The Buzz of Entrepreneurs: Hunting Dynamics Part II

Last week I blogged about the virtues of organizations with “hunting dynamics” – networks that could spread themselves out across an opportunity space to explore for opportunities that come and go in unpredictable ways. Once a resource is discovered, the network contracts so that all its members can gather round the resource to extract its value. After the resource has been used, the network springs back again into its extended mode to go exploring again. This so-called “fission-fusion” dynamic is found in an astonishingly variety of innovative groups, ranging from the Quakers and Nonconformist sects of the First Industrial Revolution and the Jewish diaspora to the West coast Norwegians and the Parsees of India. Physical locations like Silicon Valley and Route 128 in Boston have also been cited as examples of places that encourage these kinds of interactions.

These ecological dynamics are found everywhere in nature. One of the most startling is the pulsating networks of slime moulds found in ecosystems like forests that allow up to 20,000 individuals to form a single organization. Experimenters have used a mould called Physarum polycephalum (“many-headed slime mould”) to solve mazes and other complex problems. In one experiment researchers placed a mould in a space that had blocks of food on it laid out in the same relationship to each other as the cities of Portugal and Spain. Within a few hours the mould had created a network that resembled the highway system on the Iberian Peninsula! The moulds do this by exploring as many options as they can and then pruning the ones that turn out to be dead ends. It reminds one of Edison’s comment, “I didn’t fail ten thousand times. I successfully eliminated, ten thousand times, materials and combinations which wouldn’t work.”

A Buzz of Entrepreneurs

Honeybee Democracy

Honeybee Democracy

An even better example of these dynamics can be found in the behaviour of honey bees when they leave their hives in search of new nesting sites. In his book, Honeybee Democracy, biologist Thomas D. Seeley, details the amazing behavior of these insects based on his meticulous research over many years. He studies how small organisms with limited information and limited intelligence manage to make wise collective decisions in complex, variable conditions.

No one really knows what triggers a hive’s decision to leave its home and search for new site but every researcher agrees on one thing – the queen bee is not a boss that issues orders to her subjects and tells them what to do. She just lays eggs – typically about 1,500 on every summer’s day to keep the work force up to strength. Rather, the swarming behaviour is triggered by environmental cues, both internal and external to the hive. Inside the hive the triggers seem to be crowding and the presence of many young, immature bees. Outside the hive, the availability of plentiful resources is important. The process takes place in late spring/early summer and the bees have a busy time ahead. They have to prospect for a selection of suitable sites, choose among conflicting options, navigate to the new site, build a new set of combs, raise new workers (bees only live about five weeks) and stock the new hive with resources to last through the winter, Typically in North America only about 25% of colonies moving to a new home survive in the first year. Although this also means the some sites will come ready equipped with combs that can be used by the new inhabitants – a highly-prized feature of sites!

The analogies with hunting dynamics and those of entrepreneurs are clearest when we look at how hives start the search process. According to Seeley’s findings the scouts for new sites tend to be elderly foragers who change their search criteria from “bright blossoms” to “dark crevices”.  About 3-5% of the bees become scouts, which means that there are about 300-500 explorers in a typical colony of 10,000 bees and they will explore an area of about 30 square miles. On their return to the hive they “tell a story” in the form of a dance that is a mini-simulation of their flight. The dance’s duration reflects the length of their flight; its angle shows its direction relative to the position of the sun and its strength shows their assessment of the relative attractiveness of the site. It’s the passion of the bees for their sites that eventually attracts the attention of others! After the initial options are laid out by their different supporters, over time the successful scouts gain support by recruiting other bees until eventually the entire colony reaches agreement on a single site. This site is usually the best one available and balances numerous different criteria.

The way in which the bees reach this “agreement” is fascinating. First of all a quorum of 20-30 bees on a prospective site (half of them inside, half of them outside) seems to trigger a change in behavior, so the site to first reach this number becomes a tipping point for the behavior of the whole colony. This means about 75 scout bees in all are in favour of the site, as some are always in transit between it and their old home. This allows a swarm to move without necessarily having complete agreement at the time it takes action. Over time, however, bees that danced for less favourable sites lose their enthusiasm for them and go along with the popular choice. Selley and his fellow experimenters have constructed a mathematical model that replicates this behavior faithfully. By playing with the quorum size and the rates at which scout bees’ passion for their choices decays, they have shown that honeybee “democracy” makes the optimal trade-off between the speed and accuracy of their decisions.

The Takeaways

For management thinkers, the stories of slime moulds and the honeybees and how they switch from exploiting old resources to exploiting for new ones are an endless source of generative analogies. A good analogy is not a substitute for an argument – but it should remind one of good and often novel arguments. In The New Ecology of Leadership I mentioned Thomas Seeley’s work briefly. I listed the following conditions as necessary for “swarm intelligence” to emerge in a system:

  1. Diversity of knowledge about the available options
  2. Open and honest sharing of information about the options
  3. Independence in the members’ evaluations of the options
  4. Unbiased aggregation of the members’ opinions on the options
  5. Leadership that fosters but does not dominate the discussion

To this list we may add some additional thoughts from Seeley:

  1. Make sure that the group is sufficiently large for the challenge it faces
  2. Make sure the people have diverse backgrounds and perspectives
  3. Foster independent exploratory work on the part of the members
  4. Create a social environment in which people feel comfortable about proposing solutions

These days, with our concern for innovation, such advice is commonplace, but it’s interesting to realize how these adaptive behaviours have their origins in nature and the hunting dynamics of our ancestors.




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