I developed this presentation after being asked to speak with a group of young women engineers about my personal story and the most important things I had learned over the years.
As I outlined my story I realized that many of the terms and concepts I needed to do a barely reasonable job were technical terms of art drawn from a wide array of fields that were developing rapidly during the first decade of the 21st century. As a result this presentation is structured as a series of topics – most of them fairly geeky as I tried to achieve a balance between superficial treatments and eye-glazing technical details, followed by my story told in the words of these fields, and concluding with my thoughts regarding success. Despite ruthlessly cutting content, I fear that many will find my sketchy treatments of some of these topics to still be excessively detailed. So be it – the subjects fascinate me.
Today, the story in this presentation represents my perspective about what makes individuals and organizations successful, specifically within a corporate environment, though the principles are readily extended to the wider, global network we all now live and work within. In a nutshell, I argue that success is a side effect of intentional practice and that such practice at the individual and organizational levels free us up to accomplish more with less effort. We gain efficiencies by removing constraints from the system and leverage those by developing expertise.
Through a somewhat winding road, I will eventually arrive at the questions:
- What is success?
- How do I get it?
- How do I know if I have it?
I will discuss these questions in terms of these guiding principles:
- Work hard and get better
- Collaborate and add more value
- Cultivate judgment
Thank you for joining me in exploring them.
The first topic I want to discuss is the notion of metaphor.
Metaphor is absolutely central both to how we understand the world and how we communicate with each other about it. Where we don’t have shared experience, or when we want to have an abstracted, generalized conversation about our experience, we communicate using metaphor. For instance, a metaphor for what it’s like to have children is what it is like to love a pet. [This is where all the parents in the audience smile indulgently because they know both how poor a metaphor that is, as well as how hard it is to explain it’s shortcomings] As with all metaphors there are places where it provides new insight as well as places where it breaks down.
Lakoff & Johnson’s work is 3 decades old, but their insights are holding true in the face of recent developments in brain science. Gerald Edelman much more recently went so far as to say that thought, itself, begins through a process akin to metaphor.To demonstrate how metaphor is used in common language, L&J deconstruct the metaphor “Argument is War”. We will naturally say things like:
- Your claims are indefensible
- He attacked every weak point in my argument
- His criticisms were right on target
- I demolished his argument
- I’ve never won an argument with him
- If you use that strategy, he’ll wipe you out
Note that we don’t just talk about arguments in terms of war – we can actually win or lose arguments, we see the person we are arguing with as an opponent, we attack his positions and defend our own. Now imagine a culture where argument is viewed as a dance and the participants are seen as performers, and the goal is to perform in a balanced and aesthetically pleasing way. We would probably not view them as arguing at all – we would consider it something different. How we choose our metaphors very much defines our experience.
The value of metaphor is that now you can talk about the abstract concept. You candiscuss how to “cover those points, buttress your argument, get to the core, dig deeper, attack a position, etc.”
Metaphors are abstract, but they are based in our real physical and cultural experience. For example: happy is up and sad is down: probably because drooping posture typically goes along with sadness, erect posture with a positive emotional state. Another example: more is up probably because if you add more substance or physical objects to a container or pile, the level they enable communication.
For the purposes of today’s topic I’d like you to consider just how much our success depends on the metaphors we use to frame it. Can we think about success as a war or a dance? I used to think about success as a destination, or a prize. Next I thought of it as a journey. Now my metaphor is one of emergence – and how I conceptualize the 3 questions (what is success, how do I get it, & how do I know if I have it) and operationalize the 3 principles (work hard&get better, collaborate & add more value, & cultivate good judgment) has changed dramatically as a result of those metaphors.
Next let’s talk about emergence and its value as a metaphor. Emergence has become a fairly popular topic lately, but let me give some brief background.
Emergence is where complex behavior results from simple interactions
The behavior of ant colonies are so complex that people used to believe there was an “Ant Queen” or other organizing mind directing them. Yet all the behaviors derive from 2 things:
1) The nature of ant communication. When they bring food to the nest, ants leave trails of pheromones for other ants to follow. Closer to the nest those trails are stronger and easier to follow so the more direct routes to food will have the strongest trails. As more ants follow the direct paths, they lay down more pheromones that make the trails even stronger.
2) The simple rules of ant behavior: walk randomly until you find food, bring the food back to the nest, follow the strongest scent back to food, and repeat.
Those rudimentary instincts, combined (or layered), produce complex, problem-solving behaviors.
This example is simple enough for us to see emergence, but emergence doesn’t just apply to simple organizations. Recently we have all seen how the metaphor has been used to drive business and technology innovations in the web 2.0 arena with Google, Facebook, Slashdot, etc.
Let’s consider the other standard emergence example: flocking.
Imagine if you had to design flocking behavior as a software algorithm. In a synchronous centrally controlled approach, you would need to track the state of each bird and adjust its behavior based on changes in state of all of the other birds. This requires a lot of time and resources and scales factorially as you add birds. Nature’s solution, (which has also been implemented in elegant software solutions that model flocking) is to treat each bird as an agent that follows 3 simple rules:
- avoid crowding neighbors
- steer towards average heading of neighbors
- steer towards average position of neighbors
In an elegantly designed system, it seems, control can be distributed which makes it both far more adaptive and efficient. I like that metaphor, and when it comes to setting teams up for success I generally think of direct central control as a compensation mechanism for bad design. Whenever I find myself trying to achieve outcomes through direct control, I see that as a big red flag to think pretty carefully about what is preventing me from relying on the team’s “simple rules” – whatever those may be.
The most important and counterintuitive element of the emergence metaphor is that adaptive collective behavior is a side effect of simple interactions, not an outcome achieved by massive direct control.
In modern neuroscience the metaphor of mind as a controlling executive has been replaced with the metaphor of the mind as an emergent system where consciousness or self is a side effect of simple rules and feedback.
Until very recently, western philosophers talked about the self as “the ghost in the machine”, as though “you” sit behind your eyes watching the world on a giant screen that is being fed images from your optic nerves.
Over the past decade or two, neuroscientists have been modeling the workings of the brain by correlating physical locations of brain damage with changes in brain functioning. Scientists have also begun to gain a ton of new information by mapping the functioning of the brain in ways that were impossible prior to the advent of the CAT scan & MRI.
My favorite biologist is Gerald Edelman who won the nobel prize in 1972 for his work in immunology. He proved that the body is capable of creating complex adaptive systems as a result of local events with feedback – that emergent systems exist in our bodies. Next he applied his approach to brain science. He developed a theory called “Neural Darwinism” that describes in detail why and how consciousness can be explained as an emergent characteristic of the brain.
In essence, Edelman proposes that the development of the brain relies first on genetics to create an organizing structure, but since there aren’t nearly enough genes to account for the complexity of our minds, the rest of the complexity comes from our interactions with the environment. Through experience, statistically massive numbers of neural connections are generated in the brain as a result of inputs from the body, the environment and the processes of the brain itself. Just as ant trails are reinforced with additional layers of pheromones, different experiences reinforce certain neuronal connections which leads to unique configurations in all of us. The need to correlate the processing of experience across the many parts of the brain causes the brain to “talk to itself”, which sets up multiple interacting feedback loops on many levels.
Edelman works his way up the systems in the brain and their interactions with each other, the body, and the environment, demonstrating how at each level the “simple rules” of the level below create more complex, emergent behavior. He concludes that: and I quote, “The evidence suggests that consciousness is entailed by reentrant activity among cortical areas and the thalamus and by the cortex interacting with itself and with subcortical structures.” Essentially, consciousness is the process of the brain talking to itself.
I love that word “entails”. I love the idea that complex behaviors are not something separate from the elements that generate it or the rules they function by – they are comprised of those elements as a standing wave is comprised of both the matter and the vibration that compose it. As I use the word entails throughout this talk, please consider it with all the richness it implies.
Now, if Edelman’s thesis is that consciousness is entailed by the brain, Antonio Damasio’s is that rationality is entailed by emotion.
Antonio Damasio, professor of Neuroscience, Neurology, and Psychology at USC, debunks the concept of a “seat of consciousness” – and demonstrates that thinking is a function that is distributed across the brain.
In your mind, do the following subtraction problem: 342 – 173 (169)
- did you visualize it? (you were probably looking up & to the right while working on the problem, indicating use of the visual cortex)
- who did the visualizing?
Damasio claims that thoughts are images that are stored in the somatosensory cortices (visual, auditory, etc.) and can be manipulated. He explores how nature re-uses brain systems from earlier in our evolution when developing new ones. The mammal brain relies on and re-uses functions of the lizard brain. The human brain reuses and repurposes functions of the mammal brain
The metaphor of the lizard brain, mammal brain, and human brain would make real neruoscientists cringe, but for my purposes of metaphor, it will serve. With extreme oversimplification, I think of them as the systems that implement instinct, intuition, and intellect respectively.
The lizard brain comprises the oldest systems in the brain including the hypothalamus and brain stem and controls things like fight or flight and other instincts. Even very simple animals use the blood stream and nervous system for the body and brain to act on each other via electrical signals, neurotransmitters, hormones, etc. As we continued to evolve, that dynamic process of interaction and feedback among the body, brain, and environment became the platform for higher order functioning. A healthy system is characterized by something called “homeostasis” meaning that these feedback loops are in balance. You can think of the response of even the simplest organism in moving toward food or light or away from a predator as a change away from homeostasis that signals “danger” or “opportunity”, where the organism then enacts a behavior that restores homeostasis. At this level homeostasis is instinctual, reflexive, or autonomic.
The mammal brain came later and includes the limbic system and controls such things as emotions and intricate social organization. With the evolution of the mammal brain came intuition – the development of primary emotions that drive homeostasis not just from hardwired responses but stimulus that is learned from experience. Say a large moving shape looms over a baby animal. Stimuli (size, movement, etc.) are processed and detected by a component of the brain’s limbic system (say the amygdala) which triggers the increased heart rate and other things associated with the state of fear. Next, the animal “feels” fear and its neuronal network connects that feeling to the trigger. Experience creates a vast database of such connections, entailed by the neuronal network of the brain. Now the animal can collect information about scary snakes as different from scary bears and begin to tune its responses depending on what kind of threat it faces. This gives it a leg up over creatures who are limited to instinct and reflex – it can learn. At this level homeostasis is mediated by emotions – the animal feels bad and enacts certain behaviors until it feels better. Those behaviors are based in the learned responses that connect reflexes to events.
The human brain is the most recent and includes the neocortex. It has to function in far more varied and largely unpredictable physical and social environments. It works through a complex interaction of nature/nurture that gets expressed in different ways by different cultures. The human brain employs secondary emotions – it talks to itself and can cause the physical state associated with an emotion just by thinking – as when we imagine the death of a loved one. On a conscious level, our thoughts show up as images that are distributed among the higher level cortices of the brain. At a nonconscious level, networks in the prefrontal cortex automatically respond to those thoughts by matching the patterns of our thoughts to an emotional response based on past experience. Then the mammal brain automatically sends the neural and chemical signals to our bodies to create an emotional state such as sadness. At this level, homeostasis is mediated by feelings as well as emotions and reflexes
Although we think about emotion and reason as very separate the reality is that reason repurposes the emotional systems. In rational thought, the neocortex engages right along with the older brain core and rationality results from how they work together. This happens through the mechanism of feelings.
According to Damasio’s “somatic marker” theory, the pattern-matching machine in our brain that correlates feelings with experience is reused and repurposed for rational thought. Logic alone is inadequate for making decisions because of limitations of time and mental resources. In order to make a decision about something as simple as when to schedule a meeting, a hyper-rational approach would require that you consider every possible time and every possible conflict – what if I want to go to the store at 2:00 instead of 3:00 – and the logic tree quickly becomes too complex and cumbersome to handle. The emotional pattern-matching machine prunes the decision tree in advance to bring the number of options down to something manageable. It does this by giving you a “gut feeling” as each possible path pops into your mind. Damasio calls that feeling a “somatic state” and because it marks an image, or thought, he calls it a marker. The somatic marker grabs our attention and focuses it the outcomes that the pattern-matching machine has identified as negative.
[The essence of feeling an emotion is the experience of such changes in juxtaposition to the mental images that initiated the cycle.]
[Note that social conventions and ethical rules can be linked to simpler goals, drives, and instincts.]
Like Damasio, Edelman talks about about the two modes of thought being pattern recognition and logic.
Pattern recognition is the primary mode of thought because of the range that it provides in dealing with new situations – logic is very limited when dealing with wide-ranging possibility. By analogy, if you need to represent values from 0-1000 with 3 bits, you get a much wider range and less precision than if you are representing the numbers 0-7. Another way to think about pattern recognition is as massively parallel processing and logic as linear and slow.
As a result,
-The pattern recognition machine has range; it is almost always right, it’s just not always clear what it is right about
-Logic is very precise, but it is often wrong – but whatever it is wrong about is quite specific.
Good judgment means balancing your thinking and gut reactions. Aside from being imprecise, gut feelings are very dependent on your experience base. If your pattern-matching machine has been run against only a limited set of circumstances or has been trained on bad data, it will not be very reliable. Logic, on the other hand, is pure garbage in garbage out. Unless your reasoning uses good initial assumptions and conditions you will reach absurd conclusions – the kind where you should be able to count on your gut to say “that can’t possibly be right!”
So consciously balance reason and pattern recognition. When we feel we know the answer in our gut, we need to run the numbers to see if cool reason agrees. If we reason our way to an outcome, we need to do a gut check as well.
This is a lot harder than it sounds, because normally, the logic machine will rationalize the conclusions of the pattern-matching machine. Robert Heinlein calls man the “rationalizing animal” and to quote Edelman, “In Neural Darwinism, every perception is to some degree an act of creation and every memory is to some degree an act of imagination.”
It is amazing how deeply fallible our brains are designed to be! An extreme example are stroke patients who are paralyzed, otherwise completely rational, but can nonetheless be utterly convinced that their limbs move and are perfectly healthy,. When observes try to call them on it, they will create stories to justify the apparent contradictions. All of us with human brains fall victim to this, to one degree or another, on a daily basis.
Here’s how I explain it to my kids, with metaphor:
- The lizard brain keeps you alive: it breathes for you, makes your heart beat, and makes you jump out of the way when you hear a loud noise or when there is danger
- Your mammal brain has feelings. Sometimes they are good and sometimes they are bad. Sometimes they come because of something that happened, sometimes they come for no reason, and sometimes your brain even starts having feelings about your feelings. Unfortunately your mammal brain likes to use feelings to trick you.
- Your human brain uses logic, but it almost always believes the mammal brain. So if you are having a really bad feeling – it will make up a really bad story to go with that feeling. Then that story can make the mammal brain feel even worse.
Later, when they are not in the grip of emotion, I point out “do you remember how bad you felt about x?” “and how much better you feel about it now?” “isn’t it interesting how your mind tricked you about that?”
I try to help them see both thoughts and feelings as something they have, not something they are. That psychological distance seems to be helpful to them in developing judgment and for cultivating optimism by choosing narratives that support their happiness.
More mental math – In your mind muptiply 2,356×7,653
That one’s pretty hard! Most of us will get lost keeping track of the details in that computation. This is because our brains actually have severely limited cognitive resources. Most people can remember 7 things plus or minus 2. I think of this as 7 boxes I can put information in.
Most real-world problems are too complex to fit in 7 boxes, so we simplify our models until we get to something we can solve. Novices have to figure out every detail for the first time, so they have to simplify problems radically. Experts, on the other hand, have a vast base of experience that lets them shift the burden from problem-solving to pattern recognition – they can fit more complexity into each of the 7 boxes, so they can solve problems more realistically.
Pattern-based learning starts with skill building. Let’s take the example of learning to drive. The beginning driver has to solve dozens of problems, many of them at the same time such as downshifting and turning a corner. With practice, things that used to look like separate pieces such as (such as hold down the clutch, grasp the gear lever, move the gear lever up and to the right) become chunked into a single procedure (shift to third gear) – now a lot more information can be fit into one of the 7 boxes. They become habit.
Habit is great for winning back mental resources, but there is also a cost – we lose conscious access to all the details that get chunked together. Habits are hard to change and they include implicit assumptions that whatever circumstances that created the “chunking” are static and that they apply in new situations.
Expertise-building is different from other kinds of learning in how you use the cognitive resources that you free up. Most drivers free up resources as soon as they get good enough and they use them for talking on the phone, listening to the radio, texting, or other non-driving activity. But suppose you wanted to be a race-car driver. Then you would be constantly putting your mental resources into improving your driving skill. There is no “good enough” because the bar is always being raised by the competition.
Bereiter and Scardamalia talk about 3 ways to reinvest mental resources:
- Learning. Here they are talking about performing artists rehearsing or athletes practicing, or software engineers reading articles and blogs.
- Seeking out more difficult problems: move to a stiffer level of competition, climb a steeper mountain, or build a more complicated bird house
- Tackling more complex versions of problems– this is the most interesting and most central to the process of expertise. Where we have to work with simplified problems when we are novices, we can, with experience, start to “chunk” pieces of the problem together so we can incorporate more of the constraints and solve the problem more realistically.
The reinvestment of mental resources is brutally hard work, but the effect is cumulative, like compound interest. Malcolm Gladwell talks about what makes the very best better than the rest of us. His thesis is that once you pass a threshold for talent (such as getting into a top music school), the only differentiator is hard work. 10,000 hours of intentional practice is what it takes to become an expert. Not just practice, but intentional practice getting better at the mechanics of your specific area such as practicing scales for a musician.
I think of expertise as an emergent side effect of intentional learning. By focusing on practice/rehearsal and better ways to solve recurring problems, expertise emerges over time.
You could imagine trying to acquire expertise by going at it directly – such as by memorizing the patterns that experts use to solve problems, but that would be trying to use the logic machine to do the job of the pattern-matching machine. It’s a hyper-rational approach that makes sense on paper, but is doomed in practice because of the logic machine is inadequate for dealing with the sheer volume of information.
Next I want to turn to an example of the metaphor of emergence in organizations. Alan Bain talks about emergence as an organizing metaphor for building a school where practices that improve teaching and learning are self-sustaining and self-replicating.
Bain’s book is about school reform and how top-down implementations consistently fail to have an impact on student outcomes as well as being inherently unsustainable. There are incredibly successful teachers, but reforms that attempt to scale their effect to the rest of the school almost always fail. The problem is that the approaches are “hyper-rational”. They intellectually analyze what successful teachers do, create a theory of teaching and learning, codify it in “best practices” then implement it in schools. This seems logical in theory, but in practice it doesn’t work. The idea that a unique school culture can be changed by processes that are imposed from the top down just fails – in part because it requires the “top” to manage all the little details at every level which is unrealistic – there aren’t enough resources for such an inefficient approach; and in part because it is too rigid to deal with change and evolve as the organization learns.
Bain solves this by designing a school system where reforms are not top-down, they are bottom up. The desired outcomes are side effects of the day-to-day work. Bain goes through a number of design criteria including schema, simple rules, embedded design, distributed control, and emergent feedback, but the one I want to focus on is similarity at scale.
This concept leverages chaos theory and fractals. Fractals are geometric shapes, such as the one in this picture, where each part, at least in some way, is a sort of reduced-sized copy of the whole.
In an emergent, self-organizing school, like a fractal, the work of an individual teacher scales to the work of a team which scales to the work of a school.
Teachers use their experience and judgment to decide whether and how to try new things in their classroom. They investigate, then implement, then reflect, then iterate. Because the same process also exists at the team level, the innovations scale to multiple classrooms when the team investigates, then implements, then reflects, then iterates together. Then, because those same systems exist at the school-level they easily scale again.
-What you have, in this case, is not just a community of individual practitioners, but a community of practice. A community that focuses both (and this is important) on the practice of their profession and on practices for learning as professionals. At each level, like a fractal, the systems are alike and entailed by the systems at the level below. At each level, from the learning individual to the learning organization, there is the constant freeing up of resources and re-purposing them to a more complex set of problems. In the end, they create a self-sustaining community of experts within a self-sustaining expert community. Expertise scales from the level of the classroom to the level of the school.
[Schema – a self-organizing school has a schema, a commonly held set of professional understandings, beliefs, and actions about teaching and learning
Simple rules – self-organizing schools possess simple rules that drive the form and function of the school
Embedded design – self-organizing schools embed their beliefs, values, and actions about teaching and learning in every part of the organization’s design
Similarity at scale – self-organizing schools embed their beliefs, values and actions about teaching and learning at every level of the organization
Distributed control – Self-organizing schools employ networks and collaboration to enable the ready flow of feedback to all levels in the organization
Emergent feedback – Self-organizing schools possess feedback systems that are used to decide what they need to do next]
Distributed control and emergence also show up as themes among scientists who are studying the phenomenon of happiness.
Daniel Gilbert begins his book by making fun of Ram Dass and his 1970’s message “Be Here Now” – that we can escape the suffering of endless worrying by focusing on the current moment, then asks the question, if constantly worrying about the future is so painful why do we do it?
He says there is a right answer, but the answer that most of us believe is dead wrong.
WRONG ANSWER: We think about the future so we can create good outcomes because it matters how things turn out – we predict so we can control; But the reality is we can’t get to happiness through control. Our brains are brutally fallible and what we expect to experience when we imagine the future, good or bad, is rarely what we actually do experience in that situation. In practice, it turns out that the best way to predict how we are going to feel in a given situation is not to imagine ourselves in it, but to look at other people who already are.
RIGHT ANSWER: We think about the future in order to reduce our suffering by anticipating the pain. If we brace ourselves, it hurts less. By thinking about the future we are able to affect the future, and having that impact (regardless of whether it improved or worsened the outcome) in and of itself feels good.
Matthieu Ricaud is a molecular biologist who has spent decades as a Buddhist monk: In his book he talks about happiness as the goal of goals – the only goal that is pursued for itself, not as a means to something else. But rather than thinking of happiness as something that is granted and taken away by fortune and fate, Ricaud suggests that happiness is a skill – something we do. Something we practice either through analysis or contemplation
Analysis: think through systematically and candidly the causes of our own suffering and the suffering of others (intellectual , logic-based, approach)
Contemplation: rise above the whirlpool of our thoughts for a moment and looking calmly within to find the embodiment of our deepest aspirations (intuitive, pattern-training approach)
With either approach, according to Ricaud, happiness is entailed by our daily practice, not something separate from it. There are “simple rules” of practice from which happiness emerges.
I want to take just a moment to mention a recent article on the role of stress and brain plasticity. Experiments that subjected rats to chronic stress changed their ability to adapt to new situations and caused them to fall back on familiar routines and rote responses, like compulsively pressing a bar for food pellets they had no intention of eating.
To quote, “ the rats’ behavioral perturbations were reflected by a pair of complementary changes in their underlying neural circuitry. On the one hand, regions of the brain associated with executive decision-making and goal-directed behaviors had shriveled, while, conversely, brain sectors linked to habit formation had bloomed”
It’s as though stress suppresses the functions of the brain that support the kinds of higher order adaptation that are characteristic of generative, emergent behaviors.
I’ve spent a lot of time trying to ground the metaphor of emergence in different ways. Next I’m going to talk a little about my own experiences and how my metaphors for success evolved over time.
In my early career as a beginning engineer I wanted to be successful. I thought that meant => do great work, get appreciated, get promoted, be happy.
There were two problems with this approach. One: it doesn’t work that way, and two: even if it did, I was never destined to be a brilliant engineer. I didn’t love engineering. I couldn’t understand the satisfaction that other engineers got out of reading and discussing the latest articles in dr. dobbs and the IEEE. But I had perseverance and industry going for me. I worked hard enough to compensate for not having the intuition that the brilliant people around me did. I trained my pattern-recognition to be able to simulate their judgment of what was good or bad, then I solved problems multiple times to iterate towards solutions that I imagined they would find acceptable. Acceptable – but never brilliant. It was as though there was some organizing framework for thinking about engineering that they all shared but which was, essentially, invisible to me.
I compensated for my lack of engineering intuition with hard work. But the danger with compensation mechanisms is not when they fail – it’s when they succeed. And mine worked well enough that I was convinced I could always succeed by working harder. I lived firmly in a metaphor of success as some sort of prize that I could be awarded. Eventually the stress of trying to keep up with that approach caused me to become less creative and less productive. Eventually I realized that I had to give up the image of myself as someone who would some day be a successful technical powerhouse. I let go of my ambition to become a Principal Engineer and settled for a career in management. I chose my passion over prestige.
An amazing thing had happened, though, during the years I tried to be an engineer. I had trained, consciously, on the elements of engineering, understanding other people’s design patterns of thinking, and the human elements and glue that took those insights and translated them into product implementations. I had developed strong intuitions about whether projects and teams were working successfully and when there were red flags. I think this is because lacking the expertise of my colleagues, I was always using brute force to analyze the underlying details that they had chunked together by using intuition – this ended up giving me a fairly unique perspective. The crazy thing was, when I tried to talk to people about that, it was as though the organizing frameworks that I was using were invisible to many of them.
Over the years I had the chance to test my insights about setting individuals and teams up for success on a lot of different projects and I eventually ended up leading teams on the scale of hundreds of engineers. I also found a network of other engineering managers who were just as passionate and geeky about management as our colleagues were about engineering. I came to realize that success actually meant something more like => do what I’m good at, get appreciated for some of it (the parts that weren’t invisible), get promoted, be happy.
I had managed to trade in my metaphor of success as a prize, or something you get, for one of success being something you are: the accumulation of all the successes you have created over time.
But there was still a problem. I had successful teams by any external measure, but the way I managed them was by making sure I understood what was happening at all levels of the project, and staying on top of what was happening in the “bigger picture” of all the systems we interfaced to, and then setting goals and making decisions. In other words, I had created the classic command& control bottleneck, so there were never enough hours in a day. Of course, that approach also became unsustainable. I was doing what I loved, but not in a way that was good for either my own development or that of my teams and again, in time, I figured out that something had to change.
I had some constraints – one was that working harder had no chance of success- after years of 80-hour weeks there was no chance that there was spare capacity for any sort of brute-force method. I needed to change the nature of how I was working, not the volume. One of the things I experimented with was distributed control – letting more decisions and progress be made through the wisdom of the team. Paradoxically I found that less control created efficiencies at the team level because I had removed constraints from the system, allowing it to adapt and function more effectively
My real defining moment came when I turned down the opportunity to do something I had dreamed about for years – lead a remote office in the pacific northwest. I turned it down because I had an image in my head of all the things I still needed to learn and accomplish to be successful…because if I were successful and accomplished then I could do what would make me happy – such as, well, leading my own office somewhere in the pacific northwest while experimenting and learning and…hey! Wasn’t that what I had just been offered? So I called them back and said “I changed my mind – I’ll take it.”
That was the real epiphany for me. Finally, I got that success meant => do what I loved. Be happy. Period. Shortly thereafter I got promoted and lived happily ever after.
But that’s not how my story ends – it’s more how it begins.
I changed my metaphor of success again – this time from something you are to something you do. Success is something you practice. The things I used to see as success are side effects of that practice – it’s that simple. And like all simple things, also very difficult – in practice, as it were.
It was definitely a watershed moment for me – in a moment, it seemed, my pattern-matching machine switched my somatic markers to bias against success as a goal and in favor of success as an indirect outcome. In other words, I essentially lost my ambition. Success was no longer a noun, (something you have) or an adjective (something you are) but a verb (something you do). In my mind, success was a practice, an emergent process, and a standing wave entailed by my day-to-day work. And that pretty much changed the way I looked at everything.
My leadership style changed dramatically as I began experimenting recklessly with teams both in Portland and in San Diego. We consciously and intentionally worked on models for distributing control – my management teams ended up with the shared value that if you are spending too much time on management you are doing it wrong. We worked on frameworks for similarity at scale – for instance we had a simple rule of being easy to work with that applied to individuals, teams, and higher groupings…wherever there were interfaces to others. We worked in teams and as individuals regarding how to cultivate good judgment and even incorporated it into performance discussions. We looked for thought diversity based on the observation that some people were optimized for logic and others for pattern-matching to balance our judgment at the team level. It started to become impossible for me to separate out an organization from its people – it is entailed by its members and the simple rules that organize it. I can no longer disentangle individual contributions from collective accomplishment – in part because the sum is always so much greater than the parts.
I now find that the health and judgment of an organization is entailed by the health and judgment of its members in a way that is startlingly analogous to homeostasis.
These effects haven’t been limited to work – they are pervasive in my life. I think carefully about the “simple rules” for my family, such as “be kind” and “be helpful” and “cultivate judgment” that distribute control among all family members, even the youngest. My experience is that by giving away control, I have in returned received a sort of family harmony and resilience that adapts well to external events. I don’t think I would have that if I were trying to control both the events and the family’s responses in the way I would have if I had had kids in one of my earlier life stages.
Emergence is the organizing metaphor for my friendships, my communities such as schools and civic organizations, my hobbies, and almost everything I do.
what is success?
SO let’s go back to the nature of success. It turns out that how we conceptualize it, and more importantly, how we operationalize it, depends in very large part on the metaphors we use to frame it.
If we see success as a prize – be it money, respect, appreciation, improved opportunities or whatever, we are likely to be misled by the metaphor. We may be tempted to “keep our eye on the prize” and “go for the gold”. We might think that “winning isn’t everything – it’s the only thing.” We are very likely to prematurely narrow down the ways that we could be successful to only one or two options, we are likely to lose sight of win-win scenarios, and we are almost certain to miss out on any number of opportunities that don’t fit our preconceived ideas.
Worse – we are likely to see ourselves as not successful – because as soon as we achieve a goal, there will be another goal and another after that and we can’t be successful people until we have achieved all our goals.
If we see success as a journey, or a lifetime accumulation of moments, we have the advantage of being able to see every step as a contributor to our success, but there is still baggage associated with the metaphor. Most journeys have destinations and when we travel we often wish we could skip over the tedium of airports and uncomfortable seats and skip straight to the end point.
The reason I like emergence as a metaphor is that it keeps my focus squarely on the simple rules. I think success is a complex system, and in complex systems when you try to control a single variable you end up with unintended consequences and unproductive results. Going “straight for the prize” is unlikely to get you what you really want. This is one of the most interesting results from the folks engaging with the “Science of Happiness”. Once you get past a basic threshold, almost nothing you believe about what will make you happy is true. But when you tune a complex system to function beautifully, the side effects can be amazing – like fractals, and web 2.0 and self-organizing schools and even, I think, happiness.
So I find it useful to think of success as a side effect. Which leads us to the question – what are the simple rules that define the system?
how do i get it?
How do I create the simple rules and interactions that create success as a side effect?
First, realize that you have FAR more control over your success than your manager does. In our industry, most managers are in that role because they are subject matter experts in their field and they may or may not have expertise in developing people – especially if their passions and yours don’t align. If you find you have a manager with a hyper-rational approach to your development, that makes it your job to find the experts who can help you. You have the choice of ceding your development to someone else or owning it yourself.
Work hard & get better – for it’s own sake
- Develop expertise in your chosen area (if this feels like a prison sentence, perhaps consider changing areas – trade off prestige for passion)
- Don’t just have 1 year of experience 20x…when you are asked to do a job where the same problems recur…solve them better!
- Targeted practice (10,000 hours), not just repetition – this work may not always be fun, but this is like paying your dues – to your profession and yourself – it is required in order to become great
- Apply your developing expertise to the day-to-day workReinvest your cognitive resources!!
In short, become a reflective practitioner, always focusing on how to improve all aspects of your performance. Then perform at your peak, for the sake of your craft. Let rewards and external recognition become side effects of your authentic practice.
Collaborate and add more value
Recognize emergent networks and find ways to contribute to them. Consciously develop your network as a community of practice. Think and talk about how to improve your collective product regularly. Try things, then reflect on the experience together, then find tune it and try again.
From a metacognitive standpoint, pay attention to and articulate the shared schema and “simple rules” – the act of ongoing articulation is more valuable than the product. Add more value – keep iterating until you have systems that are self-sustaining, where the sum is greater than the parts.
Cultivate good judgment
- Consciously balance pattern-matching vs. reasoning
- Recognize when somatic markers cause you to react to a new situation “as if” it were an old situation
- Recognize hyper-rational approaches and false intuitions
- Manage your stress – because cultivating good judgment is about overcoming the evolutionary pitfalls of habit and under stress the brain doesn’t have the capacity to do that
But how do you do that in practice?
Perhaps by analogy to Ricaud’s approach to happiness: either through analysis or contemplation. Perhaps more pragmatically, take a look at Goleman’s work on Social and Emotional intelligence. Emotional Intelligence work in the 90s looke a lot like cognitive therapy or analysis – in this decade it has started to look a lot more like contemplative practice.
how do I know if I have it?
If you consistently work hard and get better you will, eventually receive recognition, but receiving recognition does not necessarily mean you are successful
If you collaborate and add more value, you will, by all measures, be more effective though it will be harder to correlate specific accomplishments to specific individuals
If you exercise good judgment you will have more satisfaction and more impact, but it is hard to compare what happened to what would have happened had your judgment been less strong
This is a defining question, and there are probably as many answers as there are people in the room – maybe more. I don’t know any single answer, but I wonder if the concept of homeostasis is an interesting metaphor in exploring the question. I invite you to use it as a guiding inquiry in your own practice of success, and share with me what you learn as a community of practice.