Anyone who's ever attended a Data Cookbook demonstration, or heard us talk about it at a higher education conference, has heard us say this: "Reporting is not a technology problem." While we think that statement is as true today as it was when we first uttered it, it might be true in slightly different ways.
The difficulties organizations have generating and interpreting the reports they need to run their operation come in many flavors, and they have multiple causes. Sometimes the data is incomplete, or contains inaccuracies, or hasn't been collected and stored consistently. Sometimes institutions aren't making very good use of their systems--not taking advantage of some built-in functions, for example. Frequently there aren't enough people involved in the data management process. Even though data integration is a simpler process now than it was a few years ago, the proliferation of systems on campus continues to mean data silos exist. The process for requesting and delivering reports can be cumbersome and slow, and it may have few if any real quality assurance controls.
Just as common, if not even more so, is a lack of substantive communication between data consumers and data producers. Data consumers need certain pieces of information to do their work, but they don't always excel at making clear what they need, or how they'll use it. How many seats are in that class? The on-line course catalog says 25. What classroom is it scheduled for? If it's not scheduled yet, it better be held in a room that's large enough. A proper conversation about this data request can't begin and end with the first question, and in our opinion both data consumers and data providers need to engage the other party fully before signing off.
Even that may not be enough. Maybe there's a new instructor for a course who says she'll teach 30 students, but for years that class has been offered at a time when no more than 22 students have ever signed up for it. Maybe her department has claim to a space that only seats 25, and the process to get a class moved is not widely known. Is that information stored in a data system? Across several? In a procedures document? Is it part of the institutional memory dispersed across aging and possibly soon-to-retire faculty and staff?
These kinds of process and communication problems abound, and they're magnified when we think about their application at an enterprise level. Campus management requires ever more information in order to make decisions about nearly every aspect of the modern college, and those information needs are more complicated and more comprehensive than ever before. (And just because they get the information they request doesn't mean it's the information they needed. There's more data available to decision makers, but no guarantee that they'll interpret it correctly or act on it wisely. But that's a topic for another day.)
When we observe the absence of data quality standards, or an equivocal commitment to data and systems usage, or too few staff stretched too thin, we're generally looking at a failure of data governance. When we observe a lack of communication, or data requests based on untested and unshared assumptions, or insufficient diligence performed by data providers, we're also looking at a failure of data governance (and data intelligence).
The Data Cookbook provides a platform for addressing data governance needs, and a tool set to start harnessing the power of your technology and your personnel. It won't "solve" data governance out of the box, although it can dramatically improve data stewardship and data usage and understanding almost right away. Just as throwing new technologies at reporting didn't solve that problem, simply throwing a new tool at data governance without training, an implementation strategy, and executive support won't do much good either.
For that matter, addressing data governance isn't a magic bullet for better reporting. Robust data governance doesn't automatically lead to improved decision support, more effective operations, or cost savings. There's almost always room to improve a data model, to upgrade a presentation layer, to speed up the production process. The right questions still need to be asked of and about the data, and the most colorful visualization isn't necessarily the one that best conveys the critical information.
But using the Data Cookbook means you can be collaborating more productively, it means you can be sharing organizational knowledge to stakeholders all across campus, it means you can have fewer conversations about data quality and usage and more conversations about metrics and analysis. It means you can start focusing on identifying, asking, and answering those right questions. Reporting and analytics success will require building a better data culture. We believe the Data Cookbook is one of the best tools for building that culture. If you would like to learn more please 
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(image credit StockSnap_Y2AHVPYB51_BuildingDataCulture_BP #1036)
