This brief discusses how digital transformation and analytics technology can improve decision-making in advanced materials research. It outlines common challenges such as paper-based data capture, unstructured datasets, limited collaboration, and siloed information. The document presents best practices for capturing, structuring, and analyzing scientific data using modern platforms like Signals Notebook, Data Factory, and Spotfire. These tools enable rapid search, advanced visualization, machine learning integration, and cross-source data analysis. By adopting digitally driven workflows, organizations can improve research efficiency, accelerate innovation, and better demonstrate the value of R&D outcomes across materials-focused industries.

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