Today, we’ll stretch things a little, into a world of cross-overs between network theory, human psychology, systems engineering, and maybe economics. Networking is a pretty basic concept, and the term is broadly used, to the point that the meaning is no longer precise. There are telecommunications networks that transmit digital data between a vast variety of servers, switches, data stores, your house, and you (at least your phone, your headset, your watch, and maybe your flesh-embedded monitors – but not quite your brain directly….yet). I like this sort of network because (a) it’s nice and logical, (b) it paid rather nicely for much of my professional life.
There are also networks of people, and these are a LOT messier, but interesting as well. Gladwell talks about networks of people made of three sorts of individuals: mavens (experts on a topic, but generally not well-connected), salespeople (good at advocacy and driving change), and connectors (people who know a lot of people). These theoretical people are ideals, and reality is more of a continuum, so none of us would fit such categories perfectly even presuming his categories are correct. Still, the notions of “connectors” rings true to me, and I have a couple of friends here on FB who I peg squarely in that category. The same is true for mavens, and for salespeople.
A sharp guy named Metcalfe devised a theory that became Metcalfe’s Law, which says that the value of a network is proportional to its size. With a little thought you can convince yourself that this is true. Remember fax machines? What value has a network with one fax machine? Yup…zero. How about two, or ten? Not very much. How about 10,000 or a million? Lots of value. The same became true for e-mail a generation after faxes, and more recently for social media like FB too. Bigger networks have bigger value, and quantity is a quality all its own.
What about networks of people? A person, even an expert, has modest value by themselves, and they may struggle to find problems to address, and people with problems need to find them, and most hard problems requires a group of specialists working together to solve them. Now we’re back to talking about teams – and what is a team but a group of people with varied skills working together for a common goal? This means it’s also a system, by the way - a group of diverse components functioning together to achieve a common goal. And it’s a network, given the interconnection of individuals. So, a team is just a network of people that functions as a system.
As it turns out, teams of people are reasonably complex systems, and such systems pretty much always manifest emergent behaviors, meaning that they do things and have characteristics that weren’t intended. Any manager will recognize the truth in the system engineer’s adage, “All systems exhibit emergent behaviors, most of which will be undesirable.” One of the good characteristics, though, is the ability to learn. Networks of people – teams – learn new skills and new ways to solve problems a bit differently than individuals alone, because they have broader connectivity to other people, a broader collective experience base, and can leverage broader resources. It is this ability to stretch, grow, experiment, and learn to achieve problems that provides a team with value.
So if Metcalfe’s Law says that bigger networks have more value, and people interconnect as networks, why not have huge teams? Today, people are individually and collectively more well connected than ever before, and it is not clear what this will mean to the composure and effectiveness of future teams. It is clear, though, that huge teams have different dynamics and require different structures and processes than little ones, and part of system engineering is to break down big problems into smaller ones that can be solved by modest individual teams. Silicon Valley, (and Ries’ startup culture) embraces Amazon Bezo’s the “two pizza team”, even though most larger companies may have many such teams.
Of course a network may have sub-networks, systems may have subsystems, and companies may have a hierarchy of teams – that’s what an org chart displays, after all. What determines the optimal sizes? Well, one guy a while time ago took a crack at it, and his name was Dunbar. His theory is that people can keep inter-relationships straight for about 150 people, and closer relationships with smaller group sizes. Many of you who have worked at varying sizes of companies, gone to small or big churches, or interacted with small or big vendors, will likely agree at least in principle that size does indeed matter. A few companies, notably the tech company WL Gore (inventor of Gore-Tex) embraced the Dunbar Number explicitly by keeping their plants sized no larger than about 150 people; if a company grows too big, they simply split it up. So far, it's working for them.
Tomorrow we’ll pick up with types of people networks, and how those interrelate in the real world. We might start straying into economics a bit, too.
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