The theory that a collective can solve problems better than most individuals within a group, including ‘experts’, has gained attention in recent years. Perhaps the greatest misconception surrounding the theory of the ‘Wisdom of Crowds’ has been that solving any problem using this approach will garner superior results, when in actuality there are specific conditions and situations within which collective problem solving may not be the best approach.
Let’s examine a common scenario:
Company A is planning their annual strategic planning meeting and the President has decided that they want to make the plan a collective decision among representatives of all the departments to ensure that all facets of the organization are taken into consideration. So, equipped with their flipcharts and the 15 participants they go through the process of recording everyone’s input and ideas for strategic components. They split the group into teams, each assigned one of the ideas to drill down into possible tactics for execution, all the while scribing away. By the end of the second day there are 50 flipchart pages composed of the collectives ideas and possible tactics as a take away that the President will now have his assistant type up into a fluid document. From this document of the collectives input the President will now formulate the official strategic plan for Company A.
Why is this not a good example of a ‘Wisdom of Crowds’ approach?
Let’s first talk semantics and some definitions in context:
The Wisdom of Crowds approach depends upon diversity. However, not diversity as it is generally accepted to represent social differences such as culture, age, gender, profession etc. but rather diversity in mental models which define how many approaches a person has to solve a problem. Experts generally know a lot about one thing while other informed but not expert individuals know a little about many things. Therefore, experts tend to use the same mental model (problem solving approach) in most situations and stick to explanations that fall within the realm of their expertise. Informed non-experts on the other hand are more likely to have several mental models and have a greater capacity to examine a problem and make fresh connections while linking together diverse sources of information. This lends itself to the notion that greater accuracy in collective problem solving can be achieved with fewer experts and more informed non-experts in the room.
Diversity at this level is generally only of value if the problem is complex (encompasses many units in a system). If you have an electrical problem it will be of little value to have someone from the accounting department and sales in the room to help solve the problem when all you need is an electrician (an expert). As such, the first step in determining whether a collective is better suited to solve a problem or not is to understand the type of problem you are dealing with.
Should it be determined that the problem is indeed complex and a ‘Wisdom of Crowds’ approach is appropriate, the next necessary condition to make this method work is an accurate and efficient means of aggregation – bringing the groups information together in a useable form. Useable form is the key to this definition. Aggregation in general is ‘collecting units into a whole’, which you need to do but for ‘Wisdom of Crowds’ application the information you aggregate must then be applied to the development of an solution by the collective through polling or voting.