Ã‚Â© 2007 Mark David Milliron
EDUCAUSE Review, vol. 42, no. 2 (March/April 2007): 68–69
Mark David Milliron serves as Suanne Davis Roueche Endowed Fellow, Senior Lecturer, and Director of the National Institute for Staff and Organizational Development (http://www.nisod.org) in the College of Education at the University of Texas at Austin. Comments on this article can be sent to the author at email@example.com and/or can be posted to the Web via the link at the bottom of this page.
Much like the larger corporate world, the education field has been on a journey of transformation over the past twenty-five years. In fact, some in the field have called A Nation at Risk, the 1983 report from the U.S. Department of Education, a shot across the bow to educators nationally and internationally. The authors of the report boldly claimed that the United States was suffering from a "rising tide of mediocrity" that threatened to make the country a nonplayer in an increasingly connected, knowledge-driven world. The report set off reform efforts galore at all levels of education. Soon educators began borrowing business change strategies. They went "in search of excellence" and became enamored with MBO, TQM, CQI, reengineering, Peter Senge's learning organizations, and Margaret Wheatley's chaos theory.
What happened next across education, business, healthcare, and government in the roaring 1990s was an intoxicated embrace of technology initiatives—particularly the use of the Internet—as the dominant driver of change. These efforts were spurred on by high-flying stocks, hyperbolic pundits, and more broadly attractive and useful technology. Alan Greenspan, the U.S. Federal Reserve chairman, referred to this as the time of "irrational exuberance." He warned that the oversized bubble of energy and capital—expanding with little thought to implications, cautions, or complicating factors—would most naturally burst. Indeed, it's clear now that many business leaders forgot that a little thing called profit still mattered. Meanwhile, many educators began to lose sight of their version of profit: learning.
I have referred to this time as the age of the "Techno-CroMagnon Theory." Whether led by a businessperson, chief medical officer, principal, or college president, many reform initiatives were based on an amazingly simple, almost primal assumption: "technology = good." The basic assumption was that the technology would almost magically drive business, transform medicine, and improve learning. The billions of dollars spent on hardware, software, and systems integration would somehow help us progress to a "new economy" or to "new learning." Correspondingly, across business and education, technology leaders increasingly moved from "the basement to the boardroom"—from serving ancillary support functions to sitting as key players at the table, driving operations and strategy.
What the dot-com boom provided next was a healthy dose of reality therapy: the dot-com bust. Seven trillion dollars evaporated from the stock market, companies closed, and venture capital dried up. The bust, though devastating to some, didn't sour most of us on technology. It actually had the helpful effect of moving us into a state of rational exuberance. We realized it wasn't that technology couldn't help. It was that the underlying assumption was wrong: technology is neither good nor bad. It is our use of technology tools—within our contexts and toward specific ends—that can make a difference. This idea is the foundation on which today's insight initiatives are built.
Insight initiatives are known by other names in other sectors: business intelligence, in the corporate world; evidence-based medicine, in healthcare. These efforts, which combine explorations of information from the past (hindsight) with looks to the future (foresight), come together in a moment of insight to power decisions that make a positive difference. These initiatives leverage technology, planning, research, strategy, and a host of other key elements to truly realize the treasure of student and institutional data at our fingertips.
Insight Initiatives on the Rise
Sitting with a group of CIOs at an Information Technology Association of America (ITAA) dinner meeting in late 2005, I heard different versions of the above story recounted by technology leaders from consulting companies, retailers, software companies, and educational institutions. Each was seeing the rise of insight initiatives as the sea change in the use of technology, as a move toward true information technology. They all were bringing together strategic planning, market research, operations analysis, customer relationship management, supply chain management, internal learning efforts, and cutting-edge technologies in ways they never had before. The questions driving these couplings were: What can we learn from the information within our various and often siloed technology systems about what really makes a difference? Can we glean insights from the past (e.g., data mining) and perspectives on the future (e.g., predictive analytics) to better inform decisions today?
Compelling examples of these insight initiatives are everywhere. Take, for example, an often-heard refrain in education: "Our students have Amazon.com expectations." What this is referring to is the almost instant insight that Amazon leverages in the consumer experience. When someone orders a book—even during the process of ordering a book—Amazon.com leverages data-mining and predictive analytics to show what "other people who ordered this book also ordered." The newer version of this analytically fueled predictive service can be seen in iTunes (which features a "just for you" section) and TiVo (which fills your hard drive with TV programs it thinks you'll like).
Banks too are shaping our expectations with their insight efforts. For example, a little over a year ago, my wife, Julia, received a call from a representative of her bank. The man asked, "Have you lost your credit card?" She didn't think she had, but he asked her to check. Sure enough, her card was missing. Her first question was, "How did you know?" What she soon discovered, from the nice man who told her he was sitting in a call center in India, was that she had left her card at a coffee shop three hours earlier, someone had taken the card, and that person had proceeded to buy gas from a station located within five miles of our house. However, it was a station at which my wife had never bought gas: this was the first trigger. Then the person bought an amount of gas—$5—that set off the second trigger. Julia owns a Chevy Suburban, and I often tease her that it takes $600 to fill up the tank. Once the second trigger was flagged, my wife was called to check whether it was her using the card. Sure enough, it wasn't, and the card was cancelled.
Think about this scenario and the expectations it drives. Using insight drawn from fraud analytics, a bank with millions of customers was able to flag the fraud, engage a call center halfway around the world, have someone call my wife and confirm the fraud, and then cancel the card—all within three hours. Just ten years ago, this process might have taken months or years. Worse yet, usually the customer was the one who discovered the violation and often had to pay for it, literally and figuratively.
Insight Initiatives in Education
Examples of these kinds of initiatives in education are just beginning to emerge. Access to analytics, improved data systems, and increased outcomes transparency are key recommendations in the recent Spellings Commission report, A Test of Leadership: Charting the Future of U.S. Higher Education. One of Spellings's strongest supporters, Katie Haycock and the Education Trust, launched the College Results Online (http://www.collegeresults.org) Web site to show what could be done with publicly available data.
Other, more exciting initiatives are also being driven by institutions and groups of institutions. My personal favorite is the Achieving the Dream project (http://www.achievingthedream.org), funded by the Lumina Foundation and a host of partners. Close to fifty community colleges serving high-risk students are working together, using common data definitions and analytic tools, to try to improve student access and success. Their early results are compelling.
Just think of the possibilities here: (1) being able to use trigger analytics to know when a student is about to drop out (not that he or she already has, but is about to) and which intervention would be optimal; (2) being able to leverage predictive analytics to tell a student, "Learners like you who've had this problem in calculus have found this learning object useful"; or (3) being able to dive deep into the data surrounding innovative new media and see what the potential outcomes might be. People working in recruiting, fundraising, retention, finance, and most of all, teaching and learning are all waiting in the wings for these insight initiatives to take root. Most important, however, students are waiting to finally have a very important question answered: "Can you use information about me . . . to help me?"
I'm expecting that these insight initiatives, in partnership with new teaching and learning technologies, will make the biggest difference yet in the transformation of our educational systems. At the very least, we'll have a better understanding of what works, what doesn't, and what's on the road ahead. Yes, we'll wrestle with privacy concerns, technology tools, and organizational cultural transitions (the hardest part). But in the end, this is an opportunity to couple technology with our deep and rich experience in order to gain far better insights into the value of our initiatives, programs, and strategies for our students. And serving, engaging, and inspiring students on their learning journeys is what it's all about.