Stealing practice time from performance

Stage view Bright lights“Standby Cue 103.”

“Go Cue 103.”

We had about two minutes left in the finale. Twenty five dancers filled the stage, the music director was in the pit with another twelve musicians, I was stage right talking to the lighting crew via a headset and the stage crew via hand signals. In about thirty seconds, I would give a “Warn Cue 104” followed by a Standby and a Go.

It was the final night of our ten-city tour and we were performing in a lovely theater at New Trier West High School in Winnetka, Illinois. There’s a story about the space I’ll save for another day. Steve, the only performer not yet on stage tapped me on the shoulder. I looked away from my cue book. Steve was in his costume dressed as the Statue of Liberty—another story for another time.

Ok. He’s about to make his entrance upstage center. I’m not sure why he’s interrupted me.

Until he turns around.

Steve is not actually wearing his costume. He’s taped it on so that it looks normal from the front. From behind he’s naked from head to toe.

I miss giving the warning for Cue 104, but do manage to get out the Standby and Go in time. I then warn the crew to keep their eyes on the next 90 seconds. We set up and execute the next half dozen lighting cues, the band continues to play, and Steve makes his entrance, which starts from upstage center and proceeds downstage to the edge of the orchestra pit. As Steve passes each row of dancers, that row misses a step and recovers.

The finale ends, the curtain falls, and cast and crew breaks into hysterics.

Juvenile? Certainly. Unprofessional? Not really.

One of the payoffs of rehearsal and constant practice is the capacity to go with the flow. And to know when you can tweak the flow without interfering with the audience’s experience. It was the final number in our final performance. The steps were muscle memory at this point. Letting me know at the last moment was more of a gift to the crew than a needed warning.

One thing that puzzles me about ordinary organizations is how they develop capacity to respond to the unexpected, to go with the flow successfully. The magic we see on stage or on the athletic field demands time dedicated to practice and rehearsal. It is the practice and rehearsal that creates the capacity to adapt. That time is built into the process.

Ordinary organizations don’t build this into their process. Learning and rehearsal time is limited to occasional training experiences or stolen moments of on-the-job training. The rare major systems rollout may get planned training and support time.

Conventional wisdom says that people in organizations resist change. What they resist, sensibly, is demands for polished performance without rehearsal. By ignoring the role of rehearsal and practice, organizations end up with lower levels of performance. Rehearsal happens but only by disguising some performance time as a mediocre form of rehearsal. Neither practice or performance is effective.

Taking the half-life of knowledge seriously

I’ve made the claim that the half-life of knowledge is shrinking in most domains. We often frame this from the perspective of the increasing volumes of data and information we are called on to assimilate, but there is something worth teasing out by thinking in terms of pace instead of volume.

One of the first places I encountered this notion of the accelerating decay of knowledge was in reference to its impact in engineering fields. James Plummer, Dean of Stanford’s Engineering School, observed that

“The half of life of engineering knowledge is three to five years. As dean, I used to tell students it doesn’t matter what we teach you because it will be obsolete when you graduate, so go out and have a good time.” The Engineers of the Future Will Not Resemble the Engineers of the Past

He’s right if you think of his teaching responsibility as installing an up-to-date and accurate body of knowledge. While he nods in the direction of life-long learning, he doesn’t say anything about how life-long learning should differ from the way it has been organized in formal educational settings. Our naive assumptions about how learning works are anchored in our experience in schools and classrooms; there’s stuff to be learned, an expert to teach it, and a timetable to follow. At the other extreme, there is on-the-job training with little or no structure or guidance.

We see some attention to the notion of learning how to learn. Most of that, however, focuses on how to do a better job within the structures of courses, classrooms, and schools we feel comfortable with. The proliferation of new channels for learning—Khan Academy, Udemy, MOOCs — stay within the broad outlines of that comfortable structure.

None of that addresses the question of how to approach learning when the knowledge landscape is in constant flux. What do you do if you need to pick up a new skill before someone writes the book or the course you need in this structure? How do you manage your learning when figuring out what you need to learn is the first order of business? Worse, everyone else is in the same predicament; new knowledge is accumulating and old knowledge becoming obsolete faster than the systems we know can adapt.

There is one example I can think of for managing learning under these conditions. That is the world of doctoral students in evolving disciplines.

The assumptions about knowledge and learning baked into work at that level match the environment much more effectively than the assumptions built into studies at earlier stages of learning and knowledge acquisition. That change in assumptions, in fact, is one of the traps that students fall into when they try to make the transition into doctoral level work. It isn’t that the work gets harder. The work doesn’t conform to the practices that worked for acquiring and demonstrating your mastery of a known body of knowledge.

First, you discover that the consensus on what constitutes the relevant body of knowledge is in flux and always will be. As a fledgling expert in the field a doctoral student is now expected to develop a point of view about where the knowledge edges are; eventually, you are expected to push beyond them. In stable fields, you have the luxury of limiting your search for answers to the authoritative texts. In the worlds we are discussing now, you are forced to seek out and make sense out of primary sources. Behaviors that once would have gotten you in trouble–questioning sources, arguing with your teachers, disputing conclusions–are now skills to be developed. You must learn to develop your own models and conclusions to make sense of new data as it appears.

This leads to the second key difference; there are more experts to know of and they disagree. The good ones expect you to disagree with them. Learning is less about finding a master whose feet you can sit at and more about finding colleagues to travel with. Learning takes on the flavor of conversations with challenging people.  Conversations imply that you should expect a balanced distribution of questions, answers, hypotheses, and evidence. Asking “will this be on the exam” becomes a     question you must answer for yourself.

Finally, you must develop map making skills. You are in new territory, out where the dragons lurk. You need to keep track of where the sinkholes and oases lie. This will keep you safe on your own journey and give you something to compare notes on as you encounter other travelers drawing maps of their journeys.

Learning to solve for pattern

Photo by rawpixel.com from Pexels“We need you back in the office now, Anthony’s team just got fired.”

I was at lunch. Back in the office, we were running a training simulation where a team of consultants was engaged in an assessment project for a hypothetical client. Over the course of a week, the consulting team interacted with the client by way of email, phone calls, and a handful of face-to-face meetings with client executives. The client executive roles were filled by retired executives who we paid to play the parts of CEO, CFO, and CIO.

Somehow, Anthony’s team of consultants had provoked the client CEO to fire the team on day 2 and demand that they vacate the premises. This was not a scenario we had built into the design of the simulation. How do you get fired from a  simulation? It was one of the more memorable “teachable moments” I had encountered.

We broke character and I facilitated a debrief of the “firing” that offered the junior members of the team a peek into the dynamics of managing client relationships they wouldn’t otherwise see and gave us a path back into the simulation for the remainder of the week.

It also started a deeper train of thought about how to get better at working in dynamic, high-stakes, settings. That proved important beyond the bounds of training as the environment continued to become more dynamic and the stakes continued to rise.

We designed this training simulation with help from a group at Northwestern University called the Institute for Learning Sciences. It was a group accustomed to building carefully scripted and automated training simulations for organizations such as Accenture and Verizon. They were  also accustomed to project budgets that looked more like our annual revenues than our budget.

Our resource limitations forced us to focus on design principles and forgo sophisticated technology features. We shifted the balance toward something that was more structural outline and less line by line script. We used a mix of technology and experienced support staff behind the scenes to shape and go with the flow as the simulation played out. Our goal was to create a learning environment that prepared people for the real consulting environments they would soon have. When our new consultants went out into the field for their first real assignments, we got the feedback that mattered. Our consultants were ready for what projects and clients threw at them.

The environment our consultants encountered was also changing. All organizations were dealing with accelerating innovation in strategy, technology, and organization. We had created our company on the belief that this acceleration would continue and would demand more responsive approaches to cope with and take advantage of that acceleration. The idea that the half-life of knowledge and expertise was shrinking was no longer an issue on the horizon. It was becoming a central feature of our day-to-day work.

Our training design was born of resource limitations. As much by luck as by design we had stumbled on deeper lessons for our work. We were learning how to navigate environments without a script and without rehearsal time. We were developing perspectives and practices oriented to an improv logic as the world demanded more responsiveness and adaptability.

I’ve come to believe that navigating this environment requires a shift in perspective and a set of operating practices and techniques that can be most easily described as improv adapted to organizational settings.

The shift in perspective moves from a world of connecting the dots to a world of “solving for pattern”. I borrowed the phrase from essayist Wendell Berry. It asks us to step back from the immediate details and view problems from a higher, systemic, vantage point.

Connecting the dots thinking is simplistic; find the picture hiding in the data and the details and select the appropriate script to respond. Google the term “bedbug letter” to see a classic, although possibly apocryphal, example.of connecting the dots.

Solving for pattern seeks to understand the driving forces that can explain the situation at hand as one instance of a class of similar situations. Instead of selecting a script that matches the immediate problem, solving for pattern looks for leverage points within the structure of forces where smaller nudges can trigger disproportionate responses.

As you make the shift to solving for pattern, you find yourself in a much more dynamic and collaborative environment than your likely comfortable with. If you’ve given up on the idea of a pre-existing script to work from, you must now learn how to create an actual conversation in the moment. This is the essence of improv practice in the world of theater.

Improv is something that can be learned and finding an improv class to participate in wouldn’t be a bad idea. For our purposes, it’s more useful to explore how we might adapt improv practices and mindsets to ordinary organizational settings.

Good improv practice is anchored in presence and focused attention. The fundamental rule is to agree to interact and agree to keep moving forward. In improv parlance, that agreement is referred to as “yes, and…” Adapting that mindset in an organizational setting calls for accepting that all players in a conversation have something to add.

What that also implies is a responsibility to bring as much as you can to add to the conversation and  commit to learning all that you can to better understand what everyone else in the conversation is bringing with them. This advice may seem contradictory; you must be prepared to both teach and learn at the same time. In a script world, you can simply accept the answers of specialists or insist that your specialized answers be accepted without modification.

In an improv world you must be prepared to “show your work.” Not to force your conclusions onto the conversation, but to enrich the conversation in search of a better collaborative answer. There are practices and techniques that can make the learning and the sharing easier to manage. But becoming comfortable in the mindset is essential.

Managing personal learning in a VUCA world

man hiking in forestSpinning a new consulting firm out of older, bigger, ones is a common story—no different from the founding of a new religious sect in a schism with the past. A charismatic leader and a few faithful followers declare a new revelation and start preaching from a new street corner.

When we started Diamond we all had experience in large professional service firms.  We were driven by things we didn’t like and wanted to fix and by opportunities we saw being ignored. We were less aware of the unique issues connected with being small and vulnerable.

Coming from big firms, we knew that training and knowledge management were important capabilities. As the only person who seemed marginally qualified, I was handed both problems and the hats of Chief Knowledge Officer and Chief Learning Officer. I had no staff and only the promise of a budget.

We lumped these two functions out of the reality of limited resources. In the organizations we had come from and knew, these functions were distinct. They demanded lots of resources and had grown from different origins and histories.

The decision rooted in our constraints generated insights that have become more relevant over the past twenty plus years. I want to start with the individual consultant—one of the prototypical knowledge workers that drive today’s organizations.

Alvin Toffler predicted that successful knowledge workers would be those who could “learn, unlearn, and relearn.” We live in the world he predicted. What we need to know as knowledge workers continues to grow at the same time that the half-life of our knowledge base continues to shrink.

The reality of this environment means that as a knowledge worker, you can’t count on organizations to be responsive enough to support your learning needs. They face the same problem you do and their problem is magnified by issues of scale.

Conventional strategies for learning break down. You can’t keep going back to school. You can’t afford the time and schools are as slow or slower to adapt their curricula to morphing demands as the organizations you inhabit.

Old avenues for learning in smaller, more up-to-date, chunks still exist and new avenues are appearing. If anything, the proliferation of options—YouTube, Udemy, EdX, Coursera, Khan Academy, workshops, seminars, webinars, ebooks—threatens overload more than relief.

What’s a reasonable path forward? I think it includes an explicit and dynamic personal learning plan coupled with a coherent set of supporting learning processes and practices. A learning plan should build on understanding how learning works, a view of your base of knowledge, and expectations of what skills and knowledge need developing.

Learning processes and practices provide the scaffolding and support structures that would otherwise be provided by the formal schooling environments that aren’t available. They will likely include:

  • reflective practice
  • cohort of co-learners
  • journals/journaling practice
  • reference management system
  • systematic note taking and management

What you might correctly infer from this is that I am actively engaged in updating and formalizing my own plans and practices. I’m curious who else finds this a journey they might like to join?

Dealing with the messy middle; accepting the wisdom of improv

A number of years back my thesis advisor retired and I made the trip to Boston to join in the celebration. One of the observations that has stuck with me was that the curtain was going up on Act 3 of my advisor’s career.

The reason it hit me was that I was being forced into a similar transition but not by choice. The metaphor of the curtain coming up on another act was a lot more empowering than the feeling of the curtain falling to end the performance. That helped me switch from licking my wounds to contemplating what to make of the next act.

Two things have become more clear as this act has unfolded. First, this act has called for me to step from the wings onto the stage. Not all the time, there is still work to be done from the wings, but I have to step into the light. Second, it turns out that there is no script for Act 3; Act 3 will be improv.

Now, the truth is that life is improv, but it can feel safe to pretend that there is a script. If you’ve been pretending there is a script, then making it up as you go feels like you must be cheating somehow.

There was a time when I ran the training function for Diamond Technology Partners, the consulting firm I co-founded with nine other partners and fifteen staff. When we had grown to several hundred professionals a few years later, one of our staff came to me with a proposal. Rik had been an actor before he became a consultant and convinced me that any consultant would be a better consultant with some basic improv training.

We ran the experiment with help from Second City in Chicago—a world class improv company. I joined in the initial sessions myself; much easier to evaluate an experiment from the inside than from the sidelines. It was a success but seen as a bit too threatening to the conventional wisdom by people with the power to say no. I was pushed out shortly after for other reasons and that is a story for another day.

But the improv perspective was a demarcation point in my thinking that only became clear in retrospect.

One of the mistakes that made me uncomfortable taking the stage was believing that you had to have your lines memorized to perform. I had learned one level of truth in the quest for expertise; experts were people with knowledge and answers. You wanted to find the person who wrote the book to get the best answers. If you wrote the book, then you’d better have the answers.

With two books written so far, you would think I would have also learned some deeper truths as well. But, having head and heart out of balance makes certain lessons slow to sink in. Thinking about the differences between scripted performance and improv was one of the elements in getting back to a more balanced place.

Among the fundamental principles of improv are the notions of accepting what is happening in front of you as the only meaningful starting point and of subordinating your personal agenda to letting the collaborative process play out.

What that translates into for my work is that the process is about exploring questions and digging into uncertainties not about starting with predetermined answers. That may seem trite and trivially obvious but honest inquiry is tremendously hard to do inside most organizations. The most powerful demonstration of true expertise is to be comfortable not knowing and trusting that the answers will appear after you’ve worked through the questions.

The essential part of that journey is working through the mess in the middle. There are powerful forces and temptations to rush through that stage. Developing and maintaining the strength to resist is a continuing demand.

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.

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.

Questions about questions

One of my professors, Warren McFarlan, made an observation about the choice of questions that has stuck with me. He argued that you could either ask questions that would get you published or you could ask questions that mattered.

He might have been a bit more diplomatic in his phrasing but that was the essence. Were you going to be driven by safety or by curiosity?

Most of education and society drives our questions to safety. We learn which questions lead to the answers that our teachers and managers are looking for. “Will this be on the test?” is the default question. The ways we suppress curiosity while pretending to encourage it are limitless.

I had a classmate in business school who liked to chat with our professors after class, which earned him a reputation as a brown noser. The notion that you might be genuinely curious about the subject was a foreign concept to most of our classmates. I got to know Phil as the year went on and discovered that he already had a Ph.D. in the History and Philosophy of Science. I may have been the only one in our section that he revealed this to; he believed, rightly I suspect, that this would only brand him further.

Curiosity is a dangerous value; it has killed more than cats. Suppose you also believe it is important regardless of the risks. How do you encourage, promote, and nourish real curiosity in environments that fear and suppress it?

How do you learn to ask questions that matter?

I’m making a claim here that I’ve avoided this problem and navigated the system with my curiosity intact. How did I manage that? More importantly, are there any lessons to learn?

School was a place where most things came pretty easy. But the culture still rewarded right answers and compliant behavior. As I listen to others tell tales of the pressures to achieve they faced from parents and teachers, they strike me as foreign. I was certainly praised when I did well, but I never felt pressured. My mom was always a believer. She was pleased with my results. But, she never talked about expectations. I imagine that with my six younger siblings to wrangle she was mostly relieved that I was operating on my own.

Looking back, my dad was pretty tricky. It was never “were you the best?” The question was “does this represent your best work?” If the answer was yes, the actual grade was immaterial; if the answer was no, then an A was no defense. That got me through high school and by the time I reached college I was comfortable chasing my interests instead of grades. I took courses based on my interests at the time, not based on my grade point average. As I often tell my students today, I managed to collect at least one of every possible grade.

Grades served as feedback, not measures of my value.

My work in the theater taught a second important lesson. Working on stage productions was always about scarce resources and hard deadlines. You can generally negotiate an extension on a class assignment; you can’t move opening night. On a show, the question is always “does this make what the audience sees better?” That leads to a second question, “if the audience can’t see it, why are you doing it?” There’s no good reason to paint the back side of a set.

The question is not about effort; it’s about value. We track effort because we can’t always wait to measure value; effort can be an appropriate early warning signal. Demanding maximum effort is a lazy manager’s way to avoid thinking about the value you are seeking to create.

The old adage is “if something is worth doing, it’s worth doing well.” I encountered an improved version on the bulletin board of a doctor friend:

If something is worth doing, it’s worth doing well enough for the purpose at hand. It is probably wrong, and certainly foolish, to do it any better.”

Throwing resources at problems is rarely an effective strategy despite the frequency with which it is employed. Acceptable as a strategy if you are resource rich, questionable if the problems and opportunities exceed the resources available. Getting the most leverage out of resources starts with learning how to ask better questions.

Review – Scrum: The Art of Doing Twice the Work in Half the Time

 Scrum: The Art of Doing Twice the Work in Half the Time. Jeff Sutherland and JJ Sutherland

There’s a rule of thumb in software development circles that the best programmers can be ten times as productive as average programmers. This is the underlying argument for why organizations seek to find and hire the best people. There is research to support this disparity in productivity. There is similar research on the relative productivity of teams. There, the range in productivity between the best and the rest is closer to two orders of magnitude; as much as a 1,000 times more productive.

Jeff Sutherland makes the case that the practices that collectively make up “Scrum” are one strategy for realizing those kinds of payoffs.

Sutherland is a former fighter pilot, a software developer, one of the original signatories of the Agile Manifesto, and the inventor of Scrum. This is his story of how Scrum came to be, what it is, and why it’s worthwhile. The particular value of the book is its focus on why Scrum is designed the way it is and why that matters.

Scrum’s origins and primary applications have been in the realm of software development. Sutherland builds an argument that Scrum’s principles and methods apply more broadly. Although he doesn’t make this argument directly, this wider applicability flows from evolutionary changes in the the organizational environment. Changes in the pace and complexity of organizational work simultaneously make conventional approaches less effective and Scrum more so.

Scrum is a collection of simple ideas; it’s a point of view about effective problem solving more than a formalized methodology. That’s important to keep in mind because like too many solid ideas, the essence can get lost in the broader rush to capitalize on those ideas. There appear to be an unlimited supply of training courses, consultants, and the usual paraphernalia of a trendy business idea; you’re better off spending time reading and thinking about what Sutherland has to say first. That may be all you need if you’re then willing to make the effort to put those ideas into practice.

Sutherland traces the roots of Scrum to the thinking underlying the Toyota Production System. He also draws interesting links to John Boyd’s work on strategy embodied in the OODA Loop and to the martial arts. Scrum is built on shortening the feedback between plans and action. It is a systematic way of feeling your way forward and adapting to the terrain as you travel over it.

Sutherland draws a sharp contrast with more traditional management techniques such as Waterfall project management approaches and their well-worn trappings such as Gantt charts and voluminous unread and unreadable requirements documents.

Understanding the managerial appeal and limitations of these trappings is key to grasping the contrasting benefits of Scrum. Waterfalls and Gantt charts appeal to managers because they promise certainty and control. They can’t deliver on that promise in today’s environment. In the software development world, they never could and in today’s general organizational environment they also come up short.

Understanding that appeal and why it is misplaced clarifies the strengths of Scrum. There was a time when managers came from the ranks of the managed. They had done the work they were now responsible for overseeing and were, therefore, qualified to provide the direction and feedback needed to pick a path and follow it. Management was primarily about execution and not about innovation.

The illusion in waterfall and other planning exercises is that what we are doing next is a repeat of what we have done before. If we have built 100 houses, we can be confident of what it will take to build the 101st. If we are building a new road or a new bridge, then what we have learned from the previous roads and bridges we’ve built can provide a fairly precise estimate for the next.

This breaks down, however, when we are building in new terrain or experimenting with new designs. The insights and experience of those who’ve built in the past don’t transfer cleanly to this more dynamic environment. The world of software has always been new territory and we are always experimenting. The terrain is always in flux even when the technology is temporarily stable. Now, it is those who are doing the work who are best positioned to plan and manage as we move into new territories and terrain.

Scrum comes into play when we are moving into territory where there are no roads and are no maps. If you are moving into new territory you can only plan as far ahead as you can see. There are no maps to follow. Sutherland puts it thus:

Scrum embraces uncertainty and creativity. It places a structure around the learning process, enabling teams to assess both what they’ve created and, just as important, how they created it. The Scrum framework harnesses how teams actually work and gives them the tools to self-organize and rapidly improve both speed and quality of work.

There’s a terminology and a set of techniques that make up Scrum. Sutherland covers the basics of such notions as scrum masters, product owners, backlog, sprints, retrospectives, communication saturation, continuous improvement, and stand up meetings. But he’s no fan of turning these into dogma.

Scrum runs the risk of being viewed as no more than the latest management fad. Sutherland is a true believer and has evidence to support his belief. There are lots of true believers but only a few are willing to bring substantive evidence to back up that belief. That earns Sutherland the right to offer his own closing argument:

What Scrum does is alter the very way you think about time. After engaging for a while in Sprints and Stand-ups, you stop seeing time as a linear arrow into the future but, rather, as something that is fundamentally cyclical. Each Sprint is an opportunity to do something totally new; each day, a chance to improve. Scrum encourages a holistic worldview. The person who commits to it will value each moment as a returning cycle of breath and life.

The heart of Scrum is rhythm. Rhythm is deeply important to human beings. Its beat is heard in the thrumming of our blood and rooted in some of the deepest recesses of our brains. We’re pattern seekers, driven to seek out rhythm in all aspects of our lives.

What Scrum does is create a different kind of pattern. It accepts that we’re habit-driven creatures, seekers of rhythm, somewhat predictable, but also somewhat magical and capable of greatness.

When I created Scrum, I thought, What if I can take human patterns and make them positive rather than negative? What if I can design a virtuous, self-reinforcing cycle that encourages the best parts of ourselves and diminishes the worst? In giving Scrum a daily and weekly rhythm, I guess what I was striving for was to offer people the chance to like the person they see in the mirror.

Learning from cases; getting smarter by design

One of my enduring memories from my first days in business school is a video interview of a second year student offering advice on surviving the case method. While I didn’t fully appreciate it at the time, it was totally appropriate that his advice was a case study in its own right.

He began with a story of the business challenge of “sexing chickens.” In the chicken business, it turns out that it is important to separate roosters and hens when both are no more than puffs of feathers. The clues are subtle and not reducible to a checklist. Novice chicken sexers can’t be taught to do their job but they can learn.

Prospective chicken sexers go through an apprenticeship. They sit down with a batch of chicks, pick one up, flip it over, inspect, and guess. Sitting next to our prospect is a veteran chicken sexer. The veteran’s job is to give the prospect feedback; either a “yes” for a correct guess or a smack in the head for a mistake. After a hundred or so guesses, the prospect’s error rate will drop close to zero. Neither the prospect or the veteran will be able to offer an explicit theory of what they are doing, yet they are effective.

Learning by the case method is a similar process of guessing and rapid, memorable, feedback. As an aside, recognize that this also describes the essence of machine learning. It is experiential learning at its purest.

The craft in designing case method learning lies in selecting and sequencing cases so that the lessons can be delivered more rapidly and reliably than the random accumulation of experience permits. The assumption here is that there is an order that can be exploited to guide action. There must be an underlying pattern that one can solve for.

If you subscribe to the value of the case method as a learning strategy, you are making a claim that there is a balance between theory and practice to be managed. It is a claim that the particulars matter; that experience or theory can only go so far in crafting a response. That you have a responsibility to design a response that acknowledges that every situation is a mix of old and new, predictable and unpredictable.

There’s a notion here that I am struggling with that has to do with the rate of change. I think that case-based learning potentially makes this issue more visible.

In a slow-changing world, experience matters greatly. Recognize how this situation maps to what we’ve seen and responded to before and right action is clear. As the rate of change increases, the value of experience changes. Prior experiences suggest actions and responses that can serve as the basis for designing a modified response that blends old and new.

Pushing the rate of change still higher means that effective response demands more design and less “here’s what we’ve done before.” What does that imply for learning effectively?

My hypothesis is that we need to make the experiential learning process visible, explicit, and deliberate. In a conventional case-based learning environment, there is a separation between those who are learning and those who are facilitating the learning—which is not the same thing as teaching. The goal is for those learning to build a robust, internal, theory of action. The facilitators have strong ideas about what that theory should look like and cases are sequenced to force the learners to develop an internal theory that matches the target theory.

What’s happening in higher-paced environments is that our learners and facilitators are becoming harder to distinguish. In a sense, we are back to a world of pure learning from experience. What changes is that as learners we now must be responsible for building our theories dynamically.

While this can still be described as a form of reflective practice, that reflection now must operate at several levels of abstraction. We can’t rely simply on organic processes to slowly and unpredictably get smarter over time. We need to get smarter on purpose and by design.