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Big data, predictive modeling, machine learning, and artificial intelligence are all the buzz. From business to athletics to healthcare to education, more and more people are using more and more data strategies, technologies, and tools to achieve their diverse missions. However, as leaders in each sector moved to use more data, they had to make a another more important move to make a real difference. The move mattered, the move was material, and the move is hard. It’s the move from a data culture that focuses first on performance reporting to one that is obsessed with using data to inform, inspire, and impact the main thing first. In one sector the main thing is delighting customers, which might mean using data to make real-time shopping recommendations or up-to-the-minute traffic projections. In others it is saving lives and improving health, which could mean encouraging patients to use a MyChart app for chronic disease management or a FitBit to optimize wellness. Regardless, each sector found that the traditional data orientation that obsesses over performance reporting and dashboards isn’t enough. To be sure, performance measurement is important, often existential because of funding, but it usually doesn’t drive the dramatic improvement you’re looking for until you make the move to aim data at the main thing first. The world of education is beginning to make this move. Over the last decade, colleges and universities have been diving deep into advanced analytics to help more students succeed. Indeed, Civitas Learning was founded on the promise of pulling together data science, design thinking, and dedicated educators to make a difference in student success. As this work continues, making the move from a data culture focused first on performance reporting—in our case IPEDS, accreditation reports, board updates, and administrator KPIs—to our “main thing” is clearly happening. Our main thing is helping students make the most of their learning journeys, helping them learn well and finish strong, and adopting a culture of care with our students. A culture of care means caring enough to turn on your own lights to see what’s happening at your own institution, and what’s likely to happen, in close-to-real time. Best-practice benchmarking and last year’s reports are important, but toaday’s student trajectories can be impacted in ways yesterday’s student outcomes cannot. Moreover, this move means caring enough to share the data with professionals across the institutions—advisors, faculty, peer mentors, and the students themselves–so they can use the data to make a difference in the moment or on the road ahead. Finally, it means caring enough to use these live and predictive data to inform, design, and measure the impact of the interventions, inspirations, and initiatives we undertake. From advisor apps to class scheduling tools to student nudges to emergency aid to classroom engagement tools to guided pathways, the variety of our “culture of care” work is ever expanding. In this podcast, Dr. Pete Smith, the Chief Analytics Officer at the University of Texas at Arlington–a title that bespeaks the importance of this move–unpacks the significant challenges and real opportunities around making the move to a culture of care. His institution still takes performance reporting seriously. However, they have embraced the insight from their adjacent sectors (indeed, Pete is a big baseball fan) that to improve the outcomes on these reports, data work should be focused first on a culture of care obsessed with our main thing: helping more, and more diverse students learn well and finish strong. From new organizational and reporting strategies, to new technologies, to deep culture work, this move is far from easy. But hearing from one of these first movers is compelling. Take a listen!