s. But don’t try to hand me the marketing strategy you just prepared for my chief rival. Balancing Uniqueness and Uniformity in Knowledge Work has to drive the design of knowledge work practices and methods.

There are things to be learned about doing better knowledge work from contemplating mise-en-place. Knowledge work that makes an impact is more about inventing new recipes than about being more efficient and productive in churning out known recipes for tonight’s diners. You do want a solid mise-en-place set up before you embark on experimenting with recipes. You want your environment set up and tuned so that you can focus your attention and creativity on inventing some new and wonderful delectable. But if the lunch rush is at the door, you’re not doing knowledge work, you’re doing production work. And you need to be clear about the difference. 

Don’t ask what is best

Dad was an engineer by training and temperament. His handwriting was as neat and precise as mine is not. He worked hard to express his thoughts clearly. 

My processes look and are much messier than his ever were. One trait I did inherit, however, was to worry about using language precisely. And, I was fortunate to have mentors who cared equally about precision. It isn’t something that seems a high priority in many current settings. 

There’s a question form guaranteed to set me off; “what is the best way to…?” I’ll grant that such questions are generally well-intentioned but are weighted down with so many unidentified and unarticulated assumptions as to be devoid of meaning. 

While such questions come from a good place, pushing back on their fuzziness won’t win you many friends. I’ve learned to be very cautious and selective about raising them in public. What I have tried to do is become more aware of when I am asking those forms of questions for myself. With that comes more effort to be more precise about the question I am trying to answer and to search for those assumptions. 

This is the underlying driver for my skepticism about exploring productivity in the context of knowledge work. Productivity is anchored in comparisons of “better” and “best” and I’m not sure those terms carry as much meaning as we might think. Instead, I’ve been working to shift my thinking toward the notion of “effectiveness.” It’s still too slippery a term but it does encourage me to widen my perspective to find those assumptions, understand the context, and be more precise about what I am hoping to accomplish. 

Rebalancing Planning and Doing: Seeking Knowledge Work Effectiveness

When I was first learning to be a project manager one of the mantras drummed into me was “plan the work, work the plan.” Hidden in this advice was a distinction between planning and doing. Today, we are immersed in doing; managing has been pushed to the margins. “Plan the work, work the plan” has shrunk to “work, work.”

Cal Newport, in his most recent book A World Without Email: Reimagining Work in an Age of Communication Overload, argues the case that email is the culprit. More specifically, the work style promoted and encouraged by email and other forms of instant communications. He labels this the Hyperactive Hive Mind, 

A workflow centered around ongoing conversation fueled by unstructured and unscheduled messages delivered through digital communication tools like email and instant messenger services.

Tom Davenport has often quipped that the default management strategy for knowledge workers is to “hire smart people and leave them alone.” This strategy can work if most knowledge work is independent; if your model of knowledge work is the individual data scientist, college professor, or computer programmer. 

Organizations, however, don’t exist to tackle problems that individuals can handle. They exist for problems whose scale and complexity exceed the capacity of any individual. We understand that for problems like churning out automobiles, breakfast cereals, or insurance policies. For those problems, organizations have learned to spend time to design processes that work at scale, spend time to deploy those processes, and then run those processes at scale. Running those processes at scale requires designing in the instrumentation and measurement to monitor and maintain compliance with the process. There is planning followed by doing.

Newport’s thesis is that email (and other channels of instant communication) disrupts this balance of planning and doing. The immediacy of message and response rewards one set of behaviors while concealing important costs.

This is where Newport’s and Davenport’s perspectives intersect. While we were deploying email and its cousins throughout the organization, we were also leaving all those smart people alone to figure things out on their own. We amped up the doing and left each knowledge worker to their own devices to do whatever planning seemed appropriate. 

While Newport is an academic computer scientist, he does manage to find his way to Peter Drucker’s work. Newport, Davenport, Drucker, and pretty much anyone else who’s thought about it, identify knowledge worker productivity as the problem to solve for modern organizations. Newport, however, does miss this observation from Drucker;

Whenever we have looked at any job – no matter how many thousands of years it has been performed – we have found that the traditional tools are wrong for the task

Email may not be thousands of years old, but it is the wrong tool for many tasks. At least in the way it is typically used in most organizations. 

The second half of Newport’s book works through several good approaches for attacking the problems he lays out so well. While some of his strategies can be applied unilaterally, most are premised on no longer leaving smart people alone. 

To achieve better overall outcomes, organizations need to rebalance planning and doing with respect to knowledge work. This is no longer a task that can be left to the individual knowledge worker. That leaves us trapped in a world of productivity hacks and the search for the magic shiny tool. We’ve all seen that that doesn’t work. Newport adds stronger evidence for why that approach can’t work and pointers on where to go next. The first step is to elevate the conversation to the organizational level; to put the topic on the agenda of those with the power to drive change. 

Planning to be Creative

When I was a very junior consultant, we were coached that there was one client question you were neither expected or allowed to answer, “how much is this going to cost?” A few years later, in the midst of getting my MBA, the one question you were trained to ask and answer was “how much is this going to cost?” Lately, I’ve been thinking about how much of my career has been spent caught between these two pieces of conflicting advice.

Nailing down answers to that question is a matter of nailing down assumptions. What materials from what suppliers? How many customers in each market? What’s the going rate for good sales reps? All reasonable questions; they all depend on knowing what you are doing. 

They are also generally impossible to answer when you don’t. Pretending to more knowledge or foresight than you have isn’t a recommended approach. As an individual manager, what do you do when faced with this dilemma? You’re being asked for answers to questions you are still trying to formulate. How do you work at articulating outcomes to drive planning when your fuzzy view of outcomes is what you are trying to address?

Too often, the default answer is to accept the brashest claim to knowledge in the meeting. “I have the answer” wins out over “let’s explore and see what we can learn.” We need to replace that default with approaches more likely to surface answers that we couldn’t know beforehand but outstrip the obvious, safe, and, ultimately, disappointing answers limited by what we already know.

You still have a project management task; organizations do not have unlimited resources even when the questions are open-ended. You are not simply executing, you’re also doing field research. The project management task is to thread a needle between systematically managing effort, tasks, and resources and what the phenomena in the field are revealing about how to adjust and redirect those resources and tasks. 

This marriage of exploration and execution is what agile methods are seeking in the realm of systems development. But the strategy extends to any setting where the destination has to be discovered or invented. With apologies to Gene Kranz, failure is always an option. It just shouldn’t be the only one.

The Promise of the Middle: Improving Knowledge Work Practices

Two years ago, I stumbled across Sonke Ahrens’ slim volume, How to Take Smart Notes: One Simple Technique to Boost Writing, Learning and Thinking – for Students, Academics and Nonfiction Book Writers. As a matter of practice, I am always on the lookout for potentially useful new ideas. The price of a book is a trivial cost and I only invest my time for as long as I’m learning something useful. I posted my review in March of 2019 [Unexpected Aha Moments \- Review \- How to Take Smart Notes \- McGee’s Musings). This is a bit of an interim progress report, although it feels more like a lament on just how hard change continues to be. Andy Matuschak’s recent observation that Note\-writing practices are generally ineffective hits way too close to home. 

Carving out an approach

Advice is always forward looking. The pretense is that you are starting from scratch. The reality for most of us is that we start somewhere in the middle. The problems of dealing with your existing bad habits and your existing body of work are left as an exercise for the reader.

One option is to pretend that you are starting from scratch. Ignore whatever artifacts and work in progress you’ve created to this point as well as whatever practices you’ve adopted. Start fresh with whatever your next project happens to be. Follow the proffered advice, practice new techniques, create new work products.

A second option—one that turns out to be a trap—is to believe that you need to fix or repair your history before you can move forward. It’s a trap I’ve fallen into. 

A middle approach that has evolved over time is to think of a knowledge work environment as a property that needs regular maintenance and remodeling plus occasional renovation. You do prefer to work with the materials already at hand, introducing new materials as needed. It’s also an environment that must support routine work; historic preservation is not the goal. 

Artifacts and Activities

My training and experience push me in the direction of organizing around projects and deliverables. I’ve begun reconsidering that (e.g., Deliverables and the downside of working backwards \- McGee’s Musings) and working toward a more nuanced view of knowledge work products.

There are some additional degrees of freedom to be found by shifting to more neutral terminology. I’ve started to think about what might be gained, besides alliteration,  if I start thinking in terms of “artifacts” and “activities.” 

Artifact encompasses deliverables but also extends to intermediate working papers. Anything that gets thinking outside of your head and into a representation that you can inspect and manipulate is worth considering. 

Some sequences of activity may be worth treating as discrete projects. But other sequences and patterns of activity may be worth incorporating into your repertoire and pairing with appropriate artifacts. 

Artifacts plus Activities Become Practices

The notion of “practice” has been floating around in my head for some time now. It isn’t something so structured as a process. Nor does it rise to the level of a project to be managed. But it does seem worthwhile to stay alert for stable patterns of artifacts and activities that yield insight. 

One implication here is that you should be attuned to two levels of thought. There is the ongoing work itself. And, there is a parallel level of the work of managing the work.In routine work environments, work and management are typically carried out by different players. In knowledge work, work and the management of work falls to the knowledge worker. I find it helpful to try to keep the two levels separate in my thinking. 

You never start from a blank sheet of paper

This train of thought appropriately brings me back to a piece I wrote some six months ago—Embrace the mess if you want to do better knowledge work. The trope about writing and writer’s block is the threat of the empty page or the empty screen. Unless you are at the absolute beginning of the path, this is an illusion. None of our work begins in the void; we’re always in the middle of one journey or another. Take advantage of wherever you are and start there.

Aspiring to Knowledge Work Professionalism

WorkstationIn April, 2003, the late Doug Engelbart gave the Keynote Address at the World Library Summit in Singapore; “Improving Our Ability to Improve.” The talk is an excellent entry point to one of his most powerful ideas. He also raises a specific question that I suspect wormed its way into my thinking back when I first encountered it. 

As an aside, I wish I could reconstruct the concatenation of events that led me to revisit the talk yesterday. I’m confident it was a revisit because I’ve been following Engelbart’s work for a long time and this piece was already in my systems. My note-taking and reading management systems are not so well-constructed, however, that I could do more than recall the essence of the piece. On the other hand, returning to old source materials can  pay dividends. The source may not change but my perspectives evolve.

Engelbart’s career was dedicated to exploring how information technology could augment human intelligence rather than displace it. He was especially interested in how that partnership could attack big, complex, problems. 

Shovels and bulldozers, to borrow and extend Engelbart’s analogy, both move dirt. If you have a lot of dirt to  move, a single shovel isn’t your best choice. If no one has managed to invent a bulldozer yet, you might be limited to shovels but you aren’t limited to a single shovel. 

Given a collection of shovels (and shovelers), you can organize the problem of moving dirt into a process. Process is an amplifier. With a layer of process in place, you can get further amplification by looking for ways to improve the process. Engelbart identifies one additional amplifier; improving how we do improvement. Engelbart labels these three amplifiers as A-activity, B-activity, and C-activity. It’s a simple enough model, but simple models can be very powerful. 

At the base (“A-activity” in Engelbart’s terminology), you have the realm of process; the monthly billing cycle, managing trouble-tickets at the help desk, the assembly line turning out Toyotas. The economy is built on transforming ad hoc practices into standard operating procedures and repeatable processes.

Repeatable processes that produce repeatable outputs open up the possibility of systematic improvement. What changes can you make to the process while holding the outputs constant? Process improvement (the “B-activity” in Engelbart’s model) is the realm of quality management, business process re-engineering, and continuous improvement. It’s an amplifier of benefits flowing from repeatable processes.

As an organization accumulates more experience with process improvement and more opportunities for process improvement surface, there’s another level of leverage in investigating how you can get better at those improvement processes (“C-activity”).

What Engelbart is doing here is employing a classic computer science problem solving strategy; adding a new layer of indirection or abstraction. Rather than attack a problem head on, step back from the immediate features and adopt a new perspective. Engelbart explores this three-tier model in more depth in Toward High\-Performance Organizations: A Strategic Role for Groupware \- 1992 \(AUGMENT,132811,\) \- Doug Engelbart Institute.

Returning to the keynote address, Engelbart launches into a bit of a rant about “ease of use” and letting the market decide what features and functions should be available. He isn’t a fan. As I was nodding along, Engelbart posed a question that grabbed my attention; 

Doesn’t anyone ever aspire to serious amateur or pro status in knowledge work?

If your answer is yes, then you have a problem in the context of the current information technology market and the purchasing preferences of most organizations. Those forces favor tools and services targeted toward beginner and intermediate levels of expertise. Think of the standard software installed on the typical corporate workstation. What training is provided on how to take full advantage of even those tools?

Reaching expert level performance in any field doesn’t happen by accident or by the simple accumulation of experience. It requires deliberate practice and a commitment to operate across multiple levels of perspective.