It’s common wisdom that once a wealth management shop reaches a certain size, things start to click. Phones start ringing, more referrals are generated, profits increase, and a genuine buzz about the firm begins. Although an observation like this seems a bit subjective, there is a scientific rationale behind it ?? 1/2 and it is referred to as network theory.
Scientists are finding that concepts as diverse as the interaction of molecules to the behavior of real-world economies can at least be partially explained by the complexities of interaction and the development of networks. A fascinating aspect of such research is the observation that extremely large and developed networks follow the same mathematical laws as simple ones, if they are given enough time to mature. Industries and even individual firms follow this same pattern; as a result, networking can partially explain what is happening in wealth management today, and may give a glimpse of possible scenarios in the future.
An example of a network is the dispersion of wealth. At first, describing such a distribution is akin to placing a large number of coin flippers in a room. Those lucky enough to flip heads slowly amass more assets, the distribution of which can be roughly analogous to a bell curve.
But as the experiment continues, things start changing. Winners amass other’s coins and begin figuring out ways to become better coin flippers. Lucky flippers begin to segregate themselves from the unlucky, and share information on how to increase their fortune. After the network becomes more mature, the distribution of wealth follows a power law.
A surprising number of networks, both artificial and real, obey power laws. Although such networks are not identical, they tend to follow the same basic principles. Examples include: 80% of all web searches involve 20% of websites; 70% of academic journal citations are based on 30% of scientists; and 75% of all peas are produced by only 25% of all peapods.