It can be difficult for managers to find the right balance between the time spent in meetings and the time spent solving tasks. But researchers at Wayne State University believe that ants' behavior provides an important lesson in how to do it best. By using computer simulations, based on the foraging behavior of ants, Kai Yang, professor of industrial and systems development at Wayne State University, has developed a method to assess what the optimal balance between "talk" and "work" is.
The secret of the ants is that they manage to make decisions without having to hold a meeting first. The ants, on the other hand, act as one individual, and can do amazing things without a boss. They basically function as one organism, so the need for communication is very small.
The secret of ants' efficiency is uncoordinated decision-making processes. Ants perceive and respond to the world through the colony's thousands (or millions) of eyes, rather than through the eyes of the individual. This collective intelligence is much more effective than any individual. You could say that ants act like a big brain: each individual is like a neuron in the human brain and intelligence is embedded in the interactions between the countless parts.
Scientists have studied the foraging behavior of ants and have discovered that changes in the pheromone trails the ants lay down convey the best route for the following insects to take. This discovery led to the development of the ant colony optimization models, which researchers use to optimize human behavior.
Algorithms based on ants are already a thriving industry in computer science, artificial intelligence and robotics. The algorithms can also be transferred to groups of people trying to solve complex problems, as they face the same dilemma as the ants: How do you make efficient, accurate decisions in large groups?
The researchers from Wayne State University used these ant-inspired algorithms to find the optimal balance between planning a task and executing it. Yang used mathematical models of ant behavior – “non-discrete ant colony optimization” in researcher parlance – to set up a model for how a mobile phone can most efficiently be produced on time and with the highest quality.
When the team applied these algorithms to mobile phone development, the project's completion time was reduced by 17 % (from 158 to 130.5 days), while costs were increased by only 8 %. Yang shows that it is much more efficient for tasks that normally occur as separate and sequential (eg, communication and execution) to be solved as a sequential process instead. This of course entails extra work (fixes and extra communication), but the system as a whole works more efficiently.
The research trial published in International Journal of Production Research, is of course very simplistic, so in practice there is ample opportunity for a lot to go wrong. But the ants have had 100 million years to perfect their cooperation, while humans have lived in large groups for only a few centuries, so there is good reason to believe that we have much more to learn from the ants about efficiency.
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