The value of enterprise risk management rises dramatically when a central risk function coordinates the identification of risk. The coordination task is relatively simple: Create a high-tech knowledge warehouse and allow authorized parties to discuss exposures electronically. Risk identification is more problematic since new tools are needed.

In this context, a National Geographic article in July, titled "The Genius of Swarms," triggered for me an intriguing model for risk identification in massive economic and social systems. A swarm is a large number of individual organisms that move together in the pursuit of a goal. Swarming theory describes efforts to understand the success of swarms.

The story starts with 12,000 species of ants in colonies dating back 140 million years. Ants organize highways along the shortest path to the nearest food, build elaborate nests and stage massive raids on other creatures. This leads to a conclusion that ants are clever engineers, architects and warriors. Nothing could be further from the truth, according to entomologists. These scientists who study insects point out, "When it comes to deciding what to do next, most ants do not have a clue."

An ant colony can have millions of individuals divided into workers (commonly sterile females), drones (fertile males) and queens (fertile females), none of which have any vision for the colony. Instead, leadership arises from the collective action of the colony, or swarm intelligence. Simple creatures follow simple rules. Each party acts on local information; no one has the big picture.

So how do ants find food? They communicate by touch and smell. Early morning patrols seek food outside the nest. If many come back quickly, they've found food. Foragers go out. If many come back, much food was found. Everybody goes out following a chemical path called a food trail pheromone.

Bees also display swarm intelligence. When selecting a new hive, scouts go out. An individual bee returns and dances with enthusiasm for a specific site. More go out. When a site attracts as few as 15 bees, it becomes the choice. Entomologists report the choice is usually the best among competing sites for the new hive.

A real-life example of swarming theory in risk identification is found in the story of Airbus in my Aug. 20 Emerging Risk Strategies column (BI, Aug. 20; www.BusinessInsurance.com/ERM). Airbus had a Power8 program to deal with exposures affecting the launch of the 800-passenger A380. The risk diagram omitted airport risk. When seven teams of MBA candidates tackled the A380 as an ERM risk identification project, two of the teams discovered airports' lack of readiness to handle such a huge aircraft. These teams added airport risk to the exposures (see Figure 1). Almost immediately, all seven teams "swarmed" by adding the risk to their own list.

Going further back, my April 16 column dealt with the Valentine's Day disruption of operations at New York's John F. Kennedy Airport and the struggles of JetBlue Airways to deal with the aftermath. It is unfortunate that JetBlue did not have a central risk function sharing exposures. Surely some "ant" would have identified a disruption risk at JFK. We might even expect a disruption pheromone that would lead right up to the CEO. A public relations disaster could have been avoided.

ERM did not discover swarm theory. James Surowiecki believes that a diverse collection of individuals making independent assessments provides more accurate forecasts and more successful outcomes than expert decisions and central guidance. Effectively, he describes swarming theory in his 2004 book, "The Wisdom of Crowds."

Companies have discovered it, however. The National Geographic article describes Air Liquide and its effort to find the best routes for delivery by its trucks. It tracked the routes followed by individual drivers and inserted the data into computer model with plant scheduling, weather, market pricing and truck routing. The software "pheromone" resulted in huge savings. Other companies throughout Europe use the process for deliveries and telecommunications networks.

It is time for ERM to incorporate swarm theory into its efforts to improve risk identification. Companies will likely identify and mitigate many exposures if they incorporate the collective wisdom of their "colonies" and "hives."

John J. Hampton is the KPMG Professor of Business and Dean of the School of Professional and Continuing Studies and Graduate Business Programs at St. Peter's College in New Jersey. He specializes in business ethics, legal liability and enterprise risk management. He is a former executive director of RIMS.