Eric Nehrlich, Unrepentant Generalist

Amazon link

I picked this up from the library, as yet another in the recent series of books I’ve been reading that reinforce my own biases. Overall, I liked it – I knew most of the patterns in cognition that the book describes, but it summarized them nicely with good anecdotes.

One standard model of decision-making is that we are rational beings. We examine all of our options, we think through the consequences of making a decision, we weigh the costs and benefits, and then we decide. Philosophers like Descartes think that this rational mind is what separates us from other species (“I think, therefore I am”).

Another model is that of the unconscious mind, as popularized in recent books like Sources of Power and Blink. The theory here is that our brains have evolved over millenia to have an enormous amount of processing power that is not consciously accessible, and sometimes we have to trust the “intuition” that the unconscious mind is giving us.

Lehrer’s book reviews the strengths and weaknesses of each of these cognition models to help people understand when it’s appropriate to use each model.

The rational conscious mind is limited in power – we’ve all heard the idea that we can only keep 7 information nuggets in our brain at a time. It’s a bandwidth-limited single processor (one estimate is that it processes at 20 bits/second). Its strengths are that it can logically process new situations, override our kneejerk impulses that may not be appropriate to the situation, and come up with responses that have not been tried before. Also, decisions made using the rational path are easy to explain, as they are based in logic. Its weaknesses are that it is slow and has limited capacity (check out his anecdote on self-control when trying to remember too many things), and therefore works best on well-defined problems with only a few dimensions to consider.

The unconscious brain is in many ways the opposite of the rational brain. It is a parallel processor with enormous capacity that can optimize decisions among many conflicting dimensions. It is also extremely fast – it works by training neural circuits to recognize previously seen situations and respond quickly without involving the conscious mind. When we are developing our 10,000 hours of expertise, we are building the necessary neural pathways in the unconscious brain (what Daniel Coyle says are myelin sheaths).

However, the unconscious brain does not deal well with novel situations, as it may seize on an already-trained, but inappropriate, response. It is also unreliable in situations where previously seen inputs have different outcomes because the training doesn’t work – Lehrer cites slot machines as an example of the unconscious brain desperately trying to find patterns when none exist. One final weakness is that the decisions made by the unconscious brain are difficult to explain, as they are expressed through emotions we feel and so we can’t analyze the decisions rationally.

Lehrer describes many situations when the two minds are used inappropriately. For instance, complex multivariable problems can not be answered by pure reason (Lehrer cites the example of a man who lost his emotional capacity after a brain tumor was cut out, and was completely unable to make normal life decisions). In fact, if we try to attack such problems with the rational brain, we make poorer choices because we seize on variables that are easy to explain rationally rather than considering all of the possible benefits (Lehrer cites an amusing study where undergrads had to choose a poster to take home; those that had to give a reason for choosing a poster ended up choosing posters they were less happy with compared to the ones that just chose a poster). Lehrer suggests that the best strategy when confronting a complex decision with many variables is to study it carefully to load all of the information into our unconscious brain, and then go do something else (take a walk, go for a driver) while the unconscious brain processes that information. This idea is reflected in the standard trope that the best ideas come in the shower.

However, the unconscious brain only works well in repeatable situations where it can try out different responses to the same set of inputs and encode what works into the neural pathways. In novel situations, we can’t trust our instincts and have to slow down and engage the conscious brain. Lehrer tells the story of a team fighting a forest fire when the wind shifted unexpectedly and came towards them. The leader realized the fire was going to overtake him before he could get to safety, stopped running, thought for a second, and then set his own fire to create an already burned spot, which he then stepped into so that the forest fire would go around him. Most of his team was lost because they were only listening to their emotional brains telling them to run from the fire.

I liked the book’s balance between the “Blink” theory of trust your instincts and the “Descartes” theory of following reason. Both methods of cognition have advantages and disadvantages, and the best decisions will be made by taking those strengths and weaknesses into account. In some sense, the two brains are mental tools, and it’s up to us to understand when it’s appropriate to use each tool.

I was listening to the Fresh Air interview with Jonah Lehrer, author of
How We Decide, and he mentioned an experiment that seems relevant to me right now.

Lehrer describes the experiment in a Wall Street Journal article about New Year’s Resolutions:

In one experiment, led by Baba Shiv at Stanford University, several dozen undergraduates were divided into two groups. One group was given a two-digit number to remember, while the second group was given a seven-digit number. Then they were told to walk down the hall, where they were presented with two different snack options: a slice of chocolate cake or a bowl of fruit salad.

Here’s where the results get weird. The students with seven digits to remember were nearly twice as likely to choose the cake as students given two digits. The reason, according to Prof. Shiv, is that those extra numbers took up valuable space in the brain—they were a “cognitive load”—making it that much harder to resist a decadent dessert. In other words, willpower is so weak, and the prefrontal cortex is so overtaxed, that all it takes is five extra bits of information before the brain starts to give in to temptation.

In other words, the brain is not capable of making good decisions when overtaxed. For instance, if one were working long hours at Google, one’s ability to come home and exert the self-discipline necessary to write a blog post instead of flipping on the TV would be impaired. Just as a theoretical example.

The unfortunate implication of this, and the basis for this post’s title, is that it is those times when one is stressed that one most needs the ability to make good decisions. When I get overloaded at work, I get tunnel vision and start focusing mechanically on the tasks assigned to me, rather than taking the time to figure out what’s actually important and working on that. I also make other bad decisions like drinking more soda, skipping the gym, eating chips and cookies at work, and watching TV instead of sleeping. And, of course, those behaviors make me even less efficient, which means work takes even longer, which means the behavior perpetuates itself.

As an aside, breaking the cycle required a full two weeks of doing nothing over the holidays plus a couple weeks of a “normal” work week for me to rebuild my reserves to where I felt capable of blogging again. Now that I’m keeping more reasonable hours at work, I go to the gym, I’m eating better, and I’m even excited about blogging in the evening.

So how do we avoid this paradox? It seems to me that the bad behaviors like TV and junk food are always lurking in temptation for me, and the good behaviors like hitting the gym and writing blog posts require self-discipline. Part of it is building desired behaviors into habits that I do without questioning: successful examples of that for me include biking to work and flossing while unsuccessful ones include daily situps and pushups, hitting the gym regularly and blogging. Others have success by using a game of sorts where badges are earned for performing the desired behaviors, but I have trouble taking such games seriously.

Another weapon I have is simply self-awareness. If I consciously remind myself that I’m making bad decisions when I’m overloaded, it will hopefully make me question those decisions as I’m making them e.g. putting back the Oreos from the snack area at work and grabbing an apple instead. It’s helpful for me to treat my mind and body as systems that I can learn to optimize and compensate for, like having a tool that one has learned to use despite its quirky tendencies.

An extension of that last tactic is the one the WSJ article suggests, which is building up the muscles of self-discipline. Rather than doing lots of things at once, it would be better to focus my energy on building one habit, and only start on a new behavior when the first has become automatic. Right now, I’m splitting that self-discipline energy between work, going to the gym a few times a week, and blogging more regularly, so if I find myself slipping, I’ll have to prioritize more effectively. I need to recognize that my self-discipline is limited and deploy it in the most effective way until it gets stronger, rather than exhausting it to the point where I don’t do anything.

Anyway, given my struggles with work-life balance, I wanted to mention this experiment and how I perceive it as being relevant to my life. What tactics do you use to develop new habits?

P.S. I’ll be in Boston from Feb. 6-10 and New York from Feb. 11-14, with the timing chosen so that I could attend Grant McCracken’s Chief Culture Officer Boot Camp, but that’s just the cover reason for me to catch up with friends on the East Coast. Let me know if you want to meet up.

Book website, with excerpts
Amazon link

A coworker recommended this to me, and was even kind enough to lend it to me for the weekend.

Coyle asks the question: where does talent come from? Is it nature (genetics) or nurture (environment/opportunity)? He started by visiting several talent hotbeds – the Russian tennis academy that spawned Marat Safin and Elena Dementieva, the Curacao Little League baseball team that has been consistently reaching the world semifinals, the soccer fields where Brazilians train – and constructs a thesis around what common factors he sees among those hotbeds.

Here’s what he came up with. Talent is a mix of three factors:

• Deep practice – I’ve also heard it called deliberate practice. This is the kind of practice that is referred to in the “10,000 hour rule” popularized by Malcolm Gladwell – that it takes 10,000 hours of devoted effort to become a world-class expert at something – that’s 3 hours a day for ten years. Note this doesn’t mean just doing an activity – it means continuously pushing the limits of your ability, always operating just out of your comfort zone, making mistakes and learning to fix them, getting comfortable with that dynamic of improving by failing. And it’s making sure that time is spent doing the activities that you need to improve, whether it’s ball handling in soccer, technique in tennis, or expressivity in music.

  He has three rules for deep practice:

  • Chunk it up – he breaks this into three parts as well – absorb the whole thing, break it into chunks, and then slow down each chunk until you can get it exactly right. I described something similar in my cognitive subroutines post.
  • Repeat it – This doesn’t mean repeating it mindlessly – it’s more about practicing each day and trying to push the limits just a bit more. He cites research saying that we can only live in that edge zone for three to five hours each day, so any more than that is just mindless repetition and doesn’t actually help.
  • Learn to feel it – In other words, internalize it to the point where it’s unconscious and emotions guide your reactions rather than depending on conscious rational thought. Our conscious mind is slow, so to be effective, we have to get everything into the unconscious.
• Ignition – This is the will necessary to sustain oneself through those interminable hours of deep practice. Coyle suggests that one powerful factor is seeing others do it – if they can do it, why can’t I? He gives the example of Roger Bannister and the four minute mile – it was considered humanly impossible until Bannister did it, and within a year many others had. Or the explosion of baseball talent in Curacao after watching Andruw Jones, from Curacao, hit two home runs in his World Series debut as a 19-year-old rookie. Or the rise in South Korean professional women golfers after Se Ri Pak won an LPGA event in 1998. Ignition can also occur because of a desire to belong – Coyle cites several examples of clubs or teams providing the spark for kids to invest the necessary practice time.

  My favorite point in this section was a study by Gary McPherson which tracked students who were taking up musical instruments in middle school, and discovered that the single best indicator of how successful they would be with the instrument was a question that was asked of them before they started: how long do you plan to continue playing this instrument? Those that said they were planning to play the instrument for the long term got more out of 20 minutes of practice than the short-termers got out of 90 minutes. The instrument was part of the long-termers’ identity, and so they wanted to continue pushing themselves and get into that zone of deep practice.

• Master Coaching – Coyle suggests that both deep practice and ignition can be catalyzed by a great coach. The coaches that he interviews are masters at observing each student and pushing the right buttons for each of them to get to the next level. Praise and criticism and information transfer are simply tools to push students to stay in that zone of deep practice at the edge of their abilities. For example, Coyle cites a study of John Wooden’s coaching style, which said that 7% of his communication was praise, 7% was criticism and 75% was information transfer – much of it in the form of “Here’s the right way, here’s what you’re doing (incorrectly), and now here’s the right way again” to reinforce the subtle improvements he desired. Another good quote from the coaching section was that “small successes were not stopping points, but stepping stones … Good. Okay, now do ____”.

One major theme of the book is the process by which expertise gets embedded in our brains. Coyle cites neuroscience research showing that brain circuits that get used extensively are reinforced by growing a myelin sheath around them – the myelin provides insulation for those neural pathways and improves the speed at which those neural pathways fire. In other words, as we repeat and get better at an activity, there is a physiological change that speeds up the signals in our brain so that we can do it faster. I love how this ties into my idea of cognitive subroutines and why I think that repetition and memorization is critical for expertise. I also learned that the myelin sheath breaks down so it has to be continually rebuilt, which is why we have to keep practicing every day if we want to maintain our expertise. Also, it responds to neural activity, and the activity is strongest when we are in deep practice mode, trying new things and seeing what works and what doesn’t.

All in all, a good book covering an important topic in a well-written breezy way. Admittedly, I like it partially because it reinforces my existing biases, so I liked the anecdotes and the neuroscience that supports those biases.

P.S. Another John Wooden quote: “Don’t look for the big, quick improvement. Seek the small improvement one day at a time. That’s the only way it happens – and when it happens, it lasts… Repetition is the key to learning.” This reinforces Drive‘s point that we need to pick our overall goal and get a little better each day.

One of the topics I want to think more about is organizational cognition aka how organizations think, and how to design an intelligent organization. For some reason, I was thinking about this today, and made a connection to standard theories of cognition that I hadn’t made before.

Let’s start with Descartes’s view of the world: I think, therefore I am. In this view, consciousness is what fundamentally defines us as human. Our rational, conscious minds take in sensory input, make decisions and execute actions in response. Consciousness and thinking are assumed to be identical. Note: I am aware this is an oversimplification and possibly a mis-statement of Descartes, but that’s what straw men are for – see the Wikipedia entry on the Cartesian theater for a similar take.

This view of how we think has been shown to be incomplete, at best. Books like The User Illusion and On Intelligence describe an unconscious mind which is doing so much processing and filtering that it can often respond without ever involving the conscious mind. One might picture this as a bubbling brew of unconscious perceptions and responses which only rarely permeates the conscious mind.

What was new to me today is how these two views of the human mind might map to theories of corporate management.

The first view of cognition corresponds to the archetypal hierarchical command-and-control corporate structure, with the executive team corresponding to the conscious mind. All major decisions are brought to the CEO or executive team, a decision is made, and instructions are fired off to the rest of the company to execute. Once decisions have been made, processes can be put in place to ensure that such decisions are made consistently without the need to bring them to the executives again, much like McDonald’s has its three-ring binder which specifies every aspect of running a fast food franchise in a completely standardized way.

It’s less clear what would be the management equivalent of the second view of cognition. I think it’s closer to my idea of what an intelligent organization might look like, with self-organizing teams that band together to achieve a common goal. In such an organization, managers might not be hierarchical decision-makers, but instead “exception handlers” who trouble shoot problems that are not handled well by the existing teams (for some reason, I’m picturing the Wolf from Pulp Fiction here). This would be the analogue of the conscious mind only being involved in decisions where there is no established cognitive subroutine. In such an organization, most things would bubble along, being handled by the teams, and only rarely would be surfaced to the “conscious mind” of executive management.

Of course, this is an overly broad analogy, and figuring out what such an organization would look like in practice is really difficult (how do we balance between surfacing problems when needed and keeping the critical decision-makers from being overwhelmed?). But I thought it was interesting to explicitly draw the cognition analogy to organizations and see what that might imply about management. I’ll have to think about this some more. And, of course, I’d welcome any thoughts you have.

I’ve noticed a fundamental distortion in how I view the world:

• If I know the answer or how to do something, it’s easy.
• If I don’t, it’s hard.

This is a distortion because this worldview devalues my accumulated experience and knowledge. It’s funny because I know how long it took me to learn what I’ve learned, and yet because it seems easy to me now, I assume it’s easy for everybody. A trivial example: I consider myself a low-intermediate ultimate frisbee player, and yet when my coworker asked me a question last week about various terms, I was diagramming plays on the whiteboard, explaining different defensive strategies, etc. – things which took me a couple years of playing regularly to learn.

I read Malcolm Gladwell’s Outliers recently, and one of his points in the book is that it takes 10,000 hours of deliberate practice to become a master of a discipline. I’ve commented before that this is because it takes that sort of repetition to move the skill to the unconscious so that the conscious brain can concentrate on higher level thoughts. In some sense, it’s become “easy” to my conscious brain because the unconscious brain is doing all the heavy lifting.

That’s part of the power of making things easy. Designs which make things easy provide a shortcut to a sort of “mastery”, at least with regard to accomplishing a certain task. The downside is that such shortcuts do not provide the full context necessary for true understanding, and so poor decisions will be made when parameters stray outside the boundaries for which the application was designed.

The mortgage meltdown is a good example of the perils of these shortcuts, as the ability to securitize anything and pass it on was amplified to the point where it brought down the global economy. It shows the importance of being a good information carnivore, somebody who understands their information food chain and the assumptions implicit in that chain. It also suggests that there are times when things should be difficult – because securitization worked so easily and so well, it became the default solution (creating CDOs etc.) without anybody questioning whether it was an appropriate use.

An ideal design would make it easy for users to do what the application was supposed to do, and difficult to do what it’s not. I don’t necessarily think that an application should make it impossible to do “off-label” things, as there are times when people will need to do that, but it should make it very clear that the user is likely to shoot themselves in the foot if they proceed. In other words, “making things easy” isn’t the only goal of design – it’s making the right things easy, and the wrong things hard.

P.S. I await Seppo’s comment explaining how this relates to game design

Why was the iPod successful?

• It didn’t have the most features – I once bought an Archos Jukebox with many options unavailable on the iPod at the time.
• It certainly wasn’t price – I bought a Dell DJ for $100 less than a comparable iPod in 2005.

The design and user experience, the sleekness and trendiness, certainly played a part.

But the most important thing, to me, is that the iPod made things easy. Here’s how to buy and listen to a new song on an iPod:

1. Look it up in the iTunes store.
2. Click to buy.
3. Sync your iPod.

Easy. No trying to remember where you downloaded a certain file, or making sure it’s in the right directory to get transferred to your MP3 player, or trying to find a legal copy to buy – Apple has taken all of the effort out of this fundamental transaction.

And I think this is something to remember – a good business plan can be built around taking the things that should be easy, and making them easy. Why is Google successful? It makes it easy for advertisers to find users who are searching for relevant information, and easy for users to find relevant advertisers to their interests. Google makes it easy for these two populations to find each other, and has made absurd amounts of money.

It reminds me of Seppo’s description of game design – find the fundamental unit action of a game, and make it fun. The equivalent for business model design is find a fundamental action of a user, and make it easy. There is value in making things easy, and users will pay for that value.

Even the rise of blogging can be seen as a testament to this idea. From the earliest days of the Web, it was possible to post updates and thoughts on a web page – it was crude by modern standards, posting individual HTML pages, but possible, as evidenced by my ramblings page which was started in 1994. But the advantage of blogging software is that it makes it much easier to post an update. And although I don’t pay for WordPress, I do pay a subscription to LiveJournal and MyBlogLog to make my blogging easier.

Twitter takes the next step to making it so easy to keep one’s friends informed that we can do it from anywhere we have cellular access. I think that Twitter may be the perfect mobile application in that it is easy to dip into the Twitter stream whenever I have a few minutes to kill, and I can do it from anywhere. I do worry that it is destroying my attention span, though.

One last example: Google has changed how I do things because it makes certain things so easy. I have now given blood twice and plan to continue doing so. It was always something I meant to do, but never got around to. But when Google brings the blood drive on campus, so all I have to do is go downstairs, it’s so easy that all of my objections go away, and I just do it. Similarly, having the Mountain View Public Library come to campus once a week, and making it possible for me to request books via email, means that the library is now more convenient than Amazon (which in itself is an example of a business model built around making a common action easy).

It makes me think that there are plenty of business opportunities left in the world. I feel like any time I encounter something that is difficult that I can imagine could be made easy, I should now react to it by thinking of it as an opportunity rather than a frustration. Admittedly, it’s only a business opportunity if it’s enough of an annoyance that a significant number of people will pay for a solution. By making it easy to do things that were difficult or impossible before (like buying music online or finding people interested in your advertising), an entrepreneur can create new value in the world. And it seems like there’s an endless supply of things in the world that should be easier.

I really liked Tim O’Reilly’s post today about how companies like Google and WalMart are incorporating IT into their organizational DNA. O’Reilly’s post describes how those example companies are mapping out a new way of organizing people built around integrating IT into how the organization functions:

Sensing, processing, and responding (based on pre-built models of what matters, “the database of expectations,” so to speak) is arguably the hallmark of living things. We’re now starting to build computers that work the same way. And we’re building enterprises around this new kind of sense-and-respond computing infrastructure. …It’s essential to recognize that each of these systems is a hybrid human-machine system, in which human actions are part of the computational loop.

I particularly like O’Reilly’s description of the organization as a group mind that incorporates both people and machines, as it fits in with my thoughts on organizational cognition. The organization also incorporates culture, processes and many other feedback loops that structure how the organization accomplishes its tasks.

Let’s start by taking a quick look at two existing organizational models:

• Small teams – the pre-industrial-age organizational model. In a small team, no organizational structure is needed because everybody knows what everybody else does, and decisions can be made organically or by consensus. New team members are indoctrinated into the way things work by social pressures. Whether discussing hunter-gatherer bands or artisan guilds, it’s rare that organizations grew to more than 30 people without splitting into smaller groups. There’s a reason that even modern managers understand the power of small targeted teams. Communications limited the size to which a team could grow, as the number of communication pathways grows exponentially with the size of the team.
• Hierarchy – the industrial-age organizational model. Information and decisions are funneled up to the appropriate decision-maker, and the resulting decision is distributed out to the employees who carry out those decisions. This was ideal in a world of limited communications, as each employee knew that information flowed up to their manager, and decisions flowed down from their manager, so they only had one primary communication link to maintain. Hierarchies also simplified assimilation of new people because the hierarchy defined each employee’s responsibilities, generally in an organizational handbook.

There have been various hybrid organizational models where there are hierarchies of teams and other configurations, but teams and hierarchies have been the basic building blocks for most organizations.

We are in a fascinating time where the number of possible organizational solutions has gotten much larger, as technology has removed the communication limitations that previously eliminated many potential configurations. We are just now figuring out what the new possibilities are, evaluating their strengths and weaknesses, so that we can find the appropriate option for a given venture. To put it in geekier terms, we are starting to map out the vastly expanded search space for organizational structures.

I think O’Reilly’s post identifies one direction, where organizations integrate computers so that certain decisions (like Google ranking web pages) don’t need to be handled by people and instead information deluges are handled by software. One of my interests is in trying to map out other possibilities, what they would look like and how they would fit various organizational purposes. My previous post about the future of organizations discussed how the new limitations may be social rather than technical, which implies that we need to start designing new social structures that can take advantage of the newly available technology.

One possibility that I’m playing with is that of overlapping teams with clearly defined roles. The good teams I’ve been on involved people who trusted and respected each others’ contributions to the team’s overall goals. I’d like to think that a fractal organization could be built off of such teams which each have a team goal, and then each team trusts the other teams to accomplish their goals in order to satisfy the organization goals. There would be a ton of communication necessary to distribute information within the organization to where it needs to go, but I think that is becoming more realistic by the day.

Another possibility is the free agent world, where there are no continuing organizations. Instead, coalitions of individuals are formed for specific projects, accomplish those project by bringing in other people as needed, and then disband to pursue other projects with different people. This would be the endpoint of the world where everybody becomes a consultant in their specialty.

I’m sure there are lots of other possibilities that I haven’t considered. For instance, I’m definitely interested in what we can learn from how World of Warcraft guilds are organized to accomplish their goals when every player is free to leave guilds that don’t work for them. Or how organizations mobilize volunteers to work for them – I’m sure there’s much to learn from Obama’s campaign this year. I’d love to hear of other ideas that people have on how to organize people.

P.S. I finally created the Google group/email list to discuss organizations that I mentioned in that future of organizations post, so go ahead and join up if you’re interested.

Paul Graham’s latest essay claims that small organizations are the future:

“But in the late twentieth century something changed. It turned out that economies of scale were not the only force at work. Particularly in technology, the increase in speed one could get from smaller groups started to trump the advantages of size. …For the future, the trend to bet on seems to be networks of small, autonomous groups whose performance is measured individually. And the societies that win will be the ones with the least impedance.”

This is interesting to me because I’ve been thinking about organizational cognition recently, which is the question of how an organization creates a group mind that knows more than its individual constituents. If the trend is towards smaller organizations, then perhaps the problem isn’t how to get large organizations to operate more effectively, but instead how to facilitate cooperation between organizations. These are similar problems, but existing organizational solutions like hierarchies don’t work for inter-organization collaboration, which creates urgency to find more flexible solutions.

This move towards less formal organizations to accomplish tasks is also covered well in Clay Shirky’s Here Comes Everybody. Shirky cites Ronald Coase’s theory that companies exist because the transaction costs associated with organizing people were more expensive than the associated inefficiencies of not necessarily finding the best person for each individual task. According to Shirky, new technologies lower the Coasean floor and create the possibility of impromptu evanescent gatherings of people accomplishing things together that could simply not have been organized previously.

So how small can organizations get? Are we approaching a full free market world where we recruit different people for each individual project (the analogy I use in that post is movie making)? I don’t think so. And here’s why.

My theory is that the new Coasean floor is going to be set by social trust. While we are in a world where I could hire a programmer to do a task from Elance or oDesk, I have to admit that I would be very nervous about doing so for any critical task. Why? Because I wouldn’t know the person and wouldn’t trust them.

It takes time and experience together to build the trust necessary for a team to function effectively and efficiently. Teams do not begin jelling as high performance units until each member of the team trusts the others to the point where he or she feels comfortable outsourcing parts of their intelligence to them. In other words, even though we have the physical technology now to collaborate informally and spontaneously, we do not have the social technology yet to fully exploit those capabilities (which, now that I re-read that post, reminds me that I need to get back to that topic at some point).

So where does the social trust Coasean floor lie? Katzenbach and Smith suggest that the highest performing teams have between 6 and 15 people – the lower bound is set by not having enough variety of skills within the group to really create a group mind, the upper bound by communication inefficiencies. That range sounds right to me as well, based on my own experience with various teams at various companies. To really get an answer, we’d have to map out the performance curve of groups as they grow; in other words, 2 people working on a project together might get less done than those 2 people working independently because of the communication overhead, but they might be more effective because they can bounce ideas off of each other. How that scales up to 3, 4, 5, or 10 people depends on the people, and the organization, and the communication technologies in place. But I would guess that the sweet spot is in the 6-10 person range.

If that is the team size which is most efficient from a social trust perspective, we return to the original question I posed above: how do we facilitate communication and collaboration between such small teams? What are the social and physical technologies we can use to transfer knowledge and expertise so that teams can build off of each others’ work? I don’t know what the answers to these questions are yet. Some people would suggest semantic knowledge management technologies to parse knowledge and distribute it automatically to the right people. Others would suggest quantitative approaches where measuring for the desired results will spur appropriate action. I tend towards humanistic approaches where trained generalists build the bridges between such teams, but I’m slightly biased as that’s one of the roles towards which I strive.

I think these social technology design questions have the potential to created fantastic productivity benefits over the coming decades. We’re hitting the limits of what physical technology can do for us. We have more and more powerful computers that sit idle most of the time, as users stare at them trying to figure out the interface. No amount of technology seems to remove the need for meetings to synchronize the organization. And we’re at a fascinating time when the physical technology Coasean floor has been removed, opening up new experimental possibilities for social technologies to help solve these organizational questions. I plan to continue exploring this topic, and hope that you will join me.

P.S. To be specific, a few of us from Convergence08 are starting a regular get-together where we exchange ideas on the topic of how organizations think and work, and share articles and resources via email; in fact, this post was inspired by discussion from that list. Let me know if you’d be interested in joining us.

In my post about Philip Zimbardo’s work, I mentioned the concepts of situational vs. dispositional tendencies. One might see these as being obscure cognitive constructs. However, a recent situation made me realize that beliefs about these tendencies have direct consequences on management styles. So let’s dig into this some more by starting with a description of the two tendencies before getting into consequences for management.

Dispositionists believe that our tendencies and behaviors are fixed because of the kind of person that we fundamentally are. They search for explanations in a person’s character to explain their behavior. So when a criminal steals, they try to find the “flaw” in that person’s character that would make them perform such an act. This explanatory search can concentrate on nature (looking for genetic correlations) or nurture (looking at the childhood surroundings), but the search is for a character trait within the person that explains their actions.

Situationists like Zimbardo think that people’s behaviors, while influenced by their parents and upbringing, are dominated by the situation in which they act. The Stanford Prison Experiment is the most glaring example of this, where intelligent, well-adjusted college students turned into abusive guards and mentally unbalanced prisoners within three days of being placed in a prison environment. Because of these overwhelmingly powerful situational effects, if somebody performs “evil” actions, it is not necessarily an indication of a fundamental character flaw on their part; instead the situation must be examined to see how it contributed to the actions.

When comparing the two, the dispositional viewpoint is easier to understand, with a simple narrative to explain somebody’s actions (“Lucifer is a bad person, which is why he did bad things”). The tricky thing here is that saying something is something raises warnings flags for me (see my review of Wilson’s Quantum Psychology for a longer take on the difficulties of “is”-ness). Attributing a characteristic as a fundamental component of something, as is implies, simplifies the narrative, but at the cost of making us more vulnerable to the true complexities of life (I’m reading Taleb’s The Black Swan right now which expands upon this idea). The dispositional viewpoint also has dangerous consequences in how we raise kids: treating intelligence and talent as fundamental characteristics of children actually retards their development, as they don’t even try to improve themselves. I think that while we have dispositional tendencies, we need to recognize the situation defines how we behave. But I’m going to stop with the discussion of the tendencies themselves (since others have done it better), and focus on the managerial consequences of these two ways of thinking about people.

In a dispositional workplace, life is relatively simple – you interview candidates, find the ones that have the right fundamental attributes (e.g. “Smart and Gets Things Done”), and then focus on removing obstacles to progress so that these people get things done, in accordance with their nature. It’s a nice, tidy view of the world. Unfortunately, I think it’s too simple, as it ignores the influence of the system on the attributes that people display – people that are tremendously successful and effective under one system might be completely ineffectual and unmotivated in another system where their strengths go unused, as sports teams find out each year in free agency.

Situational management is about designing the system to match people with the appropriate environment to get the desired organizational results. This system design can take a couple forms:

• Designing a financial incentive system that rewards appropriate behavior, although Robert Austin cautions us as to the difficulties with this.
• Desiging a culture and vision that reinforce the desired employee characteristics towards a common goal, such that employees “believe in the mission they are trying to accomplish and know that they are contributing to its success”, as a former CEO of Southwest Airlines puts it.
• Understanding employees’ strengths and weaknesses and giving them jobs that leverage their strengths and minimize their weaknesses. The canonical example of how not to do it is promoting a great software engineer into management, since the manager mindset is completely different than the engineer mindset. Good management in this scenario is about placing people in situations that maximize their chances for success while contributing to organizational goals.

What’s I like about this conception of management is that it means that management is a design position. Management in a dispositional world is about hiring the right people and then getting out of their way – it’s passive and uninvolved. Management in a situational world is an iterative systems design problem with constraints – managers have to pick a vision, align employees with that vision, work towards the vision, re-evaluate progress, possibly pick a different vision that aligns better with the strengths of the employees, etc. It’s an ongoing active process that involves being involved with all aspects of the business, understanding how employees work best, what the organization’s capabilities are, monitoring the environment outside of the organization to understand how to align potential outputs with environmental demand, etc, and using that understanding to better design how the company works. This is the type of manager I aspire to be someday.

Noah Brier wrote an interesting post yesterday about how certain ideas spread virally even when people disagree with them. His examples include Sarah Palin or Wired’s “Blogging is dead” article, where the blogosphere is buzzing about how bad an idea something is, but are still spreading the original idea far beyond its original audience because they can’t resist the urge to respond critically to it. I left a comment on the post, as it relates to some thoughts I’ve had over the years, and then realized that I would need a full blog post to unpack the one paragraph I wrote. So I’m writing one.

I had this vague intuition for years that arguing against an idea still supported the idea. I never was able to fully articulate this intuition until I read George Lakoff’s work on framing, which explained how arguing against a proposition still reinforces the proposition as stated. Lakoff’s classic example is “tax relief” – even arguing against “tax relief” reinforces certain connotations, including the idea that relief implies an affliction. So referencing a worldview, even if one is arguing against it, still reinforces that worldview.

So why do people do it? I have a feeling that we are wired to play finite games, where we are trying to win the game with the rules as stated, rather than infinite games, where part of the challenge is to step back and re-define the rules (James Carse’s book Finite and Infinite Games is obviously a big influence on me). So people get caught up in trying to win the argument within the context that they are given, rather than thinking about their overall picture and whether they are contributing to that. In other words, I agree with Noah’s point that “the best way to fight this kind of behavior is to not talk about it. But most people can’t help themselves.” We want to win the finite game, even when the game as framed will contribute to the other side’s success. To avoid that, we need to be thinking about playing the infinite game instead.

Getting to Yes is another framework for thinking about these sorts of issues, as it emphasizes figuring out your principal interests and focusing on those, rather than getting sucked into zero-sum positional bargaining about specific issues. If we go into a negotiation focused on winning every individual point, we may often fail to actually achieve our interests (much like Internet pundits arguing against certain issues, but only providing them more visibility and respectability in the process).

So when faced with a screed which makes us want to argue and tear down an opposing perspective point by point, we need to step back and figure out if we’re just contributing to their worldview by doing so. We need to concentrate on our overall vision and figure out whether what we’re doing is contributing to that end goal. We need to find opportunities to reframe the discussion to find points of commonality (e.g. both sides of the abortion issue agreeing that they’d like to see fewer unwanted pregnancies) so that everybody can feel like they are moving towards their goals.

Or, sometimes, we just need to accept that the other person is too locked into their viewpoint for us to be able to convince them. If their frames are so strong that all incoming information will be mapped to their frame, such that no facts or arguing will convince them, we need to recognize that and move on rather than continue to futilely waste our time. This is definitely one of the hardest skills to learn on the Internet.

Man. I really need to get back into writing regularly. There’s a whole trove of interesting territory around zero-sum vs. non-zero-sum thinking that I need to explore at some point. It’s fascinating stuff to me, and while it’s a frame that I’m probably over-applying right now, I think it has some explanatory power.