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The current trend in higher education is to attempt to leverage “predictive analytics” in order to operate more efficiently in the areas of recruiting, retention, alumni engagement for fundraising, or simple cost management. The danger in trying to predict an institutional future comes when your models are based on data that has inadvertent blind spots. These can be the result of not paying sufficient attention to historical trends. By only focusing on the flashy, new buzzwords of “disruption” and “personalization” universities and colleges run the risk of overlooking the issues that this new analytical tool was meant to resolve in the first place. While the initial impulse may be to rush to apply the new metrics to existing challenges, a slower, more deliberate approach to formulating which questions need to be answered can be significantly more productive. Once you have accurately measured past performance, and understand that predictive analytics are more of a final step than a starting point, you can then confidently apply that to planning for the future.