Innovation is a key driver of socio-economic development, often assessed through quantitative indicators. Such evaluations can unintentionally impose normative biases by favoring what has been successful in the past. This manuscript presents Multiverse Analysis as a framework to address uncertainty in the parametrization of bibliometric indicators. Two case studies are discussed: the Disruption Index, which measures technological novelty, and Disciplinary Diversity, which evaluates interdisciplinarity. Results show that small parametric changes can significantly alter outcomes, raising concerns about the objectivity of performance assessments. MA enhances transparency and helps identify where theoretical improvements are most needed.