Many businesses fail to merge and analyze data effectively. When data are merged from diverse independent sources across a business—something that is now practical and inexpensive—it becomes possible to conduct rigorous pretest-posttest comparisons of complex datasets with a precision, speed, and breadth that have not been practical until now. This article describes a method for merging independent datasets and using the compiled data to run informative quantitative analyses that facilitate sound decision-making. This approach can help support several critical tasks in evidence-based management: documenting changes in the corporate culture; measuring linkages between “soft” perceptual variables and “hard” performance metrics; conducting rigorous pretest-posttest comparisons; and evaluating program effectiveness.
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