Becoming an analytics-driven educational institution: Setting realistic goals
It seems that anywhere you turn, there are articles, blogs, points of view and so on that exhort the power of data and analytics to improve the way educational institutions can deliver the best learning experience at the most efficient cost. Nearly everyone agrees in the universal power of data and analytics when applied against the many issues that confront educational institutions: student retention and graduation, student intervention, budget and finance, and operations. But how do you begin to use this power effectively?
“We have all this data, so let’s use analytics to measure things.” That statement is a little contrived but the sentiment does exist. Often we hear executives in education utter something similar. The good news is that educational institutions want to start using the vast amounts of data available to drive change and innovation. But the next step usually entails a discussion about which tools can accomplish that objective. Line-of-business executives in education turn to information technology experts to procure the tools to become an analytics-driven institution, using analytics for a comprehensive view of each student. But tools and data only get you so far. The primary focus must be on the outcomes, along with the methods and the analytics strategy required to achieve those outcomes.
The first and most important step in any application of data and analytics is to concentrate on a strategic mission objective; that is, to know the result you want to achieve and how to determine its success. In essence, what is your goal? It can be anything that measures success, from a reduction in attrition to faster response times for students at risk. But what constitutes “success?” One useful approach is based on Peter Drucker’s “management by objectives” concepts to define SMART goals for your mission objectives: specific, measurable, achievable, realistic and timely (Drucker, The Practice of Management, 1954). Educational institutions frequently initiate lofty goals that may not be attainable because goals and objectives are often confused.
For example, executive leadership may say “We want to reduce attrition,” which is not a goal but a strategic objective. However, applying SMART principles to that objective produces a goal that can be measured and acted on: “We want to reduce student attrition among first-year students by 3 percent in year 1, 5 percent in year 2 and 7 percent in year 3.” This goal is specific—reduce student attrition among first-year students—and it is measurable, achievable, realistic and timely: by 3 percent in year 1, 5 percent in year 2 and 8 percent in year 3.
By setting realistic and achievable goals, it is much easier to rally stakeholders around realizing those goals. It’s vital to use data and analytics as a way to measure and monitor progress, using information learned from the process on an ongoing basis to revise the approach to achieving the goal, and not using analytics as a punitive measure against stakeholders. In doing so, stakeholders can embrace the stated goals and work hard to achieve the desired results.
An analytics-driven approach can help colleges and universities become analytics-driven organizations. To see how, visit IBM Analytics for Education.