One of the central tenets of bloomfield knoble is R.U.D.E. (an acronym for Research, Understanding, Design and Execution) – the process by which we help our clients achieve success. While the process remains the same from client to client, the application of the process can vary widely depending on need and circumstance. Take for example, “Research.”
At bloomfield knoble, we are big believers in using focus groups to learn, analyze and test, but it seems that we are rapidly becoming considered “old school” for our method of research. The popular notion among everyone – from agencies to brands – is to utilize social media to harness the “wisdom of the crowd” – the belief that large groups of people can make smart decisions even when poorly informed, because individual errors of judgement based on imperfect information tend to cancel out. To that, we at bloomfield knoble say, “hogwash!” (pardon my language).
A quick primer: the selfishness of humans is a central assumption of orthodox economics, where it is thought to lead to benefits for the economy as a whole. It is what 18th-century Scottish economist Adam Smith described as the “invisible hand.” For simplicity’s sake, orthodox economics assumes that people making a fundamental decision (such as whether to buy or sell something), have access to all relevant information. If the price is too high, then because we’re rational and self-interested, we don’t buy and the price falls. The general idea is that, eventually, supply equals demand. Well, it turns out that people aren’t rational, because people (like me) will pay some ridiculous amount for an old vinyl album that they loved as a kid – pretty much regardless of price.
That’s just one silly example, but it is correct to present that in addition to not being rational, humans don’t always have accurate information and certainly don’t act in isolation. We learn from each other, and what we value, buy and invest in is strongly influenced by our beliefs and cultural norms, which themselves change over time and space. Over the years, there have been various attempts to inject more realism into the field by incorporating insights into how humans actually behave. This is known as behavioral economics and works great when attempting to understand how individuals and small groups make economic decisions. This, most recently, has been the area of “nudge” – persuading people into doing what’s best by subtly influencing behavior. Unfortunately, the complexities of behavioral economics make it too unwieldy to be applied across the board.
According to a great article in New Scientist by Kate Douglas, it turns out that humans adapt our decisions according to the situation, which in turn changes the situations faced by others, and so on. The stability or instability of financial markets, for example, depends to a great extent on traders, whose strategies vary according to what they expect to be most profitable at any one time. According to Alan Kirman, an economist at the School for Advanced Studies in the Social Sciences in Paris, France, “The economy should be considered as a complex adaptive system in which agents constantly react to, influence and are influenced by the other individuals in the economy.”
This is where biologists might help. Some researchers are used to exploring the nature and functions of complex interactions between networks of individuals as part of their attempts to understand swarms of locusts, termite colonies or entire ecosystems. Their work has provided insights into how information spreads within groups and how that influences consensus decision-making, says Iain Cousin from the Max Planck Institute for Ornithology in Konstanz, Germany.
It is this new research approach that may change the way agencies and brands approach gathering information. Remember, in orthodox economics, the wisdom of the crowd helps to determine the prices of assets and ensures that markets function efficiently. “This is often misplaced,” says Cousin. By creating a computer model based on how animals make consensus decisions, Cousin and his colleagues showed last year that the wisdom of the crowd works only under certain conditions – and that contrary to popular belief, small groups with access to many sources of information tend to make the best decisions. According to their abstract:
Individuals in groups, whether composed of humans or other animal species, often make important decisions collectively, including avoiding predators, selecting a direction in which to migrate and electing political leaders. Theoretical and empirical work suggests that collective decisions can be more accurate than individual decisions, a phenomenon known as the ‘wisdom of crowds.’ In these previous studies, it has been assumed that individuals make independent estimates based on a single environmental cue. In the real world, however, most cues exhibit some spatial and temporal correlation, and consequently, the sensory information that near neighbours detect will also be, to some degree, correlated. Furthermore, it may be rare for an environment to contain only a single informative cue, with multiple cues being the norm.
We demonstrate, using two simple models, that taking this natural complexity into account considerably alters the relationship between group size and decision-making accuracy. In only a minority of environments do we observe the typical wisdom of crowds phenomenon (whereby collective accuracy increases monotonically with group size). When the wisdom of crowds is not observed, we find that a finite, and often small, group size maximizes decision accuracy. We reveal that, counterintuitively, it is the noise inherent in these small groups that enhances their accuracy, allowing individuals in such groups to avoid the detrimental effects of correlated information while exploiting the benefits of collective decision-making. Our results demonstrate that the conventional view of the wisdom of crowds may not be informative in complex and realistic environments, and that being in small groups can maximize decision accuracy across many contexts.
That’s because the individual decisions that make up the consensus are based on two types of environmental cue: those to which the entire group are exposed – known as high-correlation cues – and those that only some individuals see, or low-correlation cues. Cousin found that in larger groups, the information known by all members drowns out that which only a few individuals noticed. So if the widely known information is unreliable, larger groups make poor decisions. Smaller groups, on the other hand, still make good decisions because they rely on a greater diversity of information.
Now, I realize that I am making a bit of a stretch here. A focus group about consumer packaged goods isn’t the same as financial modeling for the Greek economy, but it does highlight the need to better understand who has what information and how to prevent over-reliance on highly correlated information, which can compromise collective intelligence. Operating in a series of smaller groups may help prevent decision-makers from indulging their natural tendency to follow the pack. Here’s a quick test for you: how many “influencers” do you follow on LinkedIn? LinkedIn even makes suggestions on who to follow and rewards people that drive action with special “influencer” badges. Information passed on to followers are perceived to have already been “vetted” or “approved,” which may actually minimize the amount of research an individual will perform.
There isn’t much argument among agencies that research is important – it’s the approach to the research that seems to be a matter of some debate. Those who would hold up research models that show vast numbers of followers on social media love “Creative A” better than “Creative B” may not be any more accurate than those who tout the results of a focus group between 8 and 12 people. Regardless, there is one thing that Adam Smith taught that holds true for agency economics – get it wrong and you’re fired! So maybe there is still something to be said for orthodox economics in advertising after all.