Community member post by Christian Schunn
What is an analogy? How can analogies be used to work productively across disciplines in teams?
We know from the pioneering work of Kevin Dunbar (1995), in studying molecular biology labs, that analogies were a key factor in why multidisciplinary labs were much more successful than labs composed of many researchers from the same backgrounds. What is it about analogies that assists multi- and interdisciplinary work?
The advice that follows comes from a decade of research involving intensive analyses of hundreds of hours of interdisciplinary science and engineering teams, following the minute-by-minute processes of the teams, and using advanced statistical techniques to look for robust patterns in behavior over time and across teams. In general, our research has shown that creative teams generate twice as many ideas per unit time when they use analogies than when they do not.
So, what is an analogy? It is the accessing and transferring of elements from familiar categories or situations to the current problem. We all use analogies such as: ‘works like magic’, ‘stinks like a rotten egg’, or ‘hit-or-miss like a risqué joke’.
These prior situations might be a comparison to a relatively similar past experience of the team member, or might involve referencing experiences from a vastly different technical or everyday situation. As an example in the context of engineering, a team member raised the following analogy to an everyday experience in designing an unsupported tube to transport liquid: “the stuff you make Venetian blinds of for example… they can be bent.”
Note that analogy is a cognitive process in which the problem solvers reason through the relationship between the prior experience and the current problem. The reasoning process produces a number of inferences for the team that can serve many purposes. Analogies can help brainstorming sessions by:
- Generating new solutions
- Identifying likely problems that weren’t yet raised
- Finding additional functions that can be exploited, and
- Explaining ideas across the team
When a team needs to resolve uncertainties without a clear way forward, raising new analogies can bring possible solutions.
Productive use of analogies is useful for stimulating both divergent and convergent thinking processes and can combat two major team problems, those of group think and confirmation bias. On the divergent side, group think is getting stuck on a shared mediocre idea, instead of harnessing the breadth of knowledge in the team. On the convergent side, confirmation bias is preferring evidence in favor of the current plan, and failing to seek evidence that different team members have access to that points to flaws in the current favored plan.
Analogies can also reduce the fixation effects of starting with a non-functional prior solution. Even expert designers will fixate when given an example of what a solution should not do, but the harm is erased when designers are given a range of analogies to consider.
Analogies can produce disagreements among team members in several productive ways, for example about the aptness of the analogy at all, the way the analogy applies to the current situation, and whether inferences can be used. In our research this effect was found for productive kinds of disagreements (disagreements about the task and processes to be used), and not for the unproductive kind of disagreement (conflicts of personality or personal attacks).
Interestingly, the physical environment surrounding the team can also influence how often teams use analogies. Looking at highly detailed artifacts (e.g., prototypes or models) appears to suppress the rate of analogizing relative to having an open conversation or looking at more abstract sketches. Of course, getting very concrete and detail-oriented has an important place in teamwork, especially multidisciplinary teamwork. But there is a time and a place for it, and it can be helpful to put away the physical artifacts from time to time.
What have your experiences been with analogies? Can you provide additional examples of how they have been helpful?
Reference and related papers
Ball, L. J. and Christensen, B. T. (2009). Analogical reasoning and mental simulation in design: Two strategies linked to uncertainty resolution. Design Studies, 30, 2: 169–186.
Chan, J. and Schunn, C. D. (2015). The impact of analogies on creative concept generation: Lessons from an in-vivo study in engineering design. Cognitive Science, 39, 1: 126-155.
Chan, J., Dow, S. P. and Schunn, C. D. (2015). Do the best design ideas (really) come from conceptually distant sources of inspiration? Design Studies, 36: 31-58.
Christensen, B. T. and Schunn, C. D. (2007). The relationship of analogical distance to analogical function and pre-inventive structure: The case of engineering design. Memory & Cognition, 35, 1: 29-38.
Dunbar, K. (1995). How scientists really reason: Scientific reasoning in real-world laboratories. In R. J. Sternberg and J. Davidson (Eds.). Mechanisms of insight. MIT Press: Cambridge, Massachusetts, Untied States of America, pp: 365-395.
Linsey, J., Tseng, I., Fu, K., Cagan, J., Wood, K. and Schunn, C. D. (2010). A study of design fixation, its mitigation and perception in engineering design faculty. Journal of Mechanical Design, 132, 4: 041003.
Paletz, S. B. F., Schunn, C. D. and Kim, K. (2013). The interplay of conflict and analogy in multidisciplinary teams. Cognition, 126, 1: 1-19.
Biography: Christian Schunn is a Senior Scientist at the Learning Research and Development Center and a Professor of Psychology, Learning Sciences and Policy, and Intelligent Systems at the University of Pittsburgh. He directs a number of research projects studying expert engineering and science teams and the effects of new tools designed to increase innovation. He also leads research projects that apply this knowledge to building innovative technology-supported STEM curricula, and studying factors that influence student and teacher STEM learning.