When Campus Technology conducted a virtual roundtable with higher education IT leaders, the top ed tech trend to watch was data-driven decision-making. Participants in the roundtable pointed out that schools must have a data management strategy that prioritizes data standardization, integration, transparency, quality and reliability. This is critical if institutions expect to take full advantage of big data, spur innovation in teaching and learning, and make the most of their resources.
Data-driven decision-making, as the phrase suggests, values and prioritizes decisions supported by high-quality, verifiable data that has been effectively processed and analyzed. This used to require the assistance of an IT specialist to create and interpret reports. However, modern analytics tools are intelligent and user-friendly, enabling virtually any user to run custom reports, which are then visualized in a way that’s easy to understand.
Technology plays a critical role in virtually all operational processes, and the data produced by that technology can create a number of competitive advantages for colleges and universities. While instinct and experience are important, institutions that employ data-driven decision-making gain deeper insights into the needs of students, faculty and the institution as a whole. Data can also be used prove, disprove and test decisions that have been made based on instinct.
There are a number of ways data-driven decision-making can benefit higher ed. Data helps schools identify at-risk students and provide the right kind of assistance at the right time to improve retention and success rates. Instead of chasing shiny, new objects, schools can use data-driven decision-making to make smarter, more informed investments in new teaching and learning models and technology. Data empowers schools to identify new or missed opportunities, respond quickly and confidently to new market conditions and evolving student needs, and roll out new, innovative services.
At the same time, data is not foolproof, and not all data-driven decisions are good ones. Data-driven decision-making only works if you use the right data, the right metrics and the right analytical approach. Where did your data come from? Could there be variables you hadn’t considered that could be affecting the results of your analysis? Have you tested your assumptions against different sets of results? All these factors will affect the quality of your decisions.
The key to maximizing the benefits and avoiding the pitfalls is the successful implementation of a data-driven decision-making strategy. Before you even look at data, you need to identify the questions you want your data to answer, and what goals you want to achieve by answering those questions. Data could could be coming from thousands of sources, so you need to determine which data sets are most valuable and relevant to your goals in different areas – recruitment, student success, fundraising, administrative operations, etc. Identify those individuals who will be responsible for collecting, managing and analyzing your data. Look for an analytics tool that’s capable of running the appropriate queries and processing the desired metrics.
Data-driven decision-making is a discipline that’s difficult if not impossible to master when your data is stored in disparate systems that can’t communicate with each other. Axiom Elite integrates and validates data from internal and external sources, and can automate decisions by applying your business logic to the data. Let us show you how Axiom Elite enables simpler data management and analysis.Return To Blog