Connect the Dots

This model of opportunity recognition follows in the tradition of rich frameworks that explain how entrepreneurs identify promising opportunities. Whereas Shane (2000) points to prior education and experience as the primary drivers of opportunity recognition, Baron (2006) incorporates a host of cognitive filters and frameworks through which external events, changes, and trends are interpreted and possibly incorporated into prototypes, new models, or simply new ideas.

Baron's model also incorporates "competing" functions of alertness and search. Those of you who have tried to teach these constructs in the classroom may have struggled to differentiate the two. In the game I describe on this page I show how gamification can be used to create a card game that addresses the major constructs of this rich model. The component of iterative card selection during game play tangibly illustrates differences between alertness and search, which become more obvious during reflective discussion at the end of each turn.

Conceptual Model of the Game

The cognitive frameworks are the experiences, skills, mental models, and heuristics we use to recognize, evaluate, and catalog external events, changes, and trends. I teach creativity techniques such as lateral thinking (e.g., de Bono, 1970, 1985, 1996, 2015, 2017), analogical and metaphorical thinking, SCAMMPER (substitute, combine, amplify, modify, magnify, put to other uses, eliminate, rearrange; e.g., Eberle, 1996; Michalko, 1991; Osborn, 1993; with a discussion of training implementation by Poon, Au, Tong, & Lau, 2014) methodology, attribute listing, and other forms of ideation prior to using this activity, so this teaching becomes part of their cognitive frameworks. (I have tried this game with students whom I have not trained in creativity techniques, and the ideas become pretty superficial). These learned creativity techniques should be considered part of a person's abilities to summon prototypes, exemplars, or other novel mental artifacts.

Alertness and Search represent types of "investments" in the "dots" of external information. In terms of incorporating these activities into the game, I consider an alertness approach as one where participants choose cards randomly to try to piece those disparate dots together based on their creative abilities. When a participant has experience in a particular domain, or has selected an initial card that suggests that domain is promising for further information, s/he is considered to be engaged in active search. For example, in the MVP deck pictured above, if a person has deep domain knowledge in sports and entertainment, she might decide to search for promising information solely from that card deck. In contrast, a person (such as a typical undergrad; sorry, y'all) might not have deep domain experience or knowledge and might decide to select randomly from multiple categories.

The perceived patterns in events, trends, and changes represent the connecting of the dots. More dots (as in more cards) represent a higher potential for inputs for promising ideas; simulating this in the game could take multiple turns that could slow down game play, but could be used to illustrate differences from fast versus slow connecting (see Kahneman, 2011, for a new layer of experience and experimentation).

Game play can involve each player using a full deck of cards or using one deck for all players. After running game play under both conditions I concluded that it's probably more useful for learning to provide each player with her own deck of cards. Why? Because at the end of a turn of multiple card drawing rounds, more than one player might have drawn the same card; the discussion and reflections can become much richer if two players offer different perspectives on the information they derived from a particular game card.