At Othot we’ve been talking for a long time about the opportunities for predictive analytics in education– from K12 to college programs. Once or twice we’ve discussed the multiple applications such as enrollment optimization, student retention, grants and tuition management, etc. You’re most likely convinced by now that Big Data and academia are ultra-compatible. So, are you ready to embrace analytics? Because, you should be.
Big Data is as pivotal for education as it is any other industry. However, while other industries are making moves to adopt and integrate predictive analytics as a strategic asset, education is still lagging. Recently, EdTech published findings from a survey that found less than a third of the higher education industry has sufficient data and the resources to analyze it and make decisions. Of those that do have those resources, most still fail to properly use the insights to make decisions. Furthermore, those that fail, fail for a number of reasons. Data is spread across operating functions, quality is poor, or they need better, more advanced analytics techniques. Higher education CIOs list “BI and analytics” as one of the Top 10 IT issues facing higher education, but also state that: “Big data is useless unless it is hygienic and organized. I see a lot of wasted investment on BI and analytics tools because data is fractured and messy.” Fractured and messy, like most of higher education’s foray into analytics so far. Bottom line: only 41% of colleges use data analytics in some way, and in many ways, the current usage is inadequate.
The story goes about the same for K12 education: plenty of data and a plethora of much-needed applications of analytics, but little momentum. States have received $600 million in funding to establish student databases over the past ten years, but little is being done with this data, and though some find success with predictive analytics, “such initiatives have mostly resulted in small pockets of innovation or incremental shifts to existing practices, rather than systemic transformation.” Houghton Mifflin Harcourt, major textbook publisher, urged that the “time was right” for predictive analytics in K12 back in 2013. Missteps and bottlenecks have caused delays in adoption because teachers are slow to change their ways, data integration is too difficult for districts, among other reasons. So here we are in 2016, with not very much progress.
I will say- for those that have tried and failed-at least an attempt was made. Predictive analytics is a daunting technological monster to try and tackle, especially on your own. But for those that have never tried, that’s akin to having life hand you an endless supply of the most delicious lemons, but never attempting to make lemonade. Get a good recipe and a powerful juicing machine, and you’re set. Here are a few things to remember going forward:
- Big Data doesn’t have to be BIG. Higher education CIOs also state: “Better small, clean, good data than a big, bad mess. CIOs need to establish a clean data baseline first; this will allow faster innovation and iteration into quality BI and analytics.” Sound advice. Quality > quantity here: massive data sets are no better than smaller data sets that are more meaningful to your strategic goals.
- You don’t have to do it all at once. Sure, it would be amazing to take on recruitment, enrollment, retention, AND financial aid issues all at once– but that is a lot of resources to commit. If your resources are limited, go after what makes the most sense for your institution. Stay focused on your High Impact Question™, or HIQ™, as we say at Othot.
- You don’t have to do it all yourself. Everyone needs predictive analytics, but that doesn’t mean everyone needs to make data science a core competency. There is a myriad of sophisticated tools to process, analyze, and visualize your data. Even better, there are companies (like Othot) that will handle the technical side of predictive analytics and provide insightful answers to your most impactful business questions– helping you to shape the future of your school or university (without all the hassle).
With the right data, tools, and strategy, the next few years will bring major changes to the education industry if decision-makers are willing to seize the opportunity. Life’s already given those lemons- it’s about time to open that lemonade stand.