Learning, bodies of knowledge, and half-lives

half life curveWe think of learning relative to a body of knowledge; we talk about learning a foreign language, data science, corporate finance, or carpentry. Academic degrees are built around demonstrating mastery of a body of knowledge.Professions are defined and certified in terms of mastering a specified body of knowledge.

I have two problems with this thinking from the perspective of learning. Who specifies what constitutes the relevant body of knowledge? And, how do you handle the problem of updating the body of knowledge? The way we conventionally think about those two questions seriously interferes with our ability to learn in the environment we face.

What is it about the environment that triggers my worries? The pace of change. We’re familiar with Moore’s Law, for example. There is the exponential growth in multiple measures of data and information. There is the exponential growth in scientific publications.

The simplest organizing idea here is the notion of the half-life of knowledge. We know that this half-life is shrinking in all sorts of fields.

What happens when that half-life is shorter than the time it takes to update a relevant body of knowledge and fold the new knowledge into certification processes and school curricula? Professional associations worry about this. Schools doing curriculum design worry as well. Organizations that find schools and professional associations moving too slowly worry and respond by creating corporate universities.

What does it all mean from the perspective of an individual trying to cope? What do you do if you understand that you can’t simply turn the problem over to the experts?

The standard responses of going back to school or trusting in the continuing education requirements of your chosen field are insufficient. All of those responses are rooted in the assumption that learning is simply about mastering a body of knowledge.

One of Alvin Toffler’s oft-quoted observations is that “the illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” He had a handle on this problem. We need to master another layer of skills, to see the body of knowledge as something dynamic and evolving.

From that vantage point we take on responsibility for actively updating and maintaining the bodies of knowledge that concern us. Whatever our central interests, we have to also acquire basic competence in how learning works and in how knowledge is created. We need to become our own curriculum designers and our own research directors.

Temporary technology limits shouldn’t become design patterns

Things are the way they are because they got that way

– Ken Boulding

This is a quote attributed to Boulding by Jerry Weinberg in his excellent Secrets of Consulting. My students will tell you that I am fond of bringing it into many a class discussion. It’s somehow more useful to me than trotting out Santayana’s observation about learning history.

We’re all hot for the new, new thing and innovation is always better when it’s disruptive. For all that, when thinking about new technology we would do well to spend time and thought understanding how we got to the current situation. Predicaments today grew out of decisions yesterday that made sense when they were made. If we want to leave fewer predicaments for our successors, we need to understand how those earlier logic trains derailed.

For example, consider the Y2K issue of the late 1990s; the transition from 1999 to 2000 raised the threat that computer programs might fail because of the common practice of storing only the last two digits of the year in computer files and databases. That common practice grew out of technology limits with storage and data access. There was also an unexamined assumption about the likely longevity of the systems being built in the 1960s, 70s, and 80s. Why worry about a problem that was decades in the future; surely the programs would be replaced long before then.

There seems to be a deeper issue at work that is troubling me. Design is always driven by constraints and requirements; what limits exist on what you hope to do. We fail to appreciate how technology constraints evolve very differently from other constraints. We treat certain limits on our designs as if they were integral to solving the problem at hand when they are actually temporary speed bumps in the technology. We solve the immediate problem—the dates in our files fit the space available—at the expense of creating a bigger problem later.

We talk of “technical debt” but I don’t think the notion works with less technical decision makers. Debt suggests you trade future interest payments for a solution now. What we do instead is lock the organization’s future within boundaries that disappear and make us look stupid to those who designed smarter.

Organizational decision making is often hampered by shortchanging the future. We don’t seem to have good methods for avoiding these mistakes in technology. Temporary technology limits become design constraints which become design assumptions that get baked into design patterns and then outlive their usefulness.

Project management, rocket science, and donuts

time to make the donutsDunkin Donuts ran a legendary ad campaign in the 1980s—“Time to Make the Donuts.” You can still find the ads online. They celebrated commitment to doing the work. What they ignored was the need to manage the work. In fact, they reinforced the idea that work and management were two distinct things.

For making donuts or widgets or Toyotas this is possibly a useful distinction. For the work that most of us do today, it does more harm than good. In the donut world work is about following recipes and management is making sure that workers follow the recipes. There’s a lot that can go into following and managing recipes; how accurately do workers follow the recipes, how fast, how many per shift.

But where do the recipes come from?

If you’d prefer to remain in a worker/manager universe, they arrive by innovation magic. Some mysterious, creative process serves up new recipes and processes to be plugged into the existing system. Perhaps there will be some change management pain and disruption to be absorbed. Perhaps you will turn to some specialist or consultant to carry out this odd work. Then, everyone can get back to work.

I think this explains something I always struggled to understand when pitching consulting projects or proposing change efforts within organizations. Decision makers always seemed to object to the project management line item and tasks in proposals and plans. For that matter, project team members weren’t keen on the process of managing the work; they wanted to focus on what they saw as the fun part of the work.

It all makes sense if doing and managing are two separate activities. But you can’t do that when they are intertwined. When the doing shapes what needs to be managed and the managing calls for picking your way through the doing then you are much more tightly coupled than the mythology of workers marching forward as managers point to the goal in the distance.

I’ve been fascinated by NASA’s recent flyby of Ultima Thule by the New Horizons Mission. If you’re interested, I’d recommend a recent Nova broadcast, Pluto and Beyond. One thing that struck me was that project management isn’t rocket science but successful rocket science certainly depends on effective project management.

This all matters because the work we are all doing these days is a lot closer to rocket science than it is to making donuts. We’d better start acting as if we believed that.

Review – Dare to Lead by Brene Brown

brown-daretolead-cover Dare to Lead: Brave Work. Tough Conversations. Whole Hearts. Brene Brown

I’m a latecomer to Brene Brown’s work. “Dare to Lead” is her most recent book and the first I’ve had the chance to read. My loss and easily correctable.

If you go to Amazon, limit your search just to books, and enter “leadership,” you get over 70,000 results. An evergreen topic to be sure and, as a student of organizations, one I’ve been tuned into for decades. This entry is worth your attention.

Brown starts with a definition of a leader as “anyone who takes responsibility for finding the potential in people and processes, and who has the courage to develop that potential.” Leadership is about how you act.

I found it particularly interesting that she deems curiosity to be an essential and central element of effective leadership. Leadership is a willingness to pick a direction and walk into the unknown. Brown draws on work by Ian Leslie who makes this observation:

Curiosity is unruly. It doesn’t like rules, or, at least, it assumes that all rules are provisional, subject to the laceration of a smart question nobody has yet thought to ask. It disdains the approved pathways, preferring diversions, unplanned excursions, impulsive left turns. In short, curiosity is deviant.

This is a take on leadership that may not mesh with conventional cliches. But Brown builds a persuasive case.

She has practical advice as well. Leadership is a skill that develops with practice; learnable, probably coachable, likely not teachable. Among the many ideas Brown offers are two that I expect to add to my own practice immediately. The first is a call to “paint done,” which asks for more imagination than a more conventional “define what equals done.” I can see how I would tackle that.

The second is a conversational gambit Brown calls “the story I make up…” The premise is that we are always making up stories to account for the behavior we see in others. Those stories are generally wrong on multiple dimensions—Google “fundamental attribution error.” Brown’s insight is that if we share the assumptions we are making and defuse them by acknowledging that they are just stories, we can get to a new, shared, story that will let us make real progress.

This is a book I will be returning to. Brown brings a rare blend of research skills and direct leadership experience to her work. Leadership is always in shorter supply than what the world demands.

You can’t separate learning and doing

If I’m not careful when I introduce myself, “Jim McGee” gets heard as “Jimmy.” Curious as that was what I was called growing up. Outside of family and a few cousins, there were only two people who regularly called me “Jimmy” One was the director of the college theater group I was in. The other is a friend and colleague I worked with during my doctoral studies.

Although it’s a pretty common name, I take a certain perverse pride in laying claim to “jimmcgee” or “jmcgee” as a user name in places like gmail and twitter. It’s a marker of being an early adopter on multiple technology platforms.

You learn stuff by playing with it. But learning and play are suspect activities in most organizations. Outside of schools, the presumption is that you’ve learned what you need to know on someone else’s dime. Even in schools, you pay for the privilege of not knowing and being a learner.

This model works in a stable or slowly-evolving environment. There are places where you learn and places where you do. If you are in a doing place and the learning places are lagging, you might find it a good idea to create a private learning place to bridge the gap. But the idea of doing and learning remain separate.

I could argue that this is fundamentally wrong for all organizations and all times; that the separation of learning and doing is an artificial distinction that only works with the right confluence of factors and only for limited periods. We’re no longer in one of those periods.

We’ve been living through an extended period of accelerating change; it’s become an empty cliche. This is a cliche that you ignore at your peril. The half-life of what we know continues to shrink.

Half-life is a notion borrowed from nuclear physics. Radioactive elements and isotopes transform at a predictable rate; the transformation of Carbon-14 into Carbon-12, for example, is one of the facts that tell us that the world is more than 6,000 years old. The time it takes for half of the Carbon-14 in a sample to decay into Carbon-12 is the half-life and is a fixed and measurable rate.

Shifting back to knowledge and knowledge work, much of what we knew from our school days has decayed in similar fashion. By some estimates an engineering degree has a half-life of less than 10 years.

If you maintain the fiction that learning is something that occurs in learning places and is separate from doing, then you hire young computer scientists, move a handful into management, and replace the rest on a regular basis. A stupid management strategy, even it is appears to be a common one.

In work with a university research lab that was dealing with growing pains, I found the phrase “smart people doing smarter work” a helpful entry point toward a more effective response. There’s been a trend in knowledge intensive organizations toward hiring more people with Ph.D.s. At first glance, this can be viewed simply as seeking out people with more recent expert knowledge. The deeper truth is that a Ph.D. is someone who lives at the boundary of learning and doing; someone who understands that it is not, in fact, a boundary.

When I was a student, teachers were the people who had answers. If you had questions, you found the expert who had answers. When I was a consultant, I was an expert. When I reached the edge of what I knew, I looked for the next expert. Eventually, I reached a point where I ran out experts who knew. Since I was still operating from a learning and doing are separate things perspective, I went back to a learning place.

What I discovered was a community of fellow explorers who introduced me to a new practice, which was to say “I don’t know, let’s find out.” I was at the place with the half-life of knowledge problem was being created and attacked in parallel.

It’s certainly possible to treat this spot as just another place for experts. You can choose to be an expert at the edge, asking questions and passing answers back the chain to others who desire answers. What’s more interesting is to ask how to respond in a world where all of us operate closer to the edge of “I don’t know, let’s find out.” What if we looked to those already operating at the boundary between learning and doing as guides for traveling in this strange territory? What tools, practices, and habits of mind can we adopt to travel more effectively and safely in an environment where change is a feature not a bug?

What problem are we trying to solve?

Lever“Give me a lever long enough and a place to stand and I will move the Earth” doesn’t work if you are standing in the wrong place.

It’s tempting to focus on the lever—to make it longer or stronger or out of some new  material. What you aren’t likely to do is take the lever you’ve got and look for a new place to stand. Nor are you likely to ask whether a lever is the relevant tool.

One of the courses I teach is on Requirements Analysis and Communications. The goal is to equip students with the tools to articulate a problem with  enough detail and precision that a effective solution can be designed and implemented. That phrasing is awkward because all too common practice is to define problems in terms of known solutions.

It’s the inverse of children with hammers pounding everything as if it were a nail. It’s claiming you have a nail to be pounded because someone with a hammer has come along.

None of this is any easier in a world rife with voices clamoring that they have the magic hammer for X.

Everybody has an answer. Everybody is selling a solution. Everybody has a hammer.

How do you learn

  • to take the time
  • to ask the questions
  • that will define the problem first?

The root question is always “what problem are we trying to solve?” The first several rounds of answers to that direct question are always statements of a solution, which is not a statement of a problem.

Asking effective questions is a learnable skill. I can give you a list of useful questions and I can lay out a process for asking them. But, what you really need is an opportunity to observe effective questioning in action, to practice in a safe environment, and to get feedback.

What I’m describing, of course, is the case method—either law school of business school flavor—or problem-based learning. What’s less emphasized is that these are inquiry processes; they are about questions, not answers. That makes them frustrating when you’re accustomed to being rewarded for answers, whether in school or in life.

The way out of that frustration is to understand the goal is building a skill not parroting an answer.

Review – Measure What Matters

Measure What Matters: How Google, Bono, and the Gates Foundation Rock the World with OKRs. John Doerr

I have a collection of T-shirts received as Christmas gifts from my wife. In that collection is one that expresses an all-too-common management practice, “the beatings will continue until morale improves.”

Most management books strive to offer better advice. Long-time venture capitalist, John Doerr, has been an evangelist for OKRs, an approach developed at Intel and in vogue across Silicon Valley. “Measure What Matters” is Doerr’s effort to package the approach for wider dissemination. It’s an approach well worth understanding.

OKRs is short for Objectives and Key Results. Doerr characterizes it as “a collaborative goal-setting protocol for companies, teams, and individuals.” Doerr and the other advocates for OKRs are engineers by training and temperament; they think in terms of elegant, interlocking systems. Well-designed OKRs are just that; the kicker is that “well-designed” is the hard part and it’s easy to miss that in the cheerleading.

Doerr defines the system as:

“A management methodology that helps to ensure that the company focuses efforts on the same important issues throughout the organization.” An OBJECTIVE, I explained, is simply WHAT is to be achieved, no more and no less. By definition, objectives are significant, concrete, action oriented, and (ideally) inspirational. When properly designed and deployed, they’re a vaccine against fuzzy thinking—and fuzzy execution. KEY RESULTS benchmark and monitor HOW we get to the objective. Effective KRs are specific and time-bound, aggressive yet realistic. Most of all, they are measurable and verifiable.

Who could object?

The rest of the book elaborates on this and walks us through a number of case studies of the challenges of putting the theory into practice. Doerr is quite explicit that the “regimen demands rigor, commitment, clear thinking, and intentional communication.”

He acknowledges that “ideas are easy—execution is everything.” Digging into the case studies and thinking about the richer stories that are compressed into the retelling is essential. Doerr tells us this if we are paying attention; “what’s neat about OKRs is that they formalize reflection.”

Today’s organizations and markets are too complex for a single mind to comprehend. You need to engage as many minds as possible to wrestle with the complexity. OKRs give you a process and a language system but success depends on the conversations that you have with the language.

Doerr only hints at the communications challenges that lurk underneath. How do you distinguish a “goal” from an “objective?” I’ve seen that conversation go in circles for hours. You can have theological debates about OKRs as well. It tempting to talk about the theology, but progress comes when you bring the conversation down to the level where you agree on specifics.

If you’re so inclined you may want to start with Doerr’s TED Talk but “Measure What Matters” needs to be on your reading list.

Process and Ritual

ring of fireWhile there’s no obligation to explain your process to anyone, working it out for yourself does matter. There’s an observation from Aldo Leopold that’s pertinent:

The last word in ignorance is the man who says of an animal or plant, “What good is it?” If the land mechanism as a whole is good, then every part is good, whether we understand it or not. If the biota, in the course of aeons, has built something we like but do not understand, then who but a fool would discard seemingly useless parts? To keep every cog and wheel is the first precaution of intelligent tinkering.

In my previous post, I spoke about the broad spine of my process. There are aspects that feel important although I’ve yet to fully understand their fit and there are other elements whose purpose escapes me but I’m reluctant to set them aside. Learning, for example, appears in multiple non-obvious ways. I allocate substantial amounts of time to reading, of course; the world moves too quickly to rely simply on the accumulation of experience. I also try to have some topic I’m learning that is new to me; as a teacher, I want to always know what it feels like not to know something.

My writing practices have evolved over the years. I’ve gradually become more comfortable with letting writing evolve. When I wrote my first book, Ernst & Young provided us with an editor to work with us as we developed the manuscript. One day, John met me in my office. As I handed him the draft of my most recent chapter, I had to take a call from a client. As I spoke with my client, I was puzzled as John flipped past the first three pages and began reading the draft at the top of page four. When the call finished, I naturally asked John why. He gently explained that he had learned that I had a habit of clearing my throat for several pages and burying the lede; page four turned out to be a fairly predictable first place to look. I’ve gotten better at discovering my lede without outside assistance and putting it where I think it belongs intentionally.

Some find writing by hand a useful element of their process; my handwriting is both too slow and too illegible to help in that regard. What I have learned, however, is that it is valuable to capture snippets of ideas and phrasing as they occur to me. Technology makes that a more reliable process. What warrants further improvement is moving from snippet to finished product.

One practice that has helped at the outset of new projects is to write a “memo to self” that outlines a storyline of the effort as a whole. This is something other than a project plan. A project plan focuses on the sequence of tasks; the storyline is an attempt to find the intellectual thread that will connect facts, insights, and conclusions into a path forward.

I can’t necessarily explain why this works. But I treat it as a form of ritual. Whether you understand the ritual doesn’t matter; what’s important is that you commit to the practice. The open question is how to make these elements more visible to the people I am working with.

Quest for the organizing thought

crystallizationI thought of starting this piece with an observation that talking about my process risked spiraling out of control until I realized that feeling was, in fact, a part of my process. The most satisfying part of my work is bringing new things into existence. An essential step is generating enough raw material to ensure that something good and pleasing is likely to emerge

The process is about designing new capabilities. The domain is technology use to support organizational performance. The process and the domain combine to define a practice but it’s helpful to treat them separately.

My process has evolved over the years based on my exposure to other thinkers and on the lessons learned over multiple iterations of the cycle. In today’s vernacular, I would call it a process of design thinking. It starts with someone declaring that a problem exists. What follows is a classic problem-solving process;

  • searching out the facts to tease out a picture of “ground truth,”
  • immersion in the stew of ground truth and the broader context, adding new morsels and tidbits until there is a super-saturated solution,
  • flashing on a crystallizing phrase or formulation that causes insight to precipitate out of the super-saturated solution
  • elaborating the implications of the crystallizing formulation for what the next world needs to look like
  • bringing the next world into being in thought and deed

The process works in multiple environments. It has to be coupled with domain expertise and local environmental insight to be practical

There are two elements of this process that have proven to be important for me, although I haven’t seen them talked about much. This could be a hint that there’s something to be developed further, or it may simply reflect my idiosyncratic perspective. The first has to do with the step I’ve described as “immersion.” I think of it as a deliberate practice of staying in the question rather than pushing on quickly to old answers we find comfortable.

The danger of staying in the question, of course, is that you never move on; something that others warn against as “analysis paralysis.” This leads to that second element. My signal to move on in the process is when I hit on a short phrase that encapsulates my take.

For example, I was working with the director of a university research lab who was wrestling with the problem of how to better manage a group of professors, post-docs, and research analysts that had grown rapidly. After an initial round of interviews, I was reviewing my raw interview notes to see what I might have learned. The phrase that popped into my head was that the Lab Director was asking how could we help “smart people do smarter work.” Nothing exotic and certainly nothing Pulitzer Prize worthy, yet it was a signal to me that I had found a thread I could now work with.

The Persistent Myth of Five Year Plans

five year plan posterI marvel that the myth of the 5-year plan persists. Without the invention of the spreadsheet it might have already passed away. You would think that the “success” of 5-year plans in the former Soviet Union would have been a better clue. Regardless, managers continue to stress over their ability to predict the future and manage to those predictions.

There are only two ways to make plans that can survive a 5-year test. One is to operate in a stable/stagnant enough environment that the future can be seen in today’s reality. The second is to take so few risks that you convert your local environment into something that can pass for stable.

Smart organizations and smart managers approach planning differently. When we started Diamond in 1994 we talked about our 23 and 1/2 year plan. This “plan” was a simple picture that showed 3 1/2 years of high growth followed by a 20-year line of sustained, steady, growth. The point of that simple picture was to set a shared direction. The first task was to establish an organization and a culture. The second was to manage that organization for the long term.

There was no way and no point to make or believe predictions about what we would be doing in 5 years. But our aspirations gave us insights into the organizational capabilities we needed to build. Without the sense of direction, we would have no way to make choices about what to work on and what to ignore.

We were indeed trying to build a business but there were also insights to take over into building a body of work perspective. Chief among them was to focus on the skills and capabilities we needed to develop. Planning was about understanding the skills we had and the skills we hoped to develop next. If you have choices about what projects to take on, then one filter is what new paths does each project open up.