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The Data-Informed Institution

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Content elements: › How education is using data for digital transformation › The mission and business value of data › Data, adaptability, and agility › Agility for data - 6 steps › How can we use data to bring adaptability to our institution? › In closing › About the author Data, adaptability, and agility Value is created not just by the data per se but also by the tools and processes in place to analyze it and produce those mission outcomes. In today's digital world, fraught with rapid change, uncertainty, and complexity—disruption, you might say—organizations in all industries need to use data to support organizational agility and to respond quickly and flexibly to changing circumstances. Agility is what lets organizations turn this rapid change and disruption into opportunity. Private and public sector enterprises in the digital age have learned that they can innovate and keep pace with the times through fast delivery of IT capabilities, which are then evolved and improved through multiple rounds of iteration. The last few years have brought techniques for building agility into the IT delivery process, including agile software development, DevOps, and Lean software development. The cloud has been used to speed up the delivery of IT capabilities, for both software and hardware. Team-based organizational structures have made it possible to mobilize the resources to meet changing needs. All of these developments have helped enterprises make their processes more agile. But agile processes are only one part of the story: It is this ability to use data flexibly—to make it available for new uses that we don't know about in advance—that is the missing link in achieving enterprise agility and distinguishes the adaptable organization from one that has merely adopted the frameworks and trappings of agile models. Business and mission agility require data agility. A data-savvy, data-informed institution is a master of both. This focus on bringing agility to data is new. As long as data was only operational, we could lock it away in highly structured databases whose structure reflected the way it would be used for those operational transactions. Our tools were relational database systems such as Oracle or SQL Server, whose strengths are in transactional processing. We used the data to conduct the transactions themselves—registration, enrollments, etc.—and to produce compliance and operational reports. The organization's data itself must also be agile. It must be easily available for uses that are unexpected and constantly changing. It must be accessible and meaningful. Faculty and staff must have tools easily available to work with the data and the skills to do so. 5

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