Under what circumstances do organizations’ use of quantitative tools in the innovation process increase innovative performance? Some argue that quantitative decision-making in organizations increases innovative performance by correcting poor or biased assumptions, while others argue that it dampens innovation by increasing the salience of measurable incremental outcomes. I propose that reconciling these perspectives requires distinguishing between the tools themselves and the epistemic culture (i.e. norms of legitimate knowledge production) of the organization in which the tools are used. I highlight two dimensions of epistemic culture: content and consensus. I argue that, all else equal, an organizational culture that uses more quantitative tools (i.e., high quantitative content) will be more likely to produce breakthrough innovations due to increased information about market opportunities. But, when organizations form high consensus about the exclusive legitimacy of a small set of quantitative tools, their view of the market is constrained to existing product dimensions that more amenable to analysis with those tools, making them less likely to produce breakthrough innovations. To test these arguments, I use computational linguistics to construct time-varying measures of epistemic culture at more than 100 large consumer packaged goods (CPG) firms using employee resume data. The results are consistent with the theoretical argument, suggesting that the firms most likely to produce breakthrough innovations do not eschew quantitative tools, but rather use them as one tool in a diverse epistemic toolkit.
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