Universities handle a large amount of data to operate. This information plays a fundamental role in decision-making. The question is, are they using data efficiently? Are they prepared to interpret them and make informed decisions?

A strategic viewpoint based on data optimization can show the true value of this information when it comes to making a university more innovative and competitive. We will explain how and why an institution can achieve these results.

Fact-based Decision Making

A range of factors will affect Higher Education institutions in the upcoming years in terms of using Data Science,  according to a study by the Education Advisory Board:

The two large effects include:

• Changes in population characteristics will lead to a decrease in the number of students.
• Budget cuts and changes to financing models will bring forth new challenges when it comes to distributing resources and creating effective strategies to ensure teaching quality does not diminish.

Technology will not be left out of solution creation for handling these and other challenges. With the development of data extraction practices and techniques, or Data Science, Higher Education institutions are now using customized algorithms capable of learning from the information they produce to uncover problems and develop strategies.

Nevertheless, as a function of the number of students, departments, personnel and courses on offer, an educational institution are already generating large amounts of raw data that are stored online and not used any further.

This is called Big Data. This information is so dense that not just any data analysis software can process it. New analytical tools are being developed to transform and optimize the data, since in some cases it could be incomplete or illegible.

Why is data use important?

In practice, Data Science tools and methods use these data and convert them into a source of solutions.

Efficient administration of this knowledge will bring an end to a management style based on notions or assumptions about what is going on within a degree program, faculty or university, all of which are insufficient for making optimal decisions.

What’s more, this can make an organization less competitive because decisions based on intuition risk resulting in inefficient course allocation when employing a blind strategy in a context comprised of multiple perspectives in terms of the results that university staff need to achieve.

Thus, systematizing and classifying data are decision-making processes that universities use for complying with the highest management standards and achieving optimal results through interpreting data that were properly gathered.

A growing reality

Forbes Magazine has compiled statistics on the growing use of software related to Big Data and ancillary services. The results show the strong dynamic nature of the sector:

• Wikibon figures predict that the global market profits for Big Data software and services will go from USD 42 billion in 2018 to USD 103 billion in 2027.
• Demand for Big Data management software appears set to grow from USD 14 billion in 2018 to USD 46 billion in 2027 according to Statista.

In practice, data utilization is helping universities detect potential problems and challenges.

For example, the Times Higher Education magazine published the data experience of the University Innovation Alliance, a coalition of public research universities in the United States. Georgia State University is a member and one of the 11 pioneering institutions using Big Data to increase student success rates.

This coalition took ten years of data from 30,000 students including the grades and courses of Georgia State to create and calibrate a model to verify more than 800 variables to detect which students were more likely to drop out.

The results were immediate. The university used this information to make adjustments and reduce the average amount of time needed for students to graduate by half a semester, saving students approximately USD 15 million in tuition (2016 figures). For every percentage point increase in student retention, Georgia State makes about USD 3 million more return on investment (ROI).

Arizona State University is another institution that is part of the coalition. The Vice Provost for Student Success at the institution, Arthur Blakemore, told Forbes that management with Big Data is found in nearly every part of the university.

Management software to analyze large volumes of data is being used in order to address one of the biggest barriers to student success: understanding mathematics. The success rate went from approximately 65% to 85%.

4 tips for university management using data

To successfully manage institutional data in a useful and practical way, universities should apply the following best practices:

1. Structure data sets

This consists of defining the organization and interrelations of data and the set of operations that can be done with them in order to facilitate their handling.

2. Store data that is connected

Once these data are properly structured, they must be placed in data storage.

3. Create automated connections between data storage and analysis platforms

An automated connection with analysis platforms will enable a simplified data analysis, which done any other way would be very complex.

4. Include dashboards to help visualize data

This tool helps quickly group data and information to have an overview of what is going on within each organization.

Data management truly relates to a deep cultural change within an institution. Therefore, it is not enough to simply have technological solutions. An investment in data governance is fundamental.

As a result, the organization receives the following benefits:

• Optimize performance: Data can specifically demonstrate how to improve processes and analyze performance. This means the institution addresses problems with agility.
• Greater profitability: By analyzing data, the educational departments can make improvements and predict diverse scenarios, getting a leg up on the competition.
• Improved decision-making: The reasoning used by leadership for making decisions is no longer based on “beliefs”, rather on hard, reliable and real data.

Conclusion

Changing the way data is managed in Higher Education has becomes mandatory for institutions that wish to be successful over the long term.

Clear results that can be processed provide perspective and trust in decisions based on data analysis, which over the long term will translate into increased productivity and more efficient operations.

This means it is necessary to do initial research into the tools available for analyzing data that deliver information that can form the foundation of the chosen strategy.

The institutional perspective will be established as a function of data, and analysis will be made through reviewing current accomplishments along with the procedural planning needed to achieve goals.