An experimental multi-model approach to instrument the sensemaking process at the team-level

Abstract

Just like Julius Caesar’s Gaul, any engineering challenge can be divided into three parts; (1) the problem, (2) solution and (3) design spaces. The interaction between solution and design, and the degree of influence that any given team has upon them will depend on the capacity of said team to make sense of the problem. This thesis presents a framework to evaluate the process of team-level sensemaking. How a small group of individuals show emotion, converse with each other and interact with the engineering problem at hand. This integrated view is tested with a small-n experiment to demonstrate the possible insights and data that can be generated and analyzed. As a contribution to collective intelligence and teamwork, the ability to objectively judge a team’s performance —via Pareto Ranks, measure the conversation dynamics —using graph theory and voice recognition, assessing the average emotion content displayed by the team members —using facial recognition, and estimating team entanglement —with physiological signals captured by smartwatches, gives a deep dive into each team’s sensemaking process.

Pending reproduction of the experiment, this first iteration seems to indicate that emotions play a role in a team’s motivation to perform, as does the timing of the conversations the team has. Also, there are heuristics that emerged from the teams when they had to judge which of their proposed in-game designs was better —even though none of them actually met the requirements.

The work presented in this thesis is the enactment of one specific sensemaking framework: Weick’s seven properties. Applied to a bounded system, where the problem under analysis is fully understood and the teams operate in game-bubble, where they all have access to the same —yet purposefully limited— information. And just like the participants in this experiment, this thesis might not have crossed the finish line set by the goals, but it certainly moved closer to it.