Schauer: InsightMatrix

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Seeing the trends and patterns within diverse sets of research data can introduce new, innovative, and otherwise unrecognized opportunities to innovation teams. The InsightMatrix makes finding and understanding these patterns possible and simple.

There is a lack of supportive tools for teams charged with the extract innovative insights from research data. The existing tools are either too simplistic (e.g., spreadsheets, word processing software, and other “list management” tools) or too technical (e.g., data mining and OLAP tools), and most aren't intended to support the diverse types of qualitative data that come from customer research.

In response, the InsightMatrix was created as a robust analytical software tool for innovation teams who need support in generating defensible, compelling insights using qualitative — and in some cases quantitative — research data. Unlike basic spreadsheets or high-end data-mining and OLAP tools, InsightMatrix can recognize and visualize patterns of correlation between varying types of data sets, can foster inductive reasoning to support the extraction of higher-level insights, and can be operated by anyone with rudimentary spreadsheet skills.





		To extract higher level relationships the InsightMatrix sorts the rows and columns of data using statistical algorithms to reveal meaningful groupings of list items. The InsightMatrix can assist users in delineating the most significant groupings. Other functionality allows quantitative data to be associated with each row and grouping. This kitchen data example is very simple, but the InsightMatrix is capable of evaluating any lists of anysize.

Advisor and pioneer: Vijay Kumar
For more on the statistical theory behind the InsightMatrix, see Jacques Bertin and Permutable Matrix